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| <span class="mdl-layout-title toc">Table Of Contents</span> |
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| <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/index.html">Python Tutorials</a><ul> |
| <li class="toctree-l2"><a class="reference internal" href="../../../tutorials/getting-started/index.html">Getting Started</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/index.html">Crash Course</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/0-introduction.html">Introduction</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/1-nparray.html">Step 1: Manipulate data with NP on MXNet</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/2-create-nn.html">Step 2: Create a neural network</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/3-autograd.html">Step 3: Automatic differentiation with autograd</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/4-components.html">Step 4: Necessary components that are not in the network</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/5-datasets.html">Step 5: <code class="docutils literal notranslate"><span class="pre">Dataset</span></code>s and <code class="docutils literal notranslate"><span class="pre">DataLoader</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/5-datasets.html#Using-own-data-with-included-Datasets">Using own data with included <code class="docutils literal notranslate"><span class="pre">Dataset</span></code>s</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/5-datasets.html#Using-your-own-data-with-custom-Datasets">Using your own data with custom <code class="docutils literal notranslate"><span class="pre">Dataset</span></code>s</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/5-datasets.html#New-in-MXNet-2.0:-faster-C++-backend-dataloaders">New in MXNet 2.0: faster C++ backend dataloaders</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/6-train-nn.html">Step 6: Train a Neural Network</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/7-use-gpus.html">Step 7: Load and Run a NN using GPU</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/to-mxnet/index.html">Moving to MXNet from Other Frameworks</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/to-mxnet/pytorch.html">PyTorch vs Apache MXNet</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/gluon_from_experiment_to_deployment.html">Gluon: from experiment to deployment</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/gluon_migration_guide.html">Gluon2.0: Migration Guide</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/logistic_regression_explained.html">Logistic regression explained</a></li> |
| <li class="toctree-l3"><a class="reference external" href="https://mxnet.apache.org/api/python/docs/tutorials/packages/gluon/image/mnist.html">MNIST</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../../tutorials/packages/index.html">Packages</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/autograd/index.html">Automatic Differentiation</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/gluon/index.html">Gluon</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/index.html">Blocks</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/custom-layer.html">Custom Layers</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/hybridize.html">Hybridize</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/init.html">Initialization</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/naming.html">Parameter and Block Naming</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/nn.html">Layers and Blocks</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/parameters.html">Parameter Management</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/save_load_params.html">Saving and Loading Gluon Models</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/activations/activations.html">Activation Blocks</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/data/index.html">Data Tutorials</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/data_augmentation.html">Image Augmentation</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/datasets.html">Gluon <code class="docutils literal notranslate"><span class="pre">Dataset</span></code>s and <code class="docutils literal notranslate"><span class="pre">DataLoader</span></code></a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/datasets.html#Using-own-data-with-included-Datasets">Using own data with included <code class="docutils literal notranslate"><span class="pre">Dataset</span></code>s</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/datasets.html#Using-own-data-with-custom-Datasets">Using own data with custom <code class="docutils literal notranslate"><span class="pre">Dataset</span></code>s</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/datasets.html#Appendix:-Upgrading-from-Module-DataIter-to-Gluon-DataLoader">Appendix: Upgrading from Module <code class="docutils literal notranslate"><span class="pre">DataIter</span></code> to Gluon <code class="docutils literal notranslate"><span class="pre">DataLoader</span></code></a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/image/index.html">Image Tutorials</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/image/info_gan.html">Image similarity search with InfoGAN</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/image/mnist.html">Handwritten Digit Recognition</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/loss/index.html">Losses</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/loss/custom-loss.html">Custom Loss Blocks</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/loss/kl_divergence.html">Kullback-Leibler (KL) Divergence</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/loss/loss.html">Loss functions</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/text/index.html">Text Tutorials</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/text/gnmt.html">Google Neural Machine Translation</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/text/transformer.html">Machine Translation with Transformer</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/training/index.html">Training</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/training/fit_api_tutorial.html">MXNet Gluon Fit API</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/training/trainer.html">Trainer</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/training/learning_rates/index.html">Learning Rates</a><ul> |
| <li class="toctree-l6"><a class="reference internal" href="../../../tutorials/packages/gluon/training/learning_rates/learning_rate_finder.html">Learning Rate Finder</a></li> |
| <li class="toctree-l6"><a class="reference internal" href="../../../tutorials/packages/gluon/training/learning_rates/learning_rate_schedules.html">Learning Rate Schedules</a></li> |
| <li class="toctree-l6"><a class="reference internal" href="../../../tutorials/packages/gluon/training/learning_rates/learning_rate_schedules_advanced.html">Advanced Learning Rate Schedules</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/training/normalization/index.html">Normalization Blocks</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/kvstore/index.html">KVStore</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/kvstore/kvstore.html">Distributed Key-Value Store</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/legacy/index.html">Legacy</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/index.html">NDArray</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/01-ndarray-intro.html">An Intro: Manipulate Data the MXNet Way with NDArray</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/02-ndarray-operations.html">NDArray Operations</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/03-ndarray-contexts.html">NDArray Contexts</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/gotchas_numpy_in_mxnet.html">Gotchas using NumPy in Apache MXNet</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/sparse/index.html">Tutorials</a><ul> |
| <li class="toctree-l6"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/sparse/csr.html">CSRNDArray - NDArray in Compressed Sparse Row Storage Format</a></li> |
| <li class="toctree-l6"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/sparse/row_sparse.html">RowSparseNDArray - NDArray for Sparse Gradient Updates</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/np/index.html">What is NP on MXNet</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/np/cheat-sheet.html">The NP on MXNet cheat sheet</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/np/np-vs-numpy.html">Differences between NP on MXNet and NumPy</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/onnx/index.html">ONNX</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/onnx/fine_tuning_gluon.html">Fine-tuning an ONNX model</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/onnx/inference_on_onnx_model.html">Running inference on MXNet/Gluon from an ONNX model</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://mxnet.apache.org/api/python/docs/tutorials/deploy/export/onnx.html">Export ONNX Models</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/optimizer/index.html">Optimizers</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/viz/index.html">Visualization</a><ul> |
| <li class="toctree-l4"><a class="reference external" href="https://mxnet.apache.org/api/faq/visualize_graph">Visualize networks</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../../tutorials/performance/index.html">Performance</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/performance/compression/index.html">Compression</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/performance/compression/int8.html">Deploy with int-8</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://mxnet.apache.org/api/faq/float16">Float16</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://mxnet.apache.org/api/faq/gradient_compression">Gradient Compression</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://gluon-cv.mxnet.io/build/examples_deployment/int8_inference.html">GluonCV with Quantized Models</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/performance/backend/index.html">Accelerated Backend Tools</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/performance/backend/dnnl/index.html">oneDNN</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/performance/backend/dnnl/dnnl_readme.html">Install MXNet with oneDNN</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/performance/backend/dnnl/dnnl_quantization.html">oneDNN Quantization</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/performance/backend/dnnl/dnnl_quantization_inc.html">Improving accuracy with Intel® Neural Compressor</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/performance/backend/tvm.html">Use TVM</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/performance/backend/profiler.html">Profiling MXNet Models</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/performance/backend/amp.html">Using AMP: Automatic Mixed Precision</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../../tutorials/deploy/index.html">Deployment</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/deploy/export/index.html">Export</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/deploy/export/onnx.html">Exporting to ONNX format</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://gluon-cv.mxnet.io/build/examples_deployment/export_network.html">Export Gluon CV Models</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://mxnet.apache.org/api/python/docs/tutorials/packages/gluon/blocks/save_load_params.html">Save / Load Parameters</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/deploy/inference/index.html">Inference</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/deploy/inference/cpp.html">Deploy into C++</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/deploy/inference/image_classification_jetson.html">Image Classication using pretrained ResNet-50 model on Jetson module</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/deploy/run-on-aws/index.html">Run on AWS</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/deploy/run-on-aws/use_ec2.html">Run on an EC2 Instance</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/deploy/run-on-aws/use_sagemaker.html">Run on Amazon SageMaker</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/deploy/run-on-aws/cloud.html">MXNet on the Cloud</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../../tutorials/extend/index.html">Extend</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/extend/customop.html">Custom Numpy Operators</a></li> |
| <li class="toctree-l3"><a class="reference external" href="https://mxnet.apache.org/api/faq/new_op">New Operator Creation</a></li> |
| <li class="toctree-l3"><a class="reference external" href="https://mxnet.apache.org/api/faq/add_op_in_backend">New Operator in MXNet Backend</a></li> |
| <li class="toctree-l3"><a class="reference external" href="https://mxnet.apache.org/api/faq/using_rtc">Using RTC for CUDA kernels</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l1"><a class="reference internal" href="../../../api/index.html">Python API</a><ul> |
| <li class="toctree-l2"><a class="reference internal" href="../../../api/np/index.html">mxnet.np</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../../api/np/arrays.html">Array objects</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/arrays.ndarray.html">The N-dimensional array (<code class="xref py py-class docutils literal notranslate"><span class="pre">ndarray</span></code>)</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/arrays.indexing.html">Indexing</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../api/np/routines.html">Routines</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.array-creation.html">Array creation routines</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.eye.html">mxnet.np.eye</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.empty.html">mxnet.np.empty</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.full.html">mxnet.np.full</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.identity.html">mxnet.np.identity</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ones.html">mxnet.np.ones</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ones_like.html">mxnet.np.ones_like</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.zeros.html">mxnet.np.zeros</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.zeros_like.html">mxnet.np.zeros_like</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.array.html">mxnet.np.array</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.copy.html">mxnet.np.copy</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arange.html">mxnet.np.arange</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linspace.html">mxnet.np.linspace</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.logspace.html">mxnet.np.logspace</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.meshgrid.html">mxnet.np.meshgrid</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.tril.html">mxnet.np.tril</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.array-manipulation.html">Array manipulation routines</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.reshape.html">mxnet.np.reshape</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ravel.html">mxnet.np.ravel</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.flatten.html">mxnet.np.ndarray.flatten</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.swapaxes.html">mxnet.np.swapaxes</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.T.html">mxnet.np.ndarray.T</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.transpose.html">mxnet.np.transpose</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.moveaxis.html">mxnet.np.moveaxis</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.rollaxis.html">mxnet.np.rollaxis</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.expand_dims.html">mxnet.np.expand_dims</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.squeeze.html">mxnet.np.squeeze</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.broadcast_to.html">mxnet.np.broadcast_to</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.broadcast_arrays.html">mxnet.np.broadcast_arrays</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.atleast_1d.html">mxnet.np.atleast_1d</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.atleast_2d.html">mxnet.np.atleast_2d</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.atleast_3d.html">mxnet.np.atleast_3d</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.concatenate.html">mxnet.np.concatenate</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.stack.html">mxnet.np.stack</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.dstack.html">mxnet.np.dstack</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.vstack.html">mxnet.np.vstack</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.column_stack.html">mxnet.np.column_stack</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.hstack.html">mxnet.np.hstack</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.split.html">mxnet.np.split</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.hsplit.html">mxnet.np.hsplit</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.vsplit.html">mxnet.np.vsplit</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.array_split.html">mxnet.np.array_split</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.dsplit.html">mxnet.np.dsplit</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.tile.html">mxnet.np.tile</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.repeat.html">mxnet.np.repeat</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.unique.html">mxnet.np.unique</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.delete.html">mxnet.np.delete</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.insert.html">mxnet.np.insert</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.append.html">mxnet.np.append</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.resize.html">mxnet.np.resize</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.trim_zeros.html">mxnet.np.trim_zeros</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.reshape.html">mxnet.np.reshape</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.flip.html">mxnet.np.flip</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.roll.html">mxnet.np.roll</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.rot90.html">mxnet.np.rot90</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.fliplr.html">mxnet.np.fliplr</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.flipud.html">mxnet.np.flipud</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.io.html">Input and output</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.genfromtxt.html">mxnet.np.genfromtxt</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.tolist.html">mxnet.np.ndarray.tolist</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.set_printoptions.html">mxnet.np.set_printoptions</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.linalg.html">Linear algebra (<code class="xref py py-mod docutils literal notranslate"><span class="pre">numpy.linalg</span></code>)</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.dot.html">mxnet.np.dot</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.vdot.html">mxnet.np.vdot</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.inner.html">mxnet.np.inner</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.outer.html">mxnet.np.outer</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.tensordot.html">mxnet.np.tensordot</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.einsum.html">mxnet.np.einsum</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.multi_dot.html">mxnet.np.linalg.multi_dot</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.matmul.html">mxnet.np.matmul</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.matrix_power.html">mxnet.np.linalg.matrix_power</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.kron.html">mxnet.np.kron</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.svd.html">mxnet.np.linalg.svd</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.cholesky.html">mxnet.np.linalg.cholesky</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.qr.html">mxnet.np.linalg.qr</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.eig.html">mxnet.np.linalg.eig</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.eigh.html">mxnet.np.linalg.eigh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.eigvals.html">mxnet.np.linalg.eigvals</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.eigvalsh.html">mxnet.np.linalg.eigvalsh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.norm.html">mxnet.np.linalg.norm</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.trace.html">mxnet.np.trace</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.cond.html">mxnet.np.linalg.cond</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.det.html">mxnet.np.linalg.det</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.matrix_rank.html">mxnet.np.linalg.matrix_rank</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.slogdet.html">mxnet.np.linalg.slogdet</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.solve.html">mxnet.np.linalg.solve</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.tensorsolve.html">mxnet.np.linalg.tensorsolve</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.lstsq.html">mxnet.np.linalg.lstsq</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.inv.html">mxnet.np.linalg.inv</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.pinv.html">mxnet.np.linalg.pinv</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.tensorinv.html">mxnet.np.linalg.tensorinv</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.math.html">Mathematical functions</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.sin.html">mxnet.np.sin</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.cos.html">mxnet.np.cos</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.tan.html">mxnet.np.tan</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arcsin.html">mxnet.np.arcsin</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arccos.html">mxnet.np.arccos</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arctan.html">mxnet.np.arctan</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.degrees.html">mxnet.np.degrees</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.radians.html">mxnet.np.radians</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.hypot.html">mxnet.np.hypot</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arctan2.html">mxnet.np.arctan2</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.deg2rad.html">mxnet.np.deg2rad</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.rad2deg.html">mxnet.np.rad2deg</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.unwrap.html">mxnet.np.unwrap</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.sinh.html">mxnet.np.sinh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.cosh.html">mxnet.np.cosh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.tanh.html">mxnet.np.tanh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arcsinh.html">mxnet.np.arcsinh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arccosh.html">mxnet.np.arccosh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arctanh.html">mxnet.np.arctanh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.rint.html">mxnet.np.rint</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.fix.html">mxnet.np.fix</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.leaky_relu.html">mxnet.npx.leaky_relu</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.multibox_detection.html">mxnet.npx.multibox_detection</a></li> |
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| <span class="mdl-layout-title toc">Table Of Contents</span> |
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| |
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| <nav class="mdl-navigation"> |
| <ul> |
| <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/index.html">Python Tutorials</a><ul> |
| <li class="toctree-l2"><a class="reference internal" href="../../../tutorials/getting-started/index.html">Getting Started</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/index.html">Crash Course</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/0-introduction.html">Introduction</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/1-nparray.html">Step 1: Manipulate data with NP on MXNet</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/2-create-nn.html">Step 2: Create a neural network</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/3-autograd.html">Step 3: Automatic differentiation with autograd</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/4-components.html">Step 4: Necessary components that are not in the network</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/5-datasets.html">Step 5: <code class="docutils literal notranslate"><span class="pre">Dataset</span></code>s and <code class="docutils literal notranslate"><span class="pre">DataLoader</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/5-datasets.html#Using-own-data-with-included-Datasets">Using own data with included <code class="docutils literal notranslate"><span class="pre">Dataset</span></code>s</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/5-datasets.html#Using-your-own-data-with-custom-Datasets">Using your own data with custom <code class="docutils literal notranslate"><span class="pre">Dataset</span></code>s</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/5-datasets.html#New-in-MXNet-2.0:-faster-C++-backend-dataloaders">New in MXNet 2.0: faster C++ backend dataloaders</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/6-train-nn.html">Step 6: Train a Neural Network</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/7-use-gpus.html">Step 7: Load and Run a NN using GPU</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/to-mxnet/index.html">Moving to MXNet from Other Frameworks</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/to-mxnet/pytorch.html">PyTorch vs Apache MXNet</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/gluon_from_experiment_to_deployment.html">Gluon: from experiment to deployment</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/gluon_migration_guide.html">Gluon2.0: Migration Guide</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/logistic_regression_explained.html">Logistic regression explained</a></li> |
| <li class="toctree-l3"><a class="reference external" href="https://mxnet.apache.org/api/python/docs/tutorials/packages/gluon/image/mnist.html">MNIST</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../../tutorials/packages/index.html">Packages</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/autograd/index.html">Automatic Differentiation</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/gluon/index.html">Gluon</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/index.html">Blocks</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/custom-layer.html">Custom Layers</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/hybridize.html">Hybridize</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/init.html">Initialization</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/naming.html">Parameter and Block Naming</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/nn.html">Layers and Blocks</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/parameters.html">Parameter Management</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/save_load_params.html">Saving and Loading Gluon Models</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/activations/activations.html">Activation Blocks</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/data/index.html">Data Tutorials</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/data_augmentation.html">Image Augmentation</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/datasets.html">Gluon <code class="docutils literal notranslate"><span class="pre">Dataset</span></code>s and <code class="docutils literal notranslate"><span class="pre">DataLoader</span></code></a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/datasets.html#Using-own-data-with-included-Datasets">Using own data with included <code class="docutils literal notranslate"><span class="pre">Dataset</span></code>s</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/datasets.html#Using-own-data-with-custom-Datasets">Using own data with custom <code class="docutils literal notranslate"><span class="pre">Dataset</span></code>s</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/datasets.html#Appendix:-Upgrading-from-Module-DataIter-to-Gluon-DataLoader">Appendix: Upgrading from Module <code class="docutils literal notranslate"><span class="pre">DataIter</span></code> to Gluon <code class="docutils literal notranslate"><span class="pre">DataLoader</span></code></a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/image/index.html">Image Tutorials</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/image/info_gan.html">Image similarity search with InfoGAN</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/image/mnist.html">Handwritten Digit Recognition</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/loss/index.html">Losses</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/loss/custom-loss.html">Custom Loss Blocks</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/loss/kl_divergence.html">Kullback-Leibler (KL) Divergence</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/loss/loss.html">Loss functions</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/text/index.html">Text Tutorials</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/text/gnmt.html">Google Neural Machine Translation</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/text/transformer.html">Machine Translation with Transformer</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/training/index.html">Training</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/training/fit_api_tutorial.html">MXNet Gluon Fit API</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/training/trainer.html">Trainer</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/training/learning_rates/index.html">Learning Rates</a><ul> |
| <li class="toctree-l6"><a class="reference internal" href="../../../tutorials/packages/gluon/training/learning_rates/learning_rate_finder.html">Learning Rate Finder</a></li> |
| <li class="toctree-l6"><a class="reference internal" href="../../../tutorials/packages/gluon/training/learning_rates/learning_rate_schedules.html">Learning Rate Schedules</a></li> |
| <li class="toctree-l6"><a class="reference internal" href="../../../tutorials/packages/gluon/training/learning_rates/learning_rate_schedules_advanced.html">Advanced Learning Rate Schedules</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/training/normalization/index.html">Normalization Blocks</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/kvstore/index.html">KVStore</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/kvstore/kvstore.html">Distributed Key-Value Store</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/legacy/index.html">Legacy</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/index.html">NDArray</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/01-ndarray-intro.html">An Intro: Manipulate Data the MXNet Way with NDArray</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/02-ndarray-operations.html">NDArray Operations</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/03-ndarray-contexts.html">NDArray Contexts</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/gotchas_numpy_in_mxnet.html">Gotchas using NumPy in Apache MXNet</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/sparse/index.html">Tutorials</a><ul> |
| <li class="toctree-l6"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/sparse/csr.html">CSRNDArray - NDArray in Compressed Sparse Row Storage Format</a></li> |
| <li class="toctree-l6"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/sparse/row_sparse.html">RowSparseNDArray - NDArray for Sparse Gradient Updates</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/np/index.html">What is NP on MXNet</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/np/cheat-sheet.html">The NP on MXNet cheat sheet</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/np/np-vs-numpy.html">Differences between NP on MXNet and NumPy</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/onnx/index.html">ONNX</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/onnx/fine_tuning_gluon.html">Fine-tuning an ONNX model</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/onnx/inference_on_onnx_model.html">Running inference on MXNet/Gluon from an ONNX model</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://mxnet.apache.org/api/python/docs/tutorials/deploy/export/onnx.html">Export ONNX Models</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/optimizer/index.html">Optimizers</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/viz/index.html">Visualization</a><ul> |
| <li class="toctree-l4"><a class="reference external" href="https://mxnet.apache.org/api/faq/visualize_graph">Visualize networks</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../../tutorials/performance/index.html">Performance</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/performance/compression/index.html">Compression</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/performance/compression/int8.html">Deploy with int-8</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://mxnet.apache.org/api/faq/float16">Float16</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://mxnet.apache.org/api/faq/gradient_compression">Gradient Compression</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://gluon-cv.mxnet.io/build/examples_deployment/int8_inference.html">GluonCV with Quantized Models</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/performance/backend/index.html">Accelerated Backend Tools</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/performance/backend/dnnl/index.html">oneDNN</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/performance/backend/dnnl/dnnl_readme.html">Install MXNet with oneDNN</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/performance/backend/dnnl/dnnl_quantization.html">oneDNN Quantization</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/performance/backend/dnnl/dnnl_quantization_inc.html">Improving accuracy with Intel® Neural Compressor</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/performance/backend/tvm.html">Use TVM</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/performance/backend/profiler.html">Profiling MXNet Models</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/performance/backend/amp.html">Using AMP: Automatic Mixed Precision</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../../tutorials/deploy/index.html">Deployment</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/deploy/export/index.html">Export</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/deploy/export/onnx.html">Exporting to ONNX format</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://gluon-cv.mxnet.io/build/examples_deployment/export_network.html">Export Gluon CV Models</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://mxnet.apache.org/api/python/docs/tutorials/packages/gluon/blocks/save_load_params.html">Save / Load Parameters</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/deploy/inference/index.html">Inference</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/deploy/inference/cpp.html">Deploy into C++</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/deploy/inference/image_classification_jetson.html">Image Classication using pretrained ResNet-50 model on Jetson module</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/deploy/run-on-aws/index.html">Run on AWS</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/deploy/run-on-aws/use_ec2.html">Run on an EC2 Instance</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/deploy/run-on-aws/use_sagemaker.html">Run on Amazon SageMaker</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/deploy/run-on-aws/cloud.html">MXNet on the Cloud</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../../tutorials/extend/index.html">Extend</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/extend/customop.html">Custom Numpy Operators</a></li> |
| <li class="toctree-l3"><a class="reference external" href="https://mxnet.apache.org/api/faq/new_op">New Operator Creation</a></li> |
| <li class="toctree-l3"><a class="reference external" href="https://mxnet.apache.org/api/faq/add_op_in_backend">New Operator in MXNet Backend</a></li> |
| <li class="toctree-l3"><a class="reference external" href="https://mxnet.apache.org/api/faq/using_rtc">Using RTC for CUDA kernels</a></li> |
| </ul> |
| </li> |
| </ul> |
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| <li class="toctree-l1"><a class="reference internal" href="../../../api/index.html">Python API</a><ul> |
| <li class="toctree-l2"><a class="reference internal" href="../../../api/np/index.html">mxnet.np</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../../api/np/arrays.html">Array objects</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/arrays.ndarray.html">The N-dimensional array (<code class="xref py py-class docutils literal notranslate"><span class="pre">ndarray</span></code>)</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/arrays.indexing.html">Indexing</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="../../../api/np/routines.html">Routines</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.array-creation.html">Array creation routines</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.eye.html">mxnet.np.eye</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.empty.html">mxnet.np.empty</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.full.html">mxnet.np.full</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.identity.html">mxnet.np.identity</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ones.html">mxnet.np.ones</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ones_like.html">mxnet.np.ones_like</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.zeros.html">mxnet.np.zeros</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.zeros_like.html">mxnet.np.zeros_like</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.array.html">mxnet.np.array</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.copy.html">mxnet.np.copy</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arange.html">mxnet.np.arange</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linspace.html">mxnet.np.linspace</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.logspace.html">mxnet.np.logspace</a></li> |
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| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.array-manipulation.html">Array manipulation routines</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.reshape.html">mxnet.np.reshape</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ravel.html">mxnet.np.ravel</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.flatten.html">mxnet.np.ndarray.flatten</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.swapaxes.html">mxnet.np.swapaxes</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.T.html">mxnet.np.ndarray.T</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.transpose.html">mxnet.np.transpose</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.moveaxis.html">mxnet.np.moveaxis</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.rollaxis.html">mxnet.np.rollaxis</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.expand_dims.html">mxnet.np.expand_dims</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.squeeze.html">mxnet.np.squeeze</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.broadcast_to.html">mxnet.np.broadcast_to</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.broadcast_arrays.html">mxnet.np.broadcast_arrays</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.atleast_1d.html">mxnet.np.atleast_1d</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.atleast_2d.html">mxnet.np.atleast_2d</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.atleast_3d.html">mxnet.np.atleast_3d</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.concatenate.html">mxnet.np.concatenate</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.stack.html">mxnet.np.stack</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.dstack.html">mxnet.np.dstack</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.vstack.html">mxnet.np.vstack</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.column_stack.html">mxnet.np.column_stack</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.hstack.html">mxnet.np.hstack</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.split.html">mxnet.np.split</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.hsplit.html">mxnet.np.hsplit</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.vsplit.html">mxnet.np.vsplit</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.array_split.html">mxnet.np.array_split</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.dsplit.html">mxnet.np.dsplit</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.tile.html">mxnet.np.tile</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.repeat.html">mxnet.np.repeat</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.unique.html">mxnet.np.unique</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.delete.html">mxnet.np.delete</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.insert.html">mxnet.np.insert</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.append.html">mxnet.np.append</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.resize.html">mxnet.np.resize</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.trim_zeros.html">mxnet.np.trim_zeros</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.reshape.html">mxnet.np.reshape</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.flip.html">mxnet.np.flip</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.roll.html">mxnet.np.roll</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.rot90.html">mxnet.np.rot90</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.fliplr.html">mxnet.np.fliplr</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.flipud.html">mxnet.np.flipud</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.io.html">Input and output</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.genfromtxt.html">mxnet.np.genfromtxt</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.tolist.html">mxnet.np.ndarray.tolist</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.set_printoptions.html">mxnet.np.set_printoptions</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.linalg.html">Linear algebra (<code class="xref py py-mod docutils literal notranslate"><span class="pre">numpy.linalg</span></code>)</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.dot.html">mxnet.np.dot</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.vdot.html">mxnet.np.vdot</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.inner.html">mxnet.np.inner</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.outer.html">mxnet.np.outer</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.tensordot.html">mxnet.np.tensordot</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.einsum.html">mxnet.np.einsum</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.multi_dot.html">mxnet.np.linalg.multi_dot</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.matmul.html">mxnet.np.matmul</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.matrix_power.html">mxnet.np.linalg.matrix_power</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.kron.html">mxnet.np.kron</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.svd.html">mxnet.np.linalg.svd</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.cholesky.html">mxnet.np.linalg.cholesky</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.qr.html">mxnet.np.linalg.qr</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.eig.html">mxnet.np.linalg.eig</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.eigh.html">mxnet.np.linalg.eigh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.eigvals.html">mxnet.np.linalg.eigvals</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.eigvalsh.html">mxnet.np.linalg.eigvalsh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.norm.html">mxnet.np.linalg.norm</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.trace.html">mxnet.np.trace</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.cond.html">mxnet.np.linalg.cond</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.det.html">mxnet.np.linalg.det</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.matrix_rank.html">mxnet.np.linalg.matrix_rank</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.slogdet.html">mxnet.np.linalg.slogdet</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.solve.html">mxnet.np.linalg.solve</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.tensorsolve.html">mxnet.np.linalg.tensorsolve</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.lstsq.html">mxnet.np.linalg.lstsq</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.inv.html">mxnet.np.linalg.inv</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.pinv.html">mxnet.np.linalg.pinv</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.tensorinv.html">mxnet.np.linalg.tensorinv</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.math.html">Mathematical functions</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.sin.html">mxnet.np.sin</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.cos.html">mxnet.np.cos</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.tan.html">mxnet.np.tan</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arcsin.html">mxnet.np.arcsin</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arccos.html">mxnet.np.arccos</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arctan.html">mxnet.np.arctan</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.degrees.html">mxnet.np.degrees</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.radians.html">mxnet.np.radians</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.hypot.html">mxnet.np.hypot</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arctan2.html">mxnet.np.arctan2</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.deg2rad.html">mxnet.np.deg2rad</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.rad2deg.html">mxnet.np.rad2deg</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.unwrap.html">mxnet.np.unwrap</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.sinh.html">mxnet.np.sinh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.cosh.html">mxnet.np.cosh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.tanh.html">mxnet.np.tanh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arcsinh.html">mxnet.np.arcsinh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arccosh.html">mxnet.np.arccosh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arctanh.html">mxnet.np.arctanh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.rint.html">mxnet.np.rint</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.fix.html">mxnet.np.fix</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.floor.html">mxnet.np.floor</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ceil.html">mxnet.np.ceil</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.trunc.html">mxnet.np.trunc</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.around.html">mxnet.np.around</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.round_.html">mxnet.np.round_</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.sum.html">mxnet.np.sum</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.prod.html">mxnet.np.prod</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.cumsum.html">mxnet.np.cumsum</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.nanprod.html">mxnet.np.nanprod</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.nansum.html">mxnet.np.nansum</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.cumprod.html">mxnet.np.cumprod</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.nancumprod.html">mxnet.np.nancumprod</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.nancumsum.html">mxnet.np.nancumsum</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.diff.html">mxnet.np.diff</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ediff1d.html">mxnet.np.ediff1d</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.cross.html">mxnet.np.cross</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.trapz.html">mxnet.np.trapz</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.exp.html">mxnet.np.exp</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.expm1.html">mxnet.np.expm1</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.log.html">mxnet.np.log</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.log10.html">mxnet.np.log10</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.log2.html">mxnet.np.log2</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.log1p.html">mxnet.np.log1p</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.logaddexp.html">mxnet.np.logaddexp</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.i0.html">mxnet.np.i0</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ldexp.html">mxnet.np.ldexp</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.signbit.html">mxnet.np.signbit</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.copysign.html">mxnet.np.copysign</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.frexp.html">mxnet.np.frexp</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.spacing.html">mxnet.np.spacing</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.lcm.html">mxnet.np.lcm</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.gcd.html">mxnet.np.gcd</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.add.html">mxnet.np.add</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.reciprocal.html">mxnet.np.reciprocal</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.negative.html">mxnet.np.negative</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.divide.html">mxnet.np.divide</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.power.html">mxnet.np.power</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.subtract.html">mxnet.np.subtract</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.mod.html">mxnet.np.mod</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.multiply.html">mxnet.np.multiply</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.true_divide.html">mxnet.np.true_divide</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.remainder.html">mxnet.np.remainder</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.positive.html">mxnet.np.positive</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.float_power.html">mxnet.np.float_power</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.fmod.html">mxnet.np.fmod</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.modf.html">mxnet.np.modf</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.divmod.html">mxnet.np.divmod</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.floor_divide.html">mxnet.np.floor_divide</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.clip.html">mxnet.np.clip</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.sqrt.html">mxnet.np.sqrt</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.cbrt.html">mxnet.np.cbrt</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.square.html">mxnet.np.square</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.absolute.html">mxnet.np.absolute</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.sign.html">mxnet.np.sign</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.maximum.html">mxnet.np.maximum</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.minimum.html">mxnet.np.minimum</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.fabs.html">mxnet.np.fabs</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.heaviside.html">mxnet.np.heaviside</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.fmax.html">mxnet.np.fmax</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.fmin.html">mxnet.np.fmin</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.nan_to_num.html">mxnet.np.nan_to_num</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.interp.html">mxnet.np.interp</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/random/index.html">np.random</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.choice.html">mxnet.np.random.choice</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.shuffle.html">mxnet.np.random.shuffle</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.normal.html">mxnet.np.random.normal</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.uniform.html">mxnet.np.random.uniform</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.rand.html">mxnet.np.random.rand</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.randint.html">mxnet.np.random.randint</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.beta.html">mxnet.np.random.beta</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.chisquare.html">mxnet.np.random.chisquare</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.exponential.html">mxnet.np.random.exponential</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.f.html">mxnet.np.random.f</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.gamma.html">mxnet.np.random.gamma</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.gumbel.html">mxnet.np.random.gumbel</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.laplace.html">mxnet.np.random.laplace</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.logistic.html">mxnet.np.random.logistic</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.lognormal.html">mxnet.np.random.lognormal</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.multinomial.html">mxnet.np.random.multinomial</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.multivariate_normal.html">mxnet.np.random.multivariate_normal</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.pareto.html">mxnet.np.random.pareto</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.power.html">mxnet.np.random.power</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.rayleigh.html">mxnet.np.random.rayleigh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/random/generated/mxnet.np.random.weibull.html">mxnet.np.random.weibull</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.sort.html">Sorting, searching, and counting</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.sort.html">mxnet.np.ndarray.sort</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.sort.html">mxnet.np.sort</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.lexsort.html">mxnet.np.lexsort</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.argsort.html">mxnet.np.argsort</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.msort.html">mxnet.np.msort</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.partition.html">mxnet.np.partition</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.argpartition.html">mxnet.np.argpartition</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.argmax.html">mxnet.np.argmax</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.argmin.html">mxnet.np.argmin</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.nanargmax.html">mxnet.np.nanargmax</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.nanargmin.html">mxnet.np.nanargmin</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.argwhere.html">mxnet.np.argwhere</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.nonzero.html">mxnet.np.nonzero</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.flatnonzero.html">mxnet.np.flatnonzero</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.where.html">mxnet.np.where</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.searchsorted.html">mxnet.np.searchsorted</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.extract.html">mxnet.np.extract</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.count_nonzero.html">mxnet.np.count_nonzero</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.statistics.html">Statistics</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.min.html">mxnet.np.min</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.max.html">mxnet.np.max</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.amin.html">mxnet.np.amin</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.amax.html">mxnet.np.amax</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.nanmin.html">mxnet.np.nanmin</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.nanmax.html">mxnet.np.nanmax</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ptp.html">mxnet.np.ptp</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.percentile.html">mxnet.np.percentile</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.nanpercentile.html">mxnet.np.nanpercentile</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.quantile.html">mxnet.np.quantile</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.nanquantile.html">mxnet.np.nanquantile</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.mean.html">mxnet.np.mean</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.std.html">mxnet.np.std</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.var.html">mxnet.np.var</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.median.html">mxnet.np.median</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.average.html">mxnet.np.average</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.nanmedian.html">mxnet.np.nanmedian</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.nanstd.html">mxnet.np.nanstd</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.nanvar.html">mxnet.np.nanvar</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.corrcoef.html">mxnet.np.corrcoef</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.correlate.html">mxnet.np.correlate</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.cov.html">mxnet.np.cov</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.histogram.html">mxnet.np.histogram</a></li> |
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| |
| <h1>Source code for mxnet.symbol.symbol</h1><div class="highlight"><pre> |
| <span></span><span class="c1"># Licensed to the Apache Software Foundation (ASF) under one</span> |
| <span class="c1"># or more contributor license agreements. See the NOTICE file</span> |
| <span class="c1"># distributed with this work for additional information</span> |
| <span class="c1"># regarding copyright ownership. The ASF licenses this file</span> |
| <span class="c1"># to you under the Apache License, Version 2.0 (the</span> |
| <span class="c1"># "License"); you may not use this file except in compliance</span> |
| <span class="c1"># with the License. You may obtain a copy of the License at</span> |
| <span class="c1">#</span> |
| <span class="c1"># http://www.apache.org/licenses/LICENSE-2.0</span> |
| <span class="c1">#</span> |
| <span class="c1"># Unless required by applicable law or agreed to in writing,</span> |
| <span class="c1"># software distributed under the License is distributed on an</span> |
| <span class="c1"># "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY</span> |
| <span class="c1"># KIND, either express or implied. See the License for the</span> |
| <span class="c1"># specific language governing permissions and limitations</span> |
| <span class="c1"># under the License.</span> |
| |
| <span class="c1"># coding: utf-8</span> |
| <span class="c1"># pylint: disable=invalid-name, protected-access, too-many-arguments, too-many-lines</span> |
| <span class="c1"># pylint: disable=import-error, no-name-in-module</span> |
| <span class="sd">"""Symbolic configuration API of MXNet."""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="kn">from</span> <span class="nn">__builtin__</span> <span class="kn">import</span> <span class="nb">slice</span> <span class="k">as</span> <span class="n">py_slice</span> |
| <span class="k">except</span> <span class="ne">ImportError</span><span class="p">:</span> |
| <span class="kn">from</span> <span class="nn">builtins</span> <span class="kn">import</span> <span class="nb">slice</span> <span class="k">as</span> <span class="n">py_slice</span> |
| |
| <span class="kn">from</span> <span class="nn">array</span> <span class="kn">import</span> <span class="n">array</span> |
| <span class="kn">import</span> <span class="nn">ctypes</span> |
| <span class="kn">import</span> <span class="nn">warnings</span> |
| <span class="kn">from</span> <span class="nn">numbers</span> <span class="kn">import</span> <span class="n">Number</span> |
| <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">_numpy</span> <span class="c1"># pylint: disable=relative-import</span> |
| |
| <span class="kn">from</span> <span class="nn">..</span> <span class="kn">import</span> <span class="n">attribute</span> |
| <span class="kn">from</span> <span class="nn">..base</span> <span class="kn">import</span> <span class="n">_LIB</span><span class="p">,</span> <span class="n">numeric_types</span><span class="p">,</span> <span class="n">c_array</span><span class="p">,</span> <span class="n">c_array_buf</span><span class="p">,</span> <span class="n">c_str</span><span class="p">,</span> <span class="n">c_str_array</span><span class="p">,</span> <span class="n">c_handle_array</span> |
| <span class="kn">from</span> <span class="nn">..base</span> <span class="kn">import</span> <span class="n">mx_uint</span><span class="p">,</span> <span class="n">py_str</span><span class="p">,</span> <span class="n">string_types</span><span class="p">,</span> <span class="n">integer_types</span><span class="p">,</span> <span class="n">mx_int</span><span class="p">,</span> <span class="n">mx_int64</span> |
| <span class="kn">from</span> <span class="nn">..base</span> <span class="kn">import</span> <span class="n">NDArrayHandle</span><span class="p">,</span> <span class="n">SymbolHandle</span> |
| <span class="kn">from</span> <span class="nn">..base</span> <span class="kn">import</span> <span class="n">check_call</span><span class="p">,</span> <span class="n">MXNetError</span><span class="p">,</span> <span class="n">NotImplementedForSymbol</span> |
| <span class="kn">from</span> <span class="nn">..device</span> <span class="kn">import</span> <span class="n">Device</span><span class="p">,</span> <span class="n">current_device</span> |
| <span class="kn">from</span> <span class="nn">..ndarray</span> <span class="kn">import</span> <span class="n">NDArray</span><span class="p">,</span> <span class="n">dtype_np_to_mx</span><span class="p">,</span> <span class="n">dtype_mx_to_np</span><span class="p">,</span> <span class="n">is_mx_dtype</span> |
| <span class="kn">from</span> <span class="nn">..ndarray.ndarray</span> <span class="kn">import</span> <span class="n">_STORAGE_TYPE_STR_TO_ID</span><span class="p">,</span> <span class="n">_int64_enabled</span><span class="p">,</span> <span class="n">_SIGNED_INT32_UPPER_LIMIT</span> |
| <span class="kn">from</span> <span class="nn">..executor</span> <span class="kn">import</span> <span class="n">Executor</span> |
| <span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">_internal</span> |
| <span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">op</span> |
| <span class="kn">from</span> <span class="nn">._internal</span> <span class="kn">import</span> <span class="n">SymbolBase</span><span class="p">,</span> <span class="n">_set_symbol_class</span> |
| <span class="kn">from</span> <span class="nn">..util</span> <span class="kn">import</span> <span class="n">is_np_shape</span> |
| <span class="kn">from</span> <span class="nn">..profiler</span> <span class="kn">import</span> <span class="n">scope</span> <span class="k">as</span> <span class="n">_profiler_scope</span> |
| <span class="kn">from</span> <span class="nn">..profiler</span> <span class="kn">import</span> <span class="n">_current_scope</span> <span class="k">as</span> <span class="n">_current_profiler_scope</span> |
| |
| <span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"Symbol"</span><span class="p">,</span> <span class="s2">"var"</span><span class="p">,</span> <span class="s2">"Variable"</span><span class="p">,</span> <span class="s2">"Group"</span><span class="p">,</span> <span class="s2">"load"</span><span class="p">,</span> <span class="s2">"fromjson"</span><span class="p">,</span> |
| <span class="s2">"pow"</span><span class="p">,</span> <span class="s2">"power"</span><span class="p">,</span> <span class="s2">"maximum"</span><span class="p">,</span> <span class="s2">"minimum"</span><span class="p">,</span> <span class="s2">"hypot"</span><span class="p">,</span> <span class="s2">"eye"</span><span class="p">,</span> <span class="s2">"zeros"</span><span class="p">,</span> |
| <span class="s2">"ones"</span><span class="p">,</span> <span class="s2">"full"</span><span class="p">,</span> <span class="s2">"arange"</span><span class="p">,</span> <span class="s2">"linspace"</span><span class="p">,</span> <span class="s2">"histogram"</span><span class="p">,</span> <span class="s2">"split_v2"</span><span class="p">]</span> |
| |
| |
| <div class="viewcode-block" id="Symbol"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol">[docs]</a><span class="k">class</span> <span class="nc">Symbol</span><span class="p">(</span><span class="n">SymbolBase</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Symbol is symbolic graph of the mxnet."""</span> |
| <span class="c1"># disable dictionary storage, also do not have parent type.</span> |
| <span class="c1"># pylint: disable=no-member</span> |
| <span class="vm">__slots__</span> <span class="o">=</span> <span class="p">[]</span> |
| |
| <span class="c1"># Make numpy functions return Symbol instead of numpy object array</span> |
| <span class="n">__array_priority__</span> <span class="o">=</span> <span class="mf">1000.0</span> |
| |
| <div class="viewcode-block" id="Symbol.as_np_ndarray"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.as_np_ndarray">[docs]</a> <span class="k">def</span> <span class="nf">as_np_ndarray</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convert mx.sym.Symbol to mx.sym.np._Symbol."""</span> |
| <span class="kn">from</span> <span class="nn">.numpy</span> <span class="kn">import</span> <span class="n">_Symbol</span> |
| <span class="n">hdl</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXShallowCopySymbol</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">hdl</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="n">_Symbol</span><span class="p">(</span><span class="n">hdl</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.as_nd_ndarray"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.as_nd_ndarray">[docs]</a> <span class="k">def</span> <span class="nf">as_nd_ndarray</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Returns self. For the convenience of conversion between legacy and np symbols."""</span> |
| <span class="k">return</span> <span class="bp">self</span></div> |
| |
| <span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Gets a string representation of the symbol."""</span> |
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_alive</span><span class="p">:</span> |
| <span class="n">name</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> |
| <span class="k">if</span> <span class="n">name</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">name</span> <span class="o">=</span> <span class="s1">', '</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="n">i</span><span class="o">.</span><span class="n">name</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="bp">self</span><span class="p">])</span> |
| <span class="k">return</span> <span class="sa">f</span><span class="s1">'<</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="si">}</span><span class="s1"> group [</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s1">]>'</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">return</span> <span class="sa">f</span><span class="s1">'<</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="si">}</span><span class="s1"> </span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s1">>'</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">return</span> <span class="s1">'<FREED </span><span class="si">{}</span><span class="s1">>'</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Returns a generator object of symbol.</span> |
| |
| <span class="sd"> One can loop through the returned object list to get outputs.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> a = mx.sym.Variable('a')</span> |
| <span class="sd"> >>> b = mx.sym.Variable('b')</span> |
| <span class="sd"> >>> c = a+b</span> |
| <span class="sd"> >>> d = mx.sym.Variable('d')</span> |
| <span class="sd"> >>> e = d+c</span> |
| <span class="sd"> >>> out = e.get_children()</span> |
| <span class="sd"> >>> out</span> |
| <span class="sd"> <Symbol Grouped></span> |
| <span class="sd"> >>> for i in out:</span> |
| <span class="sd"> ... print(i)</span> |
| <span class="sd"> ...</span> |
| <span class="sd"> <Symbol d></span> |
| <span class="sd"> <Symbol _plus0></span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="p">(</span><span class="bp">self</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">)))</span> |
| |
| <span class="k">def</span> <span class="fm">__abs__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__abs__() <=> abs(x) <=> x.abs() <=> mx.symbol.abs(x, y)"""</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">abs</span><span class="p">()</span> |
| |
| <span class="k">def</span> <span class="fm">__add__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__add__(y) <=> x+y</span> |
| |
| <span class="sd"> Scalar input is supported.</span> |
| <span class="sd"> Broadcasting is not supported. Use `broadcast_add` instead. """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_Plus</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_PlusScalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__bool__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">NotImplementedForSymbol</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="fm">__bool__</span><span class="p">,</span> <span class="s1">'bool'</span><span class="p">)</span> |
| |
| <span class="n">__nonzero__</span> <span class="o">=</span> <span class="fm">__bool__</span> |
| |
| <span class="k">def</span> <span class="fm">__iadd__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">NotImplementedForSymbol</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="fm">__iadd__</span><span class="p">,</span> <span class="s1">'+='</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__radd__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="fm">__add__</span><span class="p">(</span><span class="n">other</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__sub__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__sub__(y) <=> x-y</span> |
| |
| <span class="sd"> Scalar input is supported.</span> |
| <span class="sd"> Broadcasting is not supported. Use `broadcast_sub` instead. """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_Minus</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_MinusScalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__isub__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">NotImplementedForSymbol</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="fm">__isub__</span><span class="p">,</span> <span class="s1">'-='</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__rsub__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__rsub__(y) <=> y-x</span> |
| |
| <span class="sd"> Only `NDArray` is supported for now.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> x = mx.nd.ones((2,3))*3</span> |
| <span class="sd"> >>> y = mx.nd.ones((2,3))</span> |
| <span class="sd"> >>> x.__rsub__(y).asnumpy()</span> |
| <span class="sd"> array([[-2., -2., -2.],</span> |
| <span class="sd"> [-2., -2., -2.]], dtype=float32)</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">other</span><span class="o">.</span><span class="fm">__sub__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_RMinusScalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__mul__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__mul__(y) <=> x*y</span> |
| |
| <span class="sd"> Scalar input is supported.</span> |
| <span class="sd"> Broadcasting is not supported. Use `broadcast_mul` instead. """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_Mul</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_MulScalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__imul__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">NotImplementedForSymbol</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="fm">__imul__</span><span class="p">,</span> <span class="s1">'*='</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__rmul__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="fm">__mul__</span><span class="p">(</span><span class="n">other</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">__div__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__div__(y) <=> x/y</span> |
| |
| <span class="sd"> Scalar input is supported.</span> |
| <span class="sd"> Broadcasting is not supported. Use `broadcast_div` instead. """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_Div</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_DivScalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">__rdiv__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__rdiv__(y) <=> y/x</span> |
| |
| <span class="sd"> Only `NDArray` is supported for now.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> x = mx.nd.ones((2,3))*3</span> |
| <span class="sd"> >>> y = mx.nd.ones((2,3))</span> |
| <span class="sd"> >>> x.__rdiv__(y).asnumpy()</span> |
| <span class="sd"> array([[ 0.33333334, 0.33333334, 0.33333334],</span> |
| <span class="sd"> [ 0.33333334, 0.33333334, 0.33333334]], dtype=float32)</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">other</span><span class="o">.</span><span class="fm">__truediv__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_RDivScalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__mod__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__mod__(y) <=> x%y</span> |
| |
| <span class="sd"> Scalar input is supported.</span> |
| <span class="sd"> Broadcasting is not supported. Use `broadcast_mod` instead. """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_Mod</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_ModScalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__rmod__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__rmod__(y) <=> y%x</span> |
| |
| <span class="sd"> Only `NDArray` is supported for now.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> x = mx.nd.ones((2,3))*3</span> |
| <span class="sd"> >>> y = mx.nd.ones((2,3))</span> |
| <span class="sd"> >>> x.__rmod__(y).asnumpy()</span> |
| <span class="sd"> array([[ 1., 1., 1.,</span> |
| <span class="sd"> [ 1., 1., 1., dtype=float32)</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">other</span><span class="o">.</span><span class="fm">__mod__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_RModScalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">__idiv__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">NotImplementedForSymbol</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">__idiv__</span><span class="p">,</span> <span class="s1">'/='</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__truediv__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">__div__</span><span class="p">(</span><span class="n">other</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__rtruediv__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">__rdiv__</span><span class="p">(</span><span class="n">other</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__itruediv__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">NotImplementedForSymbol</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="fm">__itruediv__</span><span class="p">,</span> <span class="s1">'/='</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__pow__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__pow__(y) <=> x**y</span> |
| |
| <span class="sd"> Scalar input is supported.</span> |
| <span class="sd"> Broadcasting is not supported. Use `broadcast_pow` instead. """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_Power</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_PowerScalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__rpow__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__rpow__(y) <=> y ** x"""</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">other</span><span class="o">.</span><span class="fm">__pow__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> |
| <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_rpower_scalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__neg__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__neg__() <=> -x</span> |
| |
| <span class="sd"> Numerical negative, element-wise.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> a = mx.sym.Variable('a')</span> |
| <span class="sd"> >>> a</span> |
| <span class="sd"> <Symbol a></span> |
| <span class="sd"> >>> -a</span> |
| <span class="sd"> <Symbol _mulscalar0></span> |
| <span class="sd"> >>> a_neg = a.__neg__()</span> |
| <span class="sd"> >>> c = a_neg*b</span> |
| <span class="sd"> >>> ex = c.eval(ctx=mx.cpu(), a=mx.nd.ones([2,3]), b=mx.nd.ones([2,3]))</span> |
| <span class="sd"> >>> ex[0].asnumpy()</span> |
| <span class="sd"> array([[-1., -1., -1.],</span> |
| <span class="sd"> [-1., -1., -1.]], dtype=float32)</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="fm">__mul__</span><span class="p">(</span><span class="o">-</span><span class="mf">1.0</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">__copy__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">__deepcopy__</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">__deepcopy__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Returns a deep copy of the input object.</span> |
| |
| <span class="sd"> This function returns a deep copy of the input object including the current state</span> |
| <span class="sd"> of all its parameters such as weights, biases, etc.</span> |
| |
| <span class="sd"> Any changes made to the deep copy do not reflect in the original object.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> import copy</span> |
| <span class="sd"> >>> data = mx.sym.Variable('data')</span> |
| <span class="sd"> >>> data_1 = copy.deepcopy(data)</span> |
| <span class="sd"> >>> data_1 = 2*data</span> |
| <span class="sd"> >>> data_1.tojson()</span> |
| <span class="sd"> >>> data_1 is data # Data got modified</span> |
| <span class="sd"> False</span> |
| <span class="sd"> """</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolCopy</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">handle</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="n">Symbol</span><span class="p">(</span><span class="n">handle</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__eq__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__eq__(y) <=> x==y</span> |
| |
| <span class="sd"> Scalar input is supported.</span> |
| <span class="sd"> Broadcasting is not supported. Use `broadcast_equal` instead. """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_equal</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">numeric_types</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_equal_scalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__ne__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__ne__(y) <=> x!=y</span> |
| |
| <span class="sd"> Scalar input is supported.</span> |
| <span class="sd"> Broadcasting is not supported. Use `broadcast_not_equal` instead. """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_not_equal</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">numeric_types</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_not_equal_scalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__gt__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__gt__(y) <=> x>y</span> |
| |
| <span class="sd"> Scalar input is supported.</span> |
| <span class="sd"> Broadcasting is not supported. Use `broadcast_greater` instead. """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_greater</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">numeric_types</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_greater_scalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__ge__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__ge__(y) <=> x>=y</span> |
| |
| <span class="sd"> Scalar input is supported.</span> |
| <span class="sd"> Broadcasting is not supported. Use `broadcast_greater_equal` instead. """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_greater_equal</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">numeric_types</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_greater_equal_scalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__lt__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__lt__(y) <=> x<y</span> |
| |
| <span class="sd"> Scalar input is supported.</span> |
| <span class="sd"> Broadcasting is not supported. Use `broadcast_lesser` instead. """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_lesser</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">numeric_types</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_lesser_scalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__le__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__le__(y) <=> x<=y</span> |
| |
| <span class="sd"> Scalar input is supported.</span> |
| <span class="sd"> Broadcasting is not supported. Use `broadcast_lesser_equal` instead. """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_lesser_equal</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">numeric_types</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_lesser_equal_scalar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">other</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'type </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">))</span><span class="si">}</span><span class="s1"> not supported'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">handle</span> |
| <span class="k">if</span> <span class="n">handle</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="k">return</span> <span class="p">{</span><span class="s1">'handle'</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">tojson</span><span class="p">()}</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">return</span> <span class="p">{</span><span class="s1">'handle'</span><span class="p">:</span> <span class="kc">None</span><span class="p">}</span> |
| |
| <span class="k">def</span> <span class="nf">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">):</span> |
| <span class="c1"># pylint: disable=assigning-non-slot</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="n">state</span><span class="p">[</span><span class="s1">'handle'</span><span class="p">]</span> |
| <span class="k">if</span> <span class="n">handle</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">json_str</span> <span class="o">=</span> <span class="n">handle</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolCreateFromJSON</span><span class="p">(</span><span class="n">c_str</span><span class="p">(</span><span class="n">json_str</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">handle</span><span class="p">)))</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span> <span class="o">=</span> <span class="n">handle</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span> <span class="o">=</span> <span class="kc">None</span> |
| |
| <span class="k">def</span> <span class="fm">__call__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Composes symbol using inputs.</span> |
| |
| <span class="sd"> x.__call__(y, z) <=> x(y,z)</span> |
| |
| <span class="sd"> This function internally calls `_compose` to compose the symbol and</span> |
| <span class="sd"> returns the composed symbol.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> data = mx.symbol.Variable('data')</span> |
| <span class="sd"> >>> net1 = mx.symbol.FullyConnected(data=data, name='fc1', num_hidden=10)</span> |
| <span class="sd"> >>> net2 = mx.symbol.FullyConnected(name='fc3', num_hidden=10)</span> |
| <span class="sd"> >>> composed = net2(fc3_data=net1, name='composed')</span> |
| <span class="sd"> >>> composed</span> |
| <span class="sd"> <Symbol composed></span> |
| <span class="sd"> >>> called = net2.__call__(fc3_data=net1, name='composed')</span> |
| <span class="sd"> >>> called</span> |
| <span class="sd"> <Symbol composed></span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> args:</span> |
| <span class="sd"> Positional arguments.</span> |
| |
| <span class="sd"> kwargs:</span> |
| <span class="sd"> Keyword arguments.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> The resulting symbol.</span> |
| <span class="sd"> """</span> |
| <span class="n">s</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">__copy__</span><span class="p">()</span> |
| <span class="n">s</span><span class="o">.</span><span class="n">_compose</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> |
| <span class="k">return</span> <span class="n">s</span> |
| |
| <span class="k">def</span> <span class="nf">_compose</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Composes symbol using inputs.</span> |
| |
| <span class="sd"> x._compose(y, z) <=> x(y,z)</span> |
| |
| <span class="sd"> This function mutates the current symbol.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> data = mx.symbol.Variable('data')</span> |
| <span class="sd"> >>> net1 = mx.symbol.FullyConnected(data=data, name='fc1', num_hidden=10)</span> |
| <span class="sd"> >>> net2 = mx.symbol.FullyConnected(name='fc3', num_hidden=10)</span> |
| <span class="sd"> >>> net2</span> |
| <span class="sd"> <Symbol fc3></span> |
| <span class="sd"> >>> net2._compose(fc3_data=net1, name='composed')</span> |
| <span class="sd"> >>> net2</span> |
| <span class="sd"> <Symbol composed></span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> args:</span> |
| <span class="sd"> Positional arguments.</span> |
| |
| <span class="sd"> kwargs:</span> |
| <span class="sd"> Keyword arguments.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> The resulting symbol.</span> |
| <span class="sd"> """</span> |
| <span class="n">name</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'name'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> |
| |
| <span class="k">if</span> <span class="n">name</span><span class="p">:</span> |
| <span class="n">name</span> <span class="o">=</span> <span class="n">c_str</span><span class="p">(</span><span class="n">name</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">'compose only accept input Symbols </span><span class="se">\</span> |
| <span class="s1"> either as positional or keyword arguments, not both'</span><span class="p">)</span> |
| |
| <span class="k">for</span> <span class="n">arg</span> <span class="ow">in</span> <span class="n">args</span><span class="p">:</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">arg</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">'Compose expect `Symbol` as arguments'</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">val</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">values</span><span class="p">():</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">val</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">'Compose expect `Symbol` as arguments'</span><span class="p">)</span> |
| |
| <span class="n">num_args</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">)</span> <span class="o">+</span> <span class="nb">len</span><span class="p">(</span><span class="n">kwargs</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span> |
| <span class="n">keys</span> <span class="o">=</span> <span class="n">c_str_array</span><span class="p">(</span><span class="n">kwargs</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span> |
| <span class="n">args</span> <span class="o">=</span> <span class="n">c_handle_array</span><span class="p">(</span><span class="n">kwargs</span><span class="o">.</span><span class="n">values</span><span class="p">())</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">keys</span> <span class="o">=</span> <span class="kc">None</span> |
| <span class="n">args</span> <span class="o">=</span> <span class="n">c_handle_array</span><span class="p">(</span><span class="n">args</span><span class="p">)</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolCompose</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">num_args</span><span class="p">,</span> <span class="n">keys</span><span class="p">,</span> <span class="n">args</span><span class="p">))</span> |
| |
| <span class="k">def</span> <span class="fm">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">index</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""x.__getitem__(i) <=> x[i]</span> |
| |
| <span class="sd"> Returns a sliced view of the input symbol.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> a = mx.sym.var('a')</span> |
| <span class="sd"> >>> a.__getitem__(0)</span> |
| <span class="sd"> <Symbol a></span> |
| <span class="sd"> >>> a[0]</span> |
| <span class="sd"> <Symbol a></span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> index : int or str</span> |
| <span class="sd"> Indexing key</span> |
| |
| <span class="sd"> """</span> |
| <span class="n">output_count</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">index</span><span class="p">,</span> <span class="n">py_slice</span><span class="p">):</span> |
| <span class="n">start</span> <span class="o">=</span> <span class="mi">0</span> <span class="k">if</span> <span class="n">index</span><span class="o">.</span><span class="n">start</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="n">index</span><span class="o">.</span><span class="n">start</span> |
| <span class="n">stop</span> <span class="o">=</span> <span class="n">output_count</span> <span class="k">if</span> <span class="n">index</span><span class="o">.</span><span class="n">stop</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="n">index</span><span class="o">.</span><span class="n">stop</span> |
| <span class="n">step</span> <span class="o">=</span> <span class="mi">1</span> <span class="k">if</span> <span class="n">index</span><span class="o">.</span><span class="n">step</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="n">index</span><span class="o">.</span><span class="n">step</span> |
| <span class="k">return</span> <span class="n">Group</span><span class="p">([</span><span class="bp">self</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">stop</span><span class="p">,</span> <span class="n">step</span><span class="p">)])</span> |
| |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">index</span><span class="p">,</span> <span class="n">string_types</span><span class="p">):</span> |
| <span class="c1"># Returning this list of names is expensive. Some symbols may have hundreds of outputs</span> |
| <span class="n">output_names</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">()</span> |
| <span class="n">idx</span> <span class="o">=</span> <span class="kc">None</span> |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">output_names</span><span class="p">):</span> |
| <span class="k">if</span> <span class="n">name</span> <span class="o">==</span> <span class="n">index</span><span class="p">:</span> |
| <span class="k">if</span> <span class="n">idx</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'There are multiple outputs with name </span><span class="se">\"</span><span class="si">{</span><span class="n">index</span><span class="si">}</span><span class="se">\"</span><span class="s1">'</span><span class="p">)</span> |
| <span class="n">idx</span> <span class="o">=</span> <span class="n">i</span> |
| <span class="k">if</span> <span class="n">idx</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Cannot find output that matches name </span><span class="se">\"</span><span class="si">{</span><span class="n">index</span><span class="si">}</span><span class="se">\"</span><span class="s1">'</span><span class="p">)</span> |
| <span class="n">index</span> <span class="o">=</span> <span class="n">idx</span> |
| |
| <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">index</span><span class="p">,</span> <span class="nb">int</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">'Symbol only support integer index to fetch i-th output'</span><span class="p">)</span> |
| <span class="k">if</span> <span class="n">index</span> <span class="o">>=</span> <span class="n">output_count</span><span class="p">:</span> |
| <span class="c1"># Important, python determines the end by this exception</span> |
| <span class="k">raise</span> <span class="ne">IndexError</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolGetOutput</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">mx_uint</span><span class="p">(</span><span class="n">index</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">handle</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="n">Symbol</span><span class="p">(</span><span class="n">handle</span><span class="o">=</span><span class="n">handle</span><span class="p">)</span> |
| |
| <span class="nd">@property</span> |
| <span class="k">def</span> <span class="nf">name</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Gets name string from the symbol, this function only works for non-grouped symbol.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> value : str</span> |
| <span class="sd"> The name of this symbol, returns ``None`` for grouped symbol.</span> |
| <span class="sd"> """</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">()</span> |
| <span class="n">success</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_int</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolGetName</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">ret</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">success</span><span class="p">)))</span> |
| <span class="k">if</span> <span class="n">success</span><span class="o">.</span><span class="n">value</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span> |
| <span class="k">return</span> <span class="n">py_str</span><span class="p">(</span><span class="n">ret</span><span class="o">.</span><span class="n">value</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">return</span> <span class="kc">None</span> |
| |
| <div class="viewcode-block" id="Symbol.attr"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.attr">[docs]</a> <span class="k">def</span> <span class="nf">attr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">key</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Returns the attribute string for corresponding input key from the symbol.</span> |
| |
| <span class="sd"> This function only works for non-grouped symbols.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> data = mx.sym.Variable('data', attr={'mood': 'angry'})</span> |
| <span class="sd"> >>> data.attr('mood')</span> |
| <span class="sd"> 'angry'</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> key : str</span> |
| <span class="sd"> The key corresponding to the desired attribute.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> value : str</span> |
| <span class="sd"> The desired attribute value, returns ``None`` if the attribute does not exist.</span> |
| <span class="sd"> """</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">()</span> |
| <span class="n">success</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_int</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolGetAttr</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">c_str</span><span class="p">(</span><span class="n">key</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">ret</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">success</span><span class="p">)))</span> |
| <span class="k">if</span> <span class="n">success</span><span class="o">.</span><span class="n">value</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span> |
| <span class="k">return</span> <span class="n">py_str</span><span class="p">(</span><span class="n">ret</span><span class="o">.</span><span class="n">value</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">return</span> <span class="kc">None</span></div> |
| |
| <div class="viewcode-block" id="Symbol.list_attr"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.list_attr">[docs]</a> <span class="k">def</span> <span class="nf">list_attr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">recursive</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Gets all attributes from the symbol.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> data = mx.sym.Variable('data', attr={'mood': 'angry'})</span> |
| <span class="sd"> >>> data.list_attr()</span> |
| <span class="sd"> {'mood': 'angry'}</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> ret : Dict of str to str</span> |
| <span class="sd"> A dictionary mapping attribute keys to values.</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="n">recursive</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">DeprecationWarning</span><span class="p">(</span><span class="s2">"Symbol.list_attr with recursive=True has been deprecated. "</span> |
| <span class="s2">"Please use attr_dict instead."</span><span class="p">)</span> |
| <span class="n">size</span> <span class="o">=</span> <span class="n">mx_uint</span><span class="p">()</span> |
| <span class="n">pairs</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">)()</span> |
| <span class="n">f_handle</span> <span class="o">=</span> <span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolListAttrShallow</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">f_handle</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">size</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">pairs</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="p">{</span><span class="n">py_str</span><span class="p">(</span><span class="n">pairs</span><span class="p">[</span><span class="n">i</span> <span class="o">*</span> <span class="mi">2</span><span class="p">]):</span> <span class="n">py_str</span><span class="p">(</span><span class="n">pairs</span><span class="p">[</span><span class="n">i</span> <span class="o">*</span> <span class="mi">2</span> <span class="o">+</span> <span class="mi">1</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">size</span><span class="o">.</span><span class="n">value</span><span class="p">)}</span></div> |
| |
| <div class="viewcode-block" id="Symbol.attr_dict"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.attr_dict">[docs]</a> <span class="k">def</span> <span class="nf">attr_dict</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Recursively gets all attributes from the symbol and its children.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> a = mx.sym.Variable('a', attr={'a1':'a2'})</span> |
| <span class="sd"> >>> b = mx.sym.Variable('b', attr={'b1':'b2'})</span> |
| <span class="sd"> >>> c = a+b</span> |
| <span class="sd"> >>> c.attr_dict()</span> |
| <span class="sd"> {'a': {'a1': 'a2'}, 'b': {'b1': 'b2'}}</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> ret : Dict of str to dict</span> |
| <span class="sd"> There is a key in the returned dict for every child with non-empty attribute set.</span> |
| <span class="sd"> For each symbol, the name of the symbol is its key in the dict</span> |
| <span class="sd"> and the correspond value is that symbol's attribute list (itself a dictionary).</span> |
| <span class="sd"> """</span> |
| <span class="n">size</span> <span class="o">=</span> <span class="n">mx_uint</span><span class="p">()</span> |
| <span class="n">pairs</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">)()</span> |
| <span class="n">f_handle</span> <span class="o">=</span> <span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolListAttr</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">f_handle</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">size</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">pairs</span><span class="p">)))</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="p">{}</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">size</span><span class="o">.</span><span class="n">value</span><span class="p">):</span> |
| <span class="n">name</span><span class="p">,</span> <span class="n">key</span> <span class="o">=</span> <span class="n">py_str</span><span class="p">(</span><span class="n">pairs</span><span class="p">[</span><span class="n">i</span> <span class="o">*</span> <span class="mi">2</span><span class="p">])</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">'$'</span><span class="p">)</span> |
| <span class="n">val</span> <span class="o">=</span> <span class="n">py_str</span><span class="p">(</span><span class="n">pairs</span><span class="p">[</span><span class="n">i</span> <span class="o">*</span> <span class="mi">2</span> <span class="o">+</span> <span class="mi">1</span><span class="p">])</span> |
| <span class="k">if</span> <span class="n">name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">ret</span><span class="p">:</span> |
| <span class="n">ret</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="p">{}</span> |
| <span class="n">ret</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="n">key</span><span class="p">]</span> <span class="o">=</span> <span class="n">val</span> |
| <span class="k">return</span> <span class="n">ret</span></div> |
| |
| <span class="k">def</span> <span class="nf">_set_attr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Sets an attribute of the symbol.</span> |
| |
| <span class="sd"> For example. A._set_attr(foo="bar") adds the mapping ``"{foo: bar}"``</span> |
| <span class="sd"> to the symbol's attribute dictionary.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> **kwargs</span> |
| <span class="sd"> The attributes to set</span> |
| <span class="sd"> """</span> |
| <span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">value</span><span class="p">,</span> <span class="n">string_types</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"Set Attr only accepts string values"</span><span class="p">)</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolSetAttr</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">c_str</span><span class="p">(</span><span class="n">key</span><span class="p">),</span> <span class="n">c_str</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">value</span><span class="p">))))</span> |
| |
| <div class="viewcode-block" id="Symbol.get_inputs"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.get_inputs">[docs]</a> <span class="k">def</span> <span class="nf">get_inputs</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Gets a new grouped symbol `sgroup`. The output of `sgroup` is a list of inputs to this symbol.</span> |
| |
| <span class="sd"> Consider the following code:</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> a = mx.sym.var('a')</span> |
| <span class="sd"> >>> b = mx.sym.var('b')</span> |
| <span class="sd"> >>> c = a + b</span> |
| <span class="sd"> >>> d = c.get_inputs()</span> |
| <span class="sd"> >>> d</span> |
| <span class="sd"> <Symbol Grouped></span> |
| <span class="sd"> >>> d.list_outputs()</span> |
| <span class="sd"> ['a', 'b']</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> sgroup : Symbol</span> |
| <span class="sd"> A symbol group containing all input nodes of the computation graph</span> |
| <span class="sd"> used to compute the symbol.</span> |
| <span class="sd"> """</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolGetInputs</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">handle</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="n">Symbol</span><span class="p">(</span><span class="n">handle</span><span class="o">=</span><span class="n">handle</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.get_internals"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.get_internals">[docs]</a> <span class="k">def</span> <span class="nf">get_internals</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Gets a new grouped symbol `sgroup`. The output of `sgroup` is a list of</span> |
| <span class="sd"> outputs of all of the internal nodes.</span> |
| |
| <span class="sd"> Consider the following code:</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> a = mx.sym.var('a')</span> |
| <span class="sd"> >>> b = mx.sym.var('b')</span> |
| <span class="sd"> >>> c = a + b</span> |
| <span class="sd"> >>> d = c.get_internals()</span> |
| <span class="sd"> >>> d</span> |
| <span class="sd"> <Symbol Grouped></span> |
| <span class="sd"> >>> d.list_outputs()</span> |
| <span class="sd"> ['a', 'b', '_plus4_output']</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> sgroup : Symbol</span> |
| <span class="sd"> A symbol group containing all internal and leaf nodes of the computation graph</span> |
| <span class="sd"> used to compute the symbol.</span> |
| <span class="sd"> """</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolGetInternals</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">handle</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="n">Symbol</span><span class="p">(</span><span class="n">handle</span><span class="o">=</span><span class="n">handle</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.get_children"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.get_children">[docs]</a> <span class="k">def</span> <span class="nf">get_children</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Gets a new grouped symbol whose output contains</span> |
| <span class="sd"> inputs to output nodes of the original symbol.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> x = mx.sym.Variable('x')</span> |
| <span class="sd"> >>> y = mx.sym.Variable('y')</span> |
| <span class="sd"> >>> z = mx.sym.Variable('z')</span> |
| <span class="sd"> >>> a = y+z</span> |
| <span class="sd"> >>> b = x+a</span> |
| <span class="sd"> >>> b.get_children()</span> |
| <span class="sd"> <Symbol Grouped></span> |
| <span class="sd"> >>> b.get_children().list_outputs()</span> |
| <span class="sd"> ['x', '_plus10_output']</span> |
| <span class="sd"> >>> b.get_children().get_children().list_outputs()</span> |
| <span class="sd"> ['y', 'z']</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> sgroup : Symbol or None</span> |
| <span class="sd"> The children of the head node. If the symbol has no</span> |
| <span class="sd"> inputs then ``None`` will be returned.</span> |
| <span class="sd"> """</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolGetChildren</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">handle</span><span class="p">)))</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">Symbol</span><span class="p">(</span><span class="n">handle</span><span class="o">=</span><span class="n">handle</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">())</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> |
| <span class="k">return</span> <span class="kc">None</span> |
| <span class="k">return</span> <span class="n">ret</span></div> |
| |
| <div class="viewcode-block" id="Symbol.list_arguments"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.list_arguments">[docs]</a> <span class="k">def</span> <span class="nf">list_arguments</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Lists all the arguments in the symbol.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> a = mx.sym.var('a')</span> |
| <span class="sd"> >>> b = mx.sym.var('b')</span> |
| <span class="sd"> >>> c = a + b</span> |
| <span class="sd"> >>> c.list_arguments</span> |
| <span class="sd"> ['a', 'b']</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> args : list of string</span> |
| <span class="sd"> List containing the names of all the arguments required to compute the symbol.</span> |
| <span class="sd"> """</span> |
| <span class="n">size</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_uint</span><span class="p">()</span> |
| <span class="n">sarr</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">)()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolListArguments</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">size</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">sarr</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="p">[</span><span class="n">py_str</span><span class="p">(</span><span class="n">sarr</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">size</span><span class="o">.</span><span class="n">value</span><span class="p">)]</span></div> |
| |
| <div class="viewcode-block" id="Symbol.list_outputs"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.list_outputs">[docs]</a> <span class="k">def</span> <span class="nf">list_outputs</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Lists all the outputs in the symbol.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> a = mx.sym.var('a')</span> |
| <span class="sd"> >>> b = mx.sym.var('b')</span> |
| <span class="sd"> >>> c = a + b</span> |
| <span class="sd"> >>> c.list_outputs()</span> |
| <span class="sd"> ['_plus12_output']</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> list of str</span> |
| <span class="sd"> List of all the outputs.</span> |
| <span class="sd"> For most symbols, this list contains only the name of this symbol.</span> |
| <span class="sd"> For symbol groups, this is a list with the names of all symbols</span> |
| <span class="sd"> in the group.</span> |
| <span class="sd"> """</span> |
| <span class="n">size</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_uint</span><span class="p">()</span> |
| <span class="n">sarr</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">)()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolListOutputs</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">size</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">sarr</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="p">[</span><span class="n">py_str</span><span class="p">(</span><span class="n">sarr</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">size</span><span class="o">.</span><span class="n">value</span><span class="p">)]</span></div> |
| |
| <span class="c1"># pylint: disable=invalid-length-returned</span> |
| <span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Get number of outputs for the symbol.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> a = mx.sym.var('a')</span> |
| <span class="sd"> >>> b = mx.sym.var('b')</span> |
| <span class="sd"> >>> c = a + b</span> |
| <span class="sd"> >>> len(c)</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> len(self): Number of outputs</span> |
| <span class="sd"> Number of outputs</span> |
| <span class="sd"> """</span> |
| <span class="n">output_count</span> <span class="o">=</span> <span class="n">mx_uint</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolGetNumOutputs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">output_count</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="n">output_count</span><span class="o">.</span><span class="n">value</span> |
| |
| <div class="viewcode-block" id="Symbol.list_auxiliary_states"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.list_auxiliary_states">[docs]</a> <span class="k">def</span> <span class="nf">list_auxiliary_states</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Lists all the auxiliary states in the symbol.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> a = mx.sym.var('a')</span> |
| <span class="sd"> >>> b = mx.sym.var('b')</span> |
| <span class="sd"> >>> c = a + b</span> |
| <span class="sd"> >>> c.list_auxiliary_states()</span> |
| <span class="sd"> []</span> |
| |
| <span class="sd"> Example of auxiliary states in `BatchNorm`.</span> |
| |
| <span class="sd"> >>> data = mx.symbol.Variable('data')</span> |
| <span class="sd"> >>> weight = mx.sym.Variable(name='fc1_weight')</span> |
| <span class="sd"> >>> fc1 = mx.symbol.FullyConnected(data = data, weight=weight, name='fc1', num_hidden=128)</span> |
| <span class="sd"> >>> fc2 = mx.symbol.BatchNorm(fc1, name='batchnorm0')</span> |
| <span class="sd"> >>> fc2.list_auxiliary_states()</span> |
| <span class="sd"> ['batchnorm0_moving_mean', 'batchnorm0_moving_var']</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> aux_states : list of str</span> |
| <span class="sd"> List of the auxiliary states in input symbol.</span> |
| |
| <span class="sd"> Notes</span> |
| <span class="sd"> -----</span> |
| <span class="sd"> Auxiliary states are special states of symbols that do not correspond to an argument,</span> |
| <span class="sd"> and are not updated by gradient descent. Common examples of auxiliary states</span> |
| <span class="sd"> include the `moving_mean` and `moving_variance` in `BatchNorm`.</span> |
| <span class="sd"> Most operators do not have auxiliary states.</span> |
| <span class="sd"> """</span> |
| <span class="n">size</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_uint</span><span class="p">()</span> |
| <span class="n">sarr</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">)()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolListAuxiliaryStates</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">size</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">sarr</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="p">[</span><span class="n">py_str</span><span class="p">(</span><span class="n">sarr</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">size</span><span class="o">.</span><span class="n">value</span><span class="p">)]</span></div> |
| |
| <div class="viewcode-block" id="Symbol.list_inputs"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.list_inputs">[docs]</a> <span class="k">def</span> <span class="nf">list_inputs</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Lists all arguments and auxiliary states of this Symbol.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> inputs : list of str</span> |
| <span class="sd"> List of all inputs.</span> |
| |
| <span class="sd"> Examples</span> |
| <span class="sd"> --------</span> |
| <span class="sd"> >>> bn = mx.sym.BatchNorm(name='bn')</span> |
| <span class="sd"> >>> bn.list_arguments()</span> |
| <span class="sd"> ['bn_data', 'bn_gamma', 'bn_beta']</span> |
| <span class="sd"> >>> bn.list_auxiliary_states()</span> |
| <span class="sd"> ['bn_moving_mean', 'bn_moving_var']</span> |
| <span class="sd"> >>> bn.list_inputs()</span> |
| <span class="sd"> ['bn_data', 'bn_gamma', 'bn_beta', 'bn_moving_mean', 'bn_moving_var']</span> |
| <span class="sd"> """</span> |
| <span class="n">size</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_uint</span><span class="p">()</span> |
| <span class="n">sarr</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">)()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">NNSymbolListInputNames</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">size</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">sarr</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="p">[</span><span class="n">py_str</span><span class="p">(</span><span class="n">sarr</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">size</span><span class="o">.</span><span class="n">value</span><span class="p">)]</span></div> |
| |
| <div class="viewcode-block" id="Symbol.infer_type"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.infer_type">[docs]</a> <span class="k">def</span> <span class="nf">infer_type</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Infers the type of all arguments and all outputs, given the known types</span> |
| <span class="sd"> for some arguments.</span> |
| |
| <span class="sd"> This function takes the known types of some arguments in either positional way</span> |
| <span class="sd"> or keyword argument way as input. It returns a tuple of `None` values</span> |
| <span class="sd"> if there is not enough information to deduce the missing types.</span> |
| |
| <span class="sd"> Inconsistencies in the known types will cause an error to be raised.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> a = mx.sym.var('a')</span> |
| <span class="sd"> >>> b = mx.sym.var('b')</span> |
| <span class="sd"> >>> c = a + b</span> |
| <span class="sd"> >>> arg_types, out_types, aux_types = c.infer_type(a='float32')</span> |
| <span class="sd"> >>> arg_types</span> |
| <span class="sd"> [<type 'numpy.float32'>, <type 'numpy.float32'>]</span> |
| <span class="sd"> >>> out_types</span> |
| <span class="sd"> [<type 'numpy.float32'>]</span> |
| <span class="sd"> >>> aux_types</span> |
| <span class="sd"> []</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> *args :</span> |
| <span class="sd"> Type of known arguments in a positional way.</span> |
| <span class="sd"> Unknown type can be marked as None.</span> |
| |
| <span class="sd"> **kwargs :</span> |
| <span class="sd"> Keyword arguments of known types.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> arg_types : list of numpy.dtype or None</span> |
| <span class="sd"> List of argument types.</span> |
| <span class="sd"> The order is same as the order of list_arguments().</span> |
| <span class="sd"> out_types : list of numpy.dtype or None</span> |
| <span class="sd"> List of output types.</span> |
| <span class="sd"> The order is same as the order of list_outputs().</span> |
| <span class="sd"> aux_types : list of numpy.dtype or None</span> |
| <span class="sd"> List of auxiliary state types.</span> |
| <span class="sd"> The order is same as the order of list_auxiliary_states().</span> |
| <span class="sd"> """</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">res</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_infer_type_impl</span><span class="p">(</span><span class="kc">False</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> |
| <span class="k">if</span> <span class="n">res</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">arg_shapes</span><span class="p">,</span> <span class="n">_</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_infer_type_impl</span><span class="p">(</span><span class="kc">True</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> |
| <span class="n">arg_names</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">()</span> |
| <span class="n">unknowns</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">dtype</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">arg_names</span><span class="p">,</span> <span class="n">arg_shapes</span><span class="p">):</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="n">dtype</span><span class="p">:</span> |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">unknowns</span><span class="p">)</span> <span class="o">>=</span> <span class="mi">10</span><span class="p">:</span> |
| <span class="n">unknowns</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">'...'</span><span class="p">)</span> |
| <span class="k">break</span> |
| <span class="n">unknowns</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s1">: </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="n">dtype</span><span class="p">)</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span> |
| <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span> |
| <span class="s2">"Cannot decide type for the following arguments. "</span> <span class="o">+</span> |
| <span class="s2">"Consider providing them as input:</span><span class="se">\n\t</span><span class="s2">"</span> <span class="o">+</span> |
| <span class="s2">"</span><span class="se">\n\t</span><span class="s2">"</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">unknowns</span><span class="p">),</span> <span class="n">stacklevel</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span> |
| <span class="k">return</span> <span class="n">res</span> |
| <span class="k">except</span> <span class="n">MXNetError</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"infer_type error. Arguments:"</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">arg</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">args</span><span class="p">):</span> |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" #</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">arg</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" </span><span class="si">{</span><span class="n">k</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">v</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> |
| <span class="k">raise</span></div> |
| |
| <div class="viewcode-block" id="Symbol.infer_type_partial"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.infer_type_partial">[docs]</a> <span class="k">def</span> <span class="nf">infer_type_partial</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Infers the type partially.</span> |
| |
| <span class="sd"> This functions works the same way as `infer_type`,</span> |
| <span class="sd"> except that this function can return partial results.</span> |
| |
| <span class="sd"> In the following example, information about fc2 is not available. So, `infer_shape`</span> |
| <span class="sd"> will return a tuple of `None` values but `infer_shape_partial` will return partial values.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> data = mx.sym.Variable('data')</span> |
| <span class="sd"> >>> prev = mx.sym.Variable('prev')</span> |
| <span class="sd"> >>> casted_prev = mx.sym.cast(prev, dtype='float32')</span> |
| <span class="sd"> >>> out = mx.sym.Activation(data=mx.sym.elemwise_add(data, casted_prev), act_type='relu')</span> |
| <span class="sd"> >>> out.list_arguments()</span> |
| <span class="sd"> ['data', 'prev']</span> |
| <span class="sd"> >>> out.infer_type(data='float32')</span> |
| <span class="sd"> (None, None, None)</span> |
| <span class="sd"> >>> out.infer_type_partial(data='float32')</span> |
| <span class="sd"> ([numpy.float32, None], [numpy.float32], [])</span> |
| <span class="sd"> >>> # infers type if you give information about prev</span> |
| <span class="sd"> >>> out.infer_type(data='float32', prev='float16')</span> |
| <span class="sd"> ([numpy.float32, numpy.float16], [numpy.float32], [])</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> *args :</span> |
| <span class="sd"> Type of known arguments in a positional way.</span> |
| <span class="sd"> Unknown type can be marked as None.</span> |
| |
| <span class="sd"> **kwargs :</span> |
| <span class="sd"> Keyword arguments of known types.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> arg_types : list of numpy.dtype or None</span> |
| <span class="sd"> List of argument types.</span> |
| <span class="sd"> The order is same as the order of list_arguments().</span> |
| <span class="sd"> out_types : list of numpy.dtype or None</span> |
| <span class="sd"> List of output types.</span> |
| <span class="sd"> The order is same as the order of list_outputs().</span> |
| <span class="sd"> aux_types : list of numpy.dtype or None</span> |
| <span class="sd"> List of auxiliary state types.</span> |
| <span class="sd"> The order is same as the order of list_auxiliary_states().</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_infer_type_impl</span><span class="p">(</span><span class="kc">True</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <span class="k">def</span> <span class="nf">_infer_type_impl</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">partial</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""The actual implementation for calling type inference API."""</span> |
| <span class="c1"># pylint: disable=too-many-locals</span> |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'Can only specify known argument </span><span class="se">\</span> |
| <span class="s1"> types either by positional or kwargs way.'</span><span class="p">)</span> |
| <span class="n">sdata</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span> |
| <span class="n">keys</span> <span class="o">=</span> <span class="n">c_array</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">,</span> <span class="p">[])</span> |
| <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">args</span><span class="p">:</span> |
| <span class="k">if</span> <span class="n">s</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">sdata</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dtype_np_to_mx</span><span class="p">(</span><span class="n">s</span><span class="p">))</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">sdata</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">str_keys</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> |
| <span class="k">if</span> <span class="n">is_mx_dtype</span><span class="p">(</span><span class="n">v</span><span class="p">):</span> |
| <span class="n">v</span> <span class="o">=</span> <span class="n">dtype_np_to_mx</span><span class="p">(</span><span class="n">v</span><span class="p">)</span> |
| <span class="n">str_keys</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">k</span><span class="p">)</span> |
| <span class="n">sdata</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">v</span><span class="p">)</span> |
| <span class="n">keys</span> <span class="o">=</span> <span class="n">c_str_array</span><span class="p">(</span><span class="n">str_keys</span><span class="p">)</span> |
| <span class="n">arg_type_size</span> <span class="o">=</span> <span class="n">mx_uint</span><span class="p">()</span> |
| <span class="n">arg_type_data</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_int</span><span class="p">)()</span> |
| <span class="n">out_type_size</span> <span class="o">=</span> <span class="n">mx_uint</span><span class="p">()</span> |
| <span class="n">out_type_data</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_int</span><span class="p">)()</span> |
| <span class="n">aux_type_size</span> <span class="o">=</span> <span class="n">mx_uint</span><span class="p">()</span> |
| <span class="n">aux_type_data</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_int</span><span class="p">)()</span> |
| <span class="n">complete</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_int</span><span class="p">()</span> |
| <span class="k">if</span> <span class="n">partial</span><span class="p">:</span> |
| <span class="n">infer_func</span> <span class="o">=</span> <span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolInferTypePartial</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">infer_func</span> <span class="o">=</span> <span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolInferType</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">infer_func</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> |
| <span class="n">mx_uint</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">sdata</span><span class="p">)),</span> |
| <span class="n">keys</span><span class="p">,</span> |
| <span class="n">c_array_buf</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_int</span><span class="p">,</span> <span class="n">array</span><span class="p">(</span><span class="s1">'i'</span><span class="p">,</span> <span class="n">sdata</span><span class="p">)),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">arg_type_size</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">arg_type_data</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">out_type_size</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">out_type_data</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">aux_type_size</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">aux_type_data</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">complete</span><span class="p">)))</span> |
| <span class="k">if</span> <span class="n">complete</span><span class="o">.</span><span class="n">value</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span> |
| <span class="n">arg_types</span> <span class="o">=</span> <span class="p">[</span><span class="n">dtype_mx_to_np</span><span class="p">(</span><span class="n">arg_type_data</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">arg_type_size</span><span class="o">.</span><span class="n">value</span><span class="p">)]</span> |
| <span class="n">out_types</span> <span class="o">=</span> <span class="p">[</span><span class="n">dtype_mx_to_np</span><span class="p">(</span><span class="n">out_type_data</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">out_type_size</span><span class="o">.</span><span class="n">value</span><span class="p">)]</span> |
| <span class="n">aux_types</span> <span class="o">=</span> <span class="p">[</span><span class="n">dtype_mx_to_np</span><span class="p">(</span><span class="n">aux_type_data</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">aux_type_size</span><span class="o">.</span><span class="n">value</span><span class="p">)]</span> |
| <span class="k">return</span> <span class="p">(</span><span class="n">arg_types</span><span class="p">,</span> <span class="n">out_types</span><span class="p">,</span> <span class="n">aux_types</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">return</span> <span class="p">(</span><span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> |
| |
| <div class="viewcode-block" id="Symbol.infer_shape"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.infer_shape">[docs]</a> <span class="k">def</span> <span class="nf">infer_shape</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Infers the shapes of all arguments and all outputs given the known shapes of</span> |
| <span class="sd"> some arguments.</span> |
| |
| <span class="sd"> This function takes the known shapes of some arguments in either positional way</span> |
| <span class="sd"> or keyword argument way as input. It returns a tuple of `None` values</span> |
| <span class="sd"> if there is not enough information to deduce the missing shapes.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> a = mx.sym.var('a')</span> |
| <span class="sd"> >>> b = mx.sym.var('b')</span> |
| <span class="sd"> >>> c = a + b</span> |
| <span class="sd"> >>> arg_shapes, out_shapes, aux_shapes = c.infer_shape(a=(3,3))</span> |
| <span class="sd"> >>> arg_shapes</span> |
| <span class="sd"> [(3L, 3L), (3L, 3L)]</span> |
| <span class="sd"> >>> out_shapes</span> |
| <span class="sd"> [(3L, 3L)]</span> |
| <span class="sd"> >>> aux_shapes</span> |
| <span class="sd"> []</span> |
| <span class="sd"> >>> c.infer_shape(a=(0,3)) # 0s in shape means unknown dimensions. So, returns None.</span> |
| <span class="sd"> (None, None, None)</span> |
| |
| <span class="sd"> Inconsistencies in the known shapes will cause an error to be raised.</span> |
| <span class="sd"> See the following example:</span> |
| |
| <span class="sd"> >>> data = mx.sym.Variable('data')</span> |
| <span class="sd"> >>> out = mx.sym.FullyConnected(data=data, name='fc1', num_hidden=1000)</span> |
| <span class="sd"> >>> out = mx.sym.Activation(data=out, act_type='relu')</span> |
| <span class="sd"> >>> out = mx.sym.FullyConnected(data=out, name='fc2', num_hidden=10)</span> |
| <span class="sd"> >>> weight_shape= (1, 100)</span> |
| <span class="sd"> >>> data_shape = (100, 100)</span> |
| <span class="sd"> >>> out.infer_shape(data=data_shape, fc1_weight=weight_shape)</span> |
| <span class="sd"> Error in operator fc1: Shape inconsistent, Provided=(1,100), inferred shape=(1000,100)</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> *args :</span> |
| <span class="sd"> Shape of arguments in a positional way.</span> |
| <span class="sd"> Unknown shape can be marked as None.</span> |
| |
| <span class="sd"> **kwargs :</span> |
| <span class="sd"> Keyword arguments of the known shapes.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> arg_shapes : list of tuple or None</span> |
| <span class="sd"> List of argument shapes.</span> |
| <span class="sd"> The order is same as the order of list_arguments().</span> |
| <span class="sd"> out_shapes : list of tuple or None</span> |
| <span class="sd"> List of output shapes.</span> |
| <span class="sd"> The order is same as the order of list_outputs().</span> |
| <span class="sd"> aux_shapes : list of tuple or None</span> |
| <span class="sd"> List of auxiliary state shapes.</span> |
| <span class="sd"> The order is same as the order of list_auxiliary_states().</span> |
| <span class="sd"> """</span> |
| <span class="c1"># pylint: disable=too-many-locals</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">res</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_infer_shape_impl</span><span class="p">(</span><span class="kc">False</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> |
| <span class="k">if</span> <span class="n">res</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">arg_shapes</span><span class="p">,</span> <span class="n">_</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_infer_shape_impl</span><span class="p">(</span><span class="kc">True</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> |
| <span class="n">arg_names</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">()</span> |
| <span class="n">unknowns</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">shape</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">arg_names</span><span class="p">,</span> <span class="n">arg_shapes</span><span class="p">):</span> |
| <span class="k">if</span> <span class="n">is_np_shape</span><span class="p">():</span> |
| <span class="n">shape_is_none</span> <span class="o">=</span> <span class="ow">not</span> <span class="n">shape</span> <span class="ow">or</span> <span class="o">-</span><span class="mi">1</span> <span class="ow">in</span> <span class="n">shape</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">shape_is_none</span> <span class="o">=</span> <span class="ow">not</span> <span class="n">shape</span> <span class="ow">or</span> <span class="mi">0</span> <span class="ow">in</span> <span class="n">shape</span> |
| <span class="k">if</span> <span class="n">shape_is_none</span><span class="p">:</span> |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">unknowns</span><span class="p">)</span> <span class="o">>=</span> <span class="mi">10</span><span class="p">:</span> |
| <span class="n">unknowns</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">'...'</span><span class="p">)</span> |
| <span class="k">break</span> |
| <span class="n">unknowns</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s1">: </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="n">shape</span><span class="p">)</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span> |
| <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span> |
| <span class="s2">"Cannot decide shape for the following arguments "</span> <span class="o">+</span> |
| <span class="s2">"(0s in shape means unknown dimensions). "</span> <span class="o">+</span> |
| <span class="s2">"Consider providing them as input:</span><span class="se">\n\t</span><span class="s2">"</span> <span class="o">+</span> |
| <span class="s2">"</span><span class="se">\n\t</span><span class="s2">"</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">unknowns</span><span class="p">),</span> <span class="n">stacklevel</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span> |
| <span class="k">return</span> <span class="n">res</span> |
| <span class="k">except</span> <span class="n">MXNetError</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"infer_shape error. Arguments:"</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">arg</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">args</span><span class="p">):</span> |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" #</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">arg</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" </span><span class="si">{</span><span class="n">k</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">v</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> |
| <span class="k">raise</span></div> |
| |
| <div class="viewcode-block" id="Symbol.infer_shape_partial"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.infer_shape_partial">[docs]</a> <span class="k">def</span> <span class="nf">infer_shape_partial</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Infers the shape partially.</span> |
| |
| <span class="sd"> This functions works the same way as `infer_shape`,</span> |
| <span class="sd"> except that this function can return partial results.</span> |
| |
| <span class="sd"> In the following example, information about fc2 is not available. So, `infer_shape`</span> |
| <span class="sd"> will return a tuple of `None` values but `infer_shape_partial` will return partial values.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> data = mx.sym.Variable('data')</span> |
| <span class="sd"> >>> prev = mx.sym.Variable('prev')</span> |
| <span class="sd"> >>> fc1 = mx.sym.FullyConnected(data=data, name='fc1', num_hidden=128)</span> |
| <span class="sd"> >>> fc2 = mx.sym.FullyConnected(data=prev, name='fc2', num_hidden=128)</span> |
| <span class="sd"> >>> out = mx.sym.Activation(data=mx.sym.elemwise_add(fc1, fc2), act_type='relu')</span> |
| <span class="sd"> >>> out.list_arguments()</span> |
| <span class="sd"> ['data', 'fc1_weight', 'fc1_bias', 'prev', 'fc2_weight', 'fc2_bias']</span> |
| <span class="sd"> >>> out.infer_shape(data=(10,64))</span> |
| <span class="sd"> (None, None, None)</span> |
| <span class="sd"> >>> out.infer_shape_partial(data=(10,64))</span> |
| <span class="sd"> ([(10L, 64L), (128L, 64L), (128L,), (), (), ()], [(10L, 128L)], [])</span> |
| <span class="sd"> >>> # infers shape if you give information about fc2</span> |
| <span class="sd"> >>> out.infer_shape(data=(10,64), prev=(10,128))</span> |
| <span class="sd"> ([(10L, 64L), (128L, 64L), (128L,), (10L, 128L), (128L, 128L), (128L,)], [(10L, 128L)], [])</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> *args :</span> |
| <span class="sd"> Shape of arguments in a positional way.</span> |
| <span class="sd"> Unknown shape can be marked as None</span> |
| |
| <span class="sd"> **kwargs :</span> |
| <span class="sd"> Keyword arguments of known shapes.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> arg_shapes : list of tuple or None</span> |
| <span class="sd"> List of argument shapes.</span> |
| <span class="sd"> The order is same as the order of list_arguments().</span> |
| <span class="sd"> out_shapes : list of tuple or None</span> |
| <span class="sd"> List of output shapes.</span> |
| <span class="sd"> The order is same as the order of list_outputs().</span> |
| <span class="sd"> aux_shapes : list of tuple or None</span> |
| <span class="sd"> List of auxiliary state shapes.</span> |
| <span class="sd"> The order is same as the order of list_auxiliary_states().</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_infer_shape_impl</span><span class="p">(</span><span class="kc">True</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <span class="k">def</span> <span class="nf">_infer_shape_impl</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">partial</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""The actual implementation for calling shape inference API."""</span> |
| <span class="c1"># pylint: disable=too-many-locals</span> |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'Can only specify known argument </span><span class="se">\</span> |
| <span class="s1"> shapes either by positional or kwargs way.'</span><span class="p">)</span> |
| <span class="n">sdata</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="n">indptr</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">]</span> |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span> |
| <span class="n">keys</span> <span class="o">=</span> <span class="n">c_array</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">,</span> <span class="p">[])</span> |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">s</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">args</span><span class="p">):</span> |
| <span class="k">if</span> <span class="n">s</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">s</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s2">"Arguments need to be shapes (tuple), "</span> |
| <span class="sa">f</span><span class="s2">"but argument </span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2"> is </span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="n">s</span><span class="p">)</span><span class="si">}</span><span class="s2">."</span><span class="p">)</span> |
| <span class="n">sdata</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">s</span><span class="p">)</span> |
| <span class="n">indptr</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">sdata</span><span class="p">))</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">str_keys</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s2">"Arguments need to be shapes (tuple), "</span> |
| <span class="sa">f</span><span class="s2">"but '</span><span class="si">{</span><span class="n">k</span><span class="si">}</span><span class="s2">' is </span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="n">v</span><span class="p">)</span><span class="si">}</span><span class="s2">."</span><span class="p">)</span> |
| <span class="n">str_keys</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">k</span><span class="p">)</span> |
| <span class="n">sdata</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">v</span><span class="p">)</span> |
| <span class="n">indptr</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">sdata</span><span class="p">))</span> |
| <span class="n">keys</span> <span class="o">=</span> <span class="n">c_str_array</span><span class="p">(</span><span class="n">str_keys</span><span class="p">)</span> |
| <span class="n">arg_shape_size</span> <span class="o">=</span> <span class="n">mx_uint</span><span class="p">()</span> |
| <span class="n">arg_shape_ndim</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int</span><span class="p">)()</span> |
| <span class="n">out_shape_size</span> <span class="o">=</span> <span class="n">mx_uint</span><span class="p">()</span> |
| <span class="n">out_shape_ndim</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int</span><span class="p">)()</span> |
| <span class="n">aux_shape_size</span> <span class="o">=</span> <span class="n">mx_uint</span><span class="p">()</span> |
| <span class="n">aux_shape_ndim</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int</span><span class="p">)()</span> |
| <span class="n">complete</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_int</span><span class="p">()</span> |
| <span class="k">if</span> <span class="n">_int64_enabled</span><span class="p">():</span> |
| <span class="n">arg_shape_data</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int64</span><span class="p">))()</span> |
| <span class="n">out_shape_data</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int64</span><span class="p">))()</span> |
| <span class="n">aux_shape_data</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int64</span><span class="p">))()</span> |
| <span class="k">if</span> <span class="n">partial</span><span class="p">:</span> |
| <span class="n">infer_func</span> <span class="o">=</span> <span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolInferShapePartial64</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">infer_func</span> <span class="o">=</span> <span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolInferShape64</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">infer_func</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> |
| <span class="n">mx_uint</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">indptr</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">),</span> |
| <span class="n">keys</span><span class="p">,</span> |
| <span class="n">c_array_buf</span><span class="p">(</span><span class="n">mx_int64</span><span class="p">,</span> <span class="n">array</span><span class="p">(</span><span class="s1">'q'</span><span class="p">,</span> <span class="n">indptr</span><span class="p">)),</span> |
| <span class="n">c_array_buf</span><span class="p">(</span><span class="n">mx_int64</span><span class="p">,</span> <span class="n">array</span><span class="p">(</span><span class="s1">'q'</span><span class="p">,</span> <span class="n">sdata</span><span class="p">)),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">arg_shape_size</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">arg_shape_ndim</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">arg_shape_data</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">out_shape_size</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">out_shape_ndim</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">out_shape_data</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">aux_shape_size</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">aux_shape_ndim</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">aux_shape_data</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">complete</span><span class="p">)))</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">for</span> <span class="n">size</span> <span class="ow">in</span> <span class="n">sdata</span><span class="p">:</span> |
| <span class="k">if</span> <span class="n">size</span> <span class="o">></span> <span class="n">_SIGNED_INT32_UPPER_LIMIT</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"[_infer_shape_impl] Size of tensor you are trying to "</span> <span class="o">+</span> |
| <span class="s2">"allocate is larger than 2^31 elements. Please build "</span> <span class="o">+</span> |
| <span class="s2">"with flag USE_INT64_TENSOR_SIZE=1"</span><span class="p">)</span> |
| <span class="n">arg_shape_data</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int</span><span class="p">))()</span> |
| <span class="n">out_shape_data</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int</span><span class="p">))()</span> |
| <span class="n">aux_shape_data</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int</span><span class="p">))()</span> |
| <span class="k">if</span> <span class="n">partial</span><span class="p">:</span> |
| <span class="n">infer_func</span> <span class="o">=</span> <span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolInferShapePartial</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">infer_func</span> <span class="o">=</span> <span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolInferShape</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">infer_func</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> |
| <span class="n">mx_uint</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">indptr</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">),</span> |
| <span class="n">keys</span><span class="p">,</span> |
| <span class="n">c_array_buf</span><span class="p">(</span><span class="n">mx_uint</span><span class="p">,</span> <span class="n">array</span><span class="p">(</span><span class="s1">'I'</span><span class="p">,</span> <span class="n">indptr</span><span class="p">)),</span> |
| <span class="n">c_array_buf</span><span class="p">(</span><span class="n">mx_int</span><span class="p">,</span> <span class="n">array</span><span class="p">(</span><span class="s1">'i'</span><span class="p">,</span> <span class="n">sdata</span><span class="p">)),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">arg_shape_size</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">arg_shape_ndim</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">arg_shape_data</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">out_shape_size</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">out_shape_ndim</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">out_shape_data</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">aux_shape_size</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">aux_shape_ndim</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">aux_shape_data</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">complete</span><span class="p">)))</span> |
| <span class="k">if</span> <span class="n">complete</span><span class="o">.</span><span class="n">value</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span> |
| <span class="n">arg_shapes</span> <span class="o">=</span> <span class="p">[</span><span class="nb">tuple</span><span class="p">(</span><span class="n">arg_shape_data</span><span class="p">[</span><span class="n">i</span><span class="p">][:</span><span class="n">arg_shape_ndim</span><span class="p">[</span><span class="n">i</span><span class="p">]])</span> |
| <span class="k">if</span> <span class="n">arg_shape_ndim</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">>=</span> <span class="mi">0</span> <span class="k">else</span> <span class="kc">None</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">arg_shape_size</span><span class="o">.</span><span class="n">value</span><span class="p">)]</span> |
| <span class="n">out_shapes</span> <span class="o">=</span> <span class="p">[</span><span class="nb">tuple</span><span class="p">(</span><span class="n">out_shape_data</span><span class="p">[</span><span class="n">i</span><span class="p">][:</span><span class="n">out_shape_ndim</span><span class="p">[</span><span class="n">i</span><span class="p">]])</span> |
| <span class="k">if</span> <span class="n">out_shape_ndim</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">>=</span> <span class="mi">0</span> <span class="k">else</span> <span class="kc">None</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">out_shape_size</span><span class="o">.</span><span class="n">value</span><span class="p">)]</span> |
| <span class="n">aux_shapes</span> <span class="o">=</span> <span class="p">[</span><span class="nb">tuple</span><span class="p">(</span><span class="n">aux_shape_data</span><span class="p">[</span><span class="n">i</span><span class="p">][:</span><span class="n">aux_shape_ndim</span><span class="p">[</span><span class="n">i</span><span class="p">]])</span> |
| <span class="k">if</span> <span class="n">aux_shape_ndim</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">>=</span> <span class="mi">0</span> <span class="k">else</span> <span class="kc">None</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">aux_shape_size</span><span class="o">.</span><span class="n">value</span><span class="p">)]</span> |
| <span class="k">return</span> <span class="p">(</span><span class="n">arg_shapes</span><span class="p">,</span> <span class="n">out_shapes</span><span class="p">,</span> <span class="n">aux_shapes</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">return</span> <span class="p">(</span><span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> |
| <span class="c1"># pylint: enable=too-many-locals</span> |
| |
| <div class="viewcode-block" id="Symbol.debug_str"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.debug_str">[docs]</a> <span class="k">def</span> <span class="nf">debug_str</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Gets a debug string of symbol.</span> |
| |
| <span class="sd"> It contains Symbol output, variables and operators in the computation graph</span> |
| <span class="sd"> with their inputs, variables and attributes.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> string</span> |
| <span class="sd"> Debug string of the symbol.</span> |
| |
| <span class="sd"> Examples</span> |
| <span class="sd"> --------</span> |
| <span class="sd"> >>> a = mx.sym.Variable('a')</span> |
| <span class="sd"> >>> b = mx.sym.sin(a)</span> |
| <span class="sd"> >>> c = 2 * a + b</span> |
| <span class="sd"> >>> d = mx.sym.FullyConnected(data=c, num_hidden=10)</span> |
| <span class="sd"> >>> d.debug_str()</span> |
| <span class="sd"> >>> print d.debug_str()</span> |
| <span class="sd"> Symbol Outputs:</span> |
| <span class="sd"> output[0]=fullyconnected0(0)</span> |
| <span class="sd"> Variable:a</span> |
| <span class="sd"> --------------------</span> |
| <span class="sd"> Op:_mul_scalar, Name=_mulscalar0</span> |
| <span class="sd"> Inputs:</span> |
| <span class="sd"> arg[0]=a(0) version=0</span> |
| <span class="sd"> Attrs:</span> |
| <span class="sd"> scalar=2</span> |
| <span class="sd"> --------------------</span> |
| <span class="sd"> Op:sin, Name=sin0</span> |
| <span class="sd"> Inputs:</span> |
| <span class="sd"> arg[0]=a(0) version=0</span> |
| <span class="sd"> --------------------</span> |
| <span class="sd"> Op:elemwise_add, Name=_plus0</span> |
| <span class="sd"> Inputs:</span> |
| <span class="sd"> arg[0]=_mulscalar0(0)</span> |
| <span class="sd"> arg[1]=sin0(0)</span> |
| <span class="sd"> Variable:fullyconnected0_weight</span> |
| <span class="sd"> Variable:fullyconnected0_bias</span> |
| <span class="sd"> --------------------</span> |
| <span class="sd"> Op:FullyConnected, Name=fullyconnected0</span> |
| <span class="sd"> Inputs:</span> |
| <span class="sd"> arg[0]=_plus0(0)</span> |
| <span class="sd"> arg[1]=fullyconnected0_weight(0) version=0</span> |
| <span class="sd"> arg[2]=fullyconnected0_bias(0) version=0</span> |
| <span class="sd"> Attrs:</span> |
| <span class="sd"> num_hidden=10</span> |
| <span class="sd"> """</span> |
| <span class="n">debug_str</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolPrint</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">debug_str</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="n">py_str</span><span class="p">(</span><span class="n">debug_str</span><span class="o">.</span><span class="n">value</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.save"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.save">[docs]</a> <span class="k">def</span> <span class="nf">save</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">fname</span><span class="p">,</span> <span class="n">remove_amp_cast</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Saves symbol to a file.</span> |
| |
| <span class="sd"> You can also use pickle to do the job if you only work on python.</span> |
| <span class="sd"> The advantage of `load`/`save` functions is that the file contents are language agnostic.</span> |
| <span class="sd"> This means the model saved by one language binding can be loaded by a different</span> |
| <span class="sd"> language binding of `MXNet`.</span> |
| <span class="sd"> You also get the benefit of being able to directly load/save from cloud storage(S3, HDFS).</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> fname : str</span> |
| <span class="sd"> The name of the file.</span> |
| |
| <span class="sd"> - "s3://my-bucket/path/my-s3-symbol"</span> |
| <span class="sd"> - "hdfs://my-bucket/path/my-hdfs-symbol"</span> |
| <span class="sd"> - "/path-to/my-local-symbol"</span> |
| <span class="sd"> remove_amp_cast : bool, optional</span> |
| <span class="sd"> Whether to remove the amp_cast and amp_multicast operators, before saving the model.</span> |
| |
| <span class="sd"> See Also</span> |
| <span class="sd"> --------</span> |
| <span class="sd"> symbol.load : Used to load symbol from file.</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">fname</span><span class="p">,</span> <span class="n">string_types</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">'fname need to be string'</span><span class="p">)</span> |
| <span class="k">if</span> <span class="n">remove_amp_cast</span><span class="p">:</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolRemoveAmpCast</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">handle</span><span class="p">)))</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolSaveToFile</span><span class="p">(</span><span class="n">handle</span><span class="p">,</span> <span class="n">c_str</span><span class="p">(</span><span class="n">fname</span><span class="p">)))</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolSaveToFile</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">c_str</span><span class="p">(</span><span class="n">fname</span><span class="p">)))</span></div> |
| |
| <div class="viewcode-block" id="Symbol.tojson"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.tojson">[docs]</a> <span class="k">def</span> <span class="nf">tojson</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">remove_amp_cast</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Saves symbol to a JSON string.</span> |
| |
| <span class="sd"> See Also</span> |
| <span class="sd"> --------</span> |
| <span class="sd"> symbol.fromjson : Used to load symbol from JSON string.</span> |
| <span class="sd"> """</span> |
| <span class="n">json_str</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">()</span> |
| <span class="k">if</span> <span class="n">remove_amp_cast</span><span class="p">:</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolRemoveAmpCast</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">handle</span><span class="p">)))</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolSaveToJSON</span><span class="p">(</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">json_str</span><span class="p">)))</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolSaveToJSON</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">json_str</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="n">py_str</span><span class="p">(</span><span class="n">json_str</span><span class="o">.</span><span class="n">value</span><span class="p">)</span></div> |
| |
| <span class="nd">@staticmethod</span> |
| <span class="k">def</span> <span class="nf">_get_ndarray_inputs</span><span class="p">(</span><span class="n">arg_key</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">arg_names</span><span class="p">,</span> <span class="n">allow_missing</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Helper function to get NDArray lists handles from various inputs.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> arg_key : str</span> |
| <span class="sd"> The name of argument, used for error message.</span> |
| |
| <span class="sd"> args : list of NDArray or dict of str to NDArray</span> |
| <span class="sd"> Input arguments to the symbols.</span> |
| <span class="sd"> If type is list of NDArray, the position is in the same order of arg_names.</span> |
| <span class="sd"> If type is dict of str to NDArray, then it maps the name of arguments</span> |
| <span class="sd"> to the corresponding NDArray,</span> |
| |
| <span class="sd"> args_names : list of string</span> |
| <span class="sd"> List of argument names.</span> |
| |
| <span class="sd"> allow_missing : boolean</span> |
| <span class="sd"> Whether missing argument is allowed.</span> |
| <span class="sd"> When allowed, the missing handle will be set to None(null)</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> handles : list of NDArrayHandle</span> |
| <span class="sd"> The positional list of NDArrayHandles generated from input.</span> |
| <span class="sd"> """</span> |
| <span class="c1"># setup args</span> |
| <span class="n">arg_handles</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="n">arg_arrays</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">args</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span> |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">arg_names</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Length of </span><span class="si">{</span><span class="n">arg_key</span><span class="si">}</span><span class="s1"> does not match the number of arguments'</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">narr</span> <span class="ow">in</span> <span class="n">args</span><span class="p">:</span> |
| <span class="k">if</span> <span class="n">narr</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">allow_missing</span><span class="p">:</span> |
| <span class="n">arg_handles</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span> |
| <span class="k">elif</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">narr</span><span class="p">,</span> <span class="n">NDArray</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">'Only accept list of NDArrays or dict of str to NDArray'</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">arg_handles</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">narr</span><span class="o">.</span><span class="n">handle</span><span class="p">)</span> |
| <span class="n">arg_arrays</span> <span class="o">=</span> <span class="n">args</span> |
| <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">args</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span> |
| <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">arg_names</span><span class="p">:</span> |
| <span class="k">if</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">args</span><span class="p">:</span> |
| <span class="n">narr</span> <span class="o">=</span> <span class="n">args</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">narr</span><span class="p">,</span> <span class="n">NDArray</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">'Only accept list of NDArrays or dict of str to NDArray'</span><span class="p">)</span> |
| <span class="n">arg_handles</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">narr</span><span class="o">.</span><span class="n">handle</span><span class="p">)</span> |
| <span class="n">arg_arrays</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">narr</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">if</span> <span class="n">allow_missing</span><span class="p">:</span> |
| <span class="n">arg_handles</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span> |
| <span class="n">arg_arrays</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'key `</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s1">` is missing in `</span><span class="si">{</span><span class="n">arg_key</span><span class="si">}</span><span class="s1">`'</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">'Only accept list of NDArrays or dict of str to NDArray'</span><span class="p">)</span> |
| <span class="k">return</span> <span class="n">c_array</span><span class="p">(</span><span class="n">NDArrayHandle</span><span class="p">,</span> <span class="n">arg_handles</span><span class="p">),</span> <span class="n">arg_arrays</span> |
| |
| <span class="k">def</span> <span class="nf">_gen_atomic_symbol</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXGenAtomicSymbolFromSymbol</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">handle</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="n">Symbol</span><span class="p">(</span><span class="n">handle</span><span class="p">)</span> |
| |
| |
| <span class="c1"># pylint: disable=too-many-locals</span> |
| <div class="viewcode-block" id="Symbol.optimize_for"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.optimize_for">[docs]</a> <span class="k">def</span> <span class="nf">optimize_for</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">backend</span><span class="p">,</span> <span class="n">args</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">aux</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">ctx</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> |
| <span class="n">shape_dict</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">type_dict</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">stype_dict</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">skip_infer</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sa">r</span><span class="sd">"""Partitions current symbol and optimizes it for a given backend.</span> |
| |
| <span class="sd"> The backend must have registered the partitioning graph pass in</span> |
| <span class="sd"> ``SubgraphBackendRegistry``.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> backend : str</span> |
| <span class="sd"> The name of backend, as registered in ``SubgraphBackendRegistry``</span> |
| <span class="sd"> args : dict of str to NDArray, optional</span> |
| <span class="sd"> Input arguments to the symbol, required to infer shapes/types before partitioning</span> |
| <span class="sd"> If type is a dict of str to NDArray, then it maps the names of arguments</span> |
| <span class="sd"> to the corresponding NDArray. Undefined arguments' NDArrays</span> |
| <span class="sd"> don't have to be specified in the dict.</span> |
| <span class="sd"> aux : dict of str to NDArray, optional</span> |
| <span class="sd"> Input auxiliary arguments to the symbol</span> |
| <span class="sd"> If type is a dict of str to :class:`NDArray`, then it maps the name of arguments</span> |
| <span class="sd"> to the corresponding :class:`NDArray`.</span> |
| <span class="sd"> ctx : Context, optional</span> |
| <span class="sd"> Device context, used to infer stypes</span> |
| <span class="sd"> shape_dict : Dict of str->tuple, optional</span> |
| <span class="sd"> Input shape dictionary.</span> |
| <span class="sd"> Used iff input :class:`NDArray` is not in ``args``.</span> |
| <span class="sd"> type_dict : Dict of str->numpy.dtype, optional</span> |
| <span class="sd"> Input type dictionary.</span> |
| <span class="sd"> Used iff input :class:`NDArray` is not in ``args``.</span> |
| <span class="sd"> stype_dict : Dict of str->str, optional</span> |
| <span class="sd"> Input storage type dictionary.</span> |
| <span class="sd"> Used iff input :class:`NDArray` is not in ``args``.</span> |
| <span class="sd"> skip_infer : bool, optional</span> |
| <span class="sd"> If True, the optimization skips the shape, type and storage type inference pass.</span> |
| <span class="sd"> kwargs : optional arguments</span> |
| <span class="sd"> Passed on to ``PrePartition`` and ``PostPartition`` functions of ``SubgraphProperty``</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> out : SymbolHandle</span> |
| <span class="sd"> A symbol with the partitioned graph for target backend.</span> |
| <span class="sd"> """</span> |
| <span class="n">out</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">backend</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> |
| <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">args</span><span class="p">,</span> <span class="nb">dict</span><span class="p">)</span> <span class="ow">or</span> <span class="n">args</span> <span class="ow">is</span> <span class="kc">None</span> |
| <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">aux</span><span class="p">,</span> <span class="nb">dict</span><span class="p">)</span> <span class="ow">or</span> <span class="n">aux</span> <span class="ow">is</span> <span class="kc">None</span> |
| |
| <span class="k">if</span> <span class="n">args</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">or</span> <span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> |
| <span class="n">args_</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="n">args_handle</span> <span class="o">=</span> <span class="n">c_array</span><span class="p">(</span><span class="n">NDArrayHandle</span><span class="p">,</span> <span class="p">[])</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">args_handle</span><span class="p">,</span> <span class="n">args_</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_get_ndarray_inputs</span><span class="p">(</span><span class="s1">'args'</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">(),</span> <span class="kc">True</span><span class="p">)</span> |
| |
| <span class="k">if</span> <span class="n">aux</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">or</span> <span class="nb">len</span><span class="p">(</span><span class="n">aux</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> |
| <span class="n">aux_</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="n">aux_handle</span> <span class="o">=</span> <span class="n">c_array</span><span class="p">(</span><span class="n">NDArrayHandle</span><span class="p">,</span> <span class="p">[])</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">aux_handle</span><span class="p">,</span> <span class="n">aux_</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_get_ndarray_inputs</span><span class="p">(</span><span class="s1">'aux_states'</span><span class="p">,</span> <span class="n">aux</span><span class="p">,</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">list_auxiliary_states</span><span class="p">(),</span> <span class="kc">True</span><span class="p">)</span> |
| <span class="k">if</span> <span class="n">ctx</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">ctx</span> <span class="o">=</span> <span class="n">current_device</span><span class="p">()</span> |
| <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">ctx</span><span class="p">,</span> <span class="n">Device</span><span class="p">)</span> |
| |
| |
| <span class="c1"># parse input data shape dict</span> |
| <span class="n">num_input_shapes</span> <span class="o">=</span> <span class="mi">0</span> |
| <span class="n">input_shape_names</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">)()</span> |
| <span class="n">input_shape_data</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int64</span><span class="p">)()</span> |
| <span class="n">input_shape_idx</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_uint</span><span class="p">)()</span> |
| <span class="k">if</span> <span class="n">shape_dict</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">input_shape_names</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="n">input_shape_data</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="n">input_shape_idx</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">]</span> |
| <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">shape_dict</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="p">(</span><span class="nb">tuple</span><span class="p">,</span> <span class="nb">list</span><span class="p">)):</span> |
| <span class="n">input_shape_names</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">k</span><span class="p">)</span> |
| <span class="n">input_shape_data</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">v</span><span class="p">)</span> |
| <span class="n">input_shape_idx</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">input_shape_data</span><span class="p">))</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">v</span><span class="p">)</span> <span class="o">+</span> <span class="s2">" has to be a tuple or list."</span><span class="p">)</span> |
| <span class="n">num_input_shapes</span> <span class="o">=</span> <span class="n">mx_uint</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">input_shape_names</span><span class="p">))</span> |
| <span class="n">input_shape_names</span> <span class="o">=</span> <span class="n">c_str_array</span><span class="p">(</span><span class="n">input_shape_names</span><span class="p">)</span> |
| <span class="n">input_shape_data</span> <span class="o">=</span> <span class="n">c_array_buf</span><span class="p">(</span><span class="n">mx_int64</span><span class="p">,</span> <span class="n">array</span><span class="p">(</span><span class="s1">'q'</span><span class="p">,</span> <span class="n">input_shape_data</span><span class="p">))</span> |
| <span class="n">input_shape_idx</span> <span class="o">=</span> <span class="n">c_array_buf</span><span class="p">(</span><span class="n">mx_uint</span><span class="p">,</span> <span class="n">array</span><span class="p">(</span><span class="s1">'i'</span><span class="p">,</span> <span class="n">input_shape_idx</span><span class="p">))</span> |
| |
| <span class="c1"># parse input data types dict</span> |
| <span class="n">num_input_types</span> <span class="o">=</span> <span class="mi">0</span> |
| <span class="n">input_type_names</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">)()</span> <span class="c1"># provided type argument names</span> |
| <span class="n">input_type_data</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_uint</span><span class="p">)()</span> <span class="c1"># provided types</span> |
| <span class="k">if</span> <span class="n">type_dict</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">input_type_names</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="n">input_type_data</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">type_dict</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> |
| <span class="n">v</span> <span class="o">=</span> <span class="n">dtype_np_to_mx</span><span class="p">(</span><span class="n">v</span><span class="p">)</span> |
| <span class="n">input_type_names</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">k</span><span class="p">)</span> |
| <span class="n">input_type_data</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">v</span><span class="p">)</span> |
| |
| <span class="n">num_input_types</span> <span class="o">=</span> <span class="n">mx_uint</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">input_type_names</span><span class="p">))</span> |
| <span class="n">input_type_names</span> <span class="o">=</span> <span class="n">c_str_array</span><span class="p">(</span><span class="n">input_type_names</span><span class="p">)</span> |
| <span class="n">input_type_data</span> <span class="o">=</span> <span class="n">c_array_buf</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_int</span><span class="p">,</span> <span class="n">array</span><span class="p">(</span><span class="s1">'i'</span><span class="p">,</span> <span class="n">input_type_data</span><span class="p">))</span> |
| |
| <span class="c1"># parse input data storage types dict</span> |
| <span class="n">num_input_stypes</span> <span class="o">=</span> <span class="mi">0</span> |
| <span class="c1"># provided storage type argument names</span> |
| <span class="n">input_stype_names</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">)()</span> |
| <span class="n">input_stype_data</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_uint</span><span class="p">)()</span> <span class="c1"># provided storage types</span> |
| <span class="k">if</span> <span class="n">stype_dict</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">input_stype_names</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="n">input_stype_data</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">stype_dict</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> |
| <span class="k">if</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">_STORAGE_TYPE_STR_TO_ID</span><span class="p">:</span> |
| <span class="n">input_stype_names</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">k</span><span class="p">)</span> |
| <span class="n">input_stype_data</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_STORAGE_TYPE_STR_TO_ID</span><span class="p">[</span><span class="n">v</span><span class="p">])</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">v</span><span class="p">)</span> <span class="o">+</span> <span class="s2">" is not a MXNet storage type."</span><span class="p">)</span> |
| |
| <span class="n">num_input_stypes</span> <span class="o">=</span> <span class="n">mx_uint</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">input_stype_names</span><span class="p">))</span> |
| <span class="n">input_stype_names</span> <span class="o">=</span> <span class="n">c_str_array</span><span class="p">(</span><span class="n">input_stype_names</span><span class="p">)</span> |
| <span class="n">input_stype_data</span> <span class="o">=</span> <span class="n">c_array_buf</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_int</span><span class="p">,</span> <span class="n">array</span><span class="p">(</span><span class="s1">'i'</span><span class="p">,</span> <span class="n">input_stype_data</span><span class="p">))</span> |
| |
| <span class="n">new_args_size</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_uint</span><span class="p">()</span> |
| <span class="n">new_arg_names</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">)()</span> |
| <span class="n">new_args_handle</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">NDArrayHandle</span><span class="p">)()</span> |
| <span class="n">new_aux_size</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_uint</span><span class="p">()</span> |
| <span class="n">new_aux_names</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">)()</span> |
| <span class="n">new_aux_handle</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">NDArrayHandle</span><span class="p">)()</span> |
| |
| <span class="n">key_list</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="n">val_list</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">val</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> |
| <span class="n">key_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">key</span><span class="p">)</span> |
| <span class="n">val_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">val</span><span class="p">))</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXOptimizeForBackend</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> |
| <span class="n">c_str</span><span class="p">(</span><span class="n">backend</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">c_int</span><span class="p">(</span><span class="n">ctx</span><span class="o">.</span><span class="n">device_typeid</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">out</span><span class="p">),</span> |
| <span class="n">mx_uint</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">args_</span><span class="p">)),</span> |
| <span class="n">args_handle</span><span class="p">,</span> |
| <span class="n">mx_uint</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">aux_</span><span class="p">)),</span> |
| <span class="n">aux_handle</span><span class="p">,</span> |
| <span class="n">mx_uint</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">key_list</span><span class="p">)),</span> |
| <span class="n">c_str_array</span><span class="p">(</span><span class="n">key_list</span><span class="p">),</span> |
| <span class="n">c_str_array</span><span class="p">(</span><span class="n">val_list</span><span class="p">),</span> |
| <span class="n">num_input_shapes</span><span class="p">,</span> |
| <span class="n">input_shape_names</span><span class="p">,</span> |
| <span class="n">input_shape_data</span><span class="p">,</span> |
| <span class="n">input_shape_idx</span><span class="p">,</span> |
| <span class="n">num_input_types</span><span class="p">,</span> |
| <span class="n">input_type_names</span><span class="p">,</span> |
| <span class="n">input_type_data</span><span class="p">,</span> |
| <span class="n">num_input_stypes</span><span class="p">,</span> |
| <span class="n">input_stype_names</span><span class="p">,</span> |
| <span class="n">input_stype_data</span><span class="p">,</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">c_bool</span><span class="p">(</span><span class="n">skip_infer</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">new_args_size</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">new_args_handle</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">new_arg_names</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">new_aux_size</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">new_aux_handle</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">new_aux_names</span><span class="p">)))</span> |
| <span class="c1"># add new args/aux</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="n">args</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">new_args_size</span><span class="o">.</span><span class="n">value</span><span class="p">):</span> |
| <span class="n">args</span><span class="p">[</span><span class="n">py_str</span><span class="p">(</span><span class="n">new_arg_names</span><span class="p">[</span><span class="n">i</span><span class="p">])]</span> <span class="o">=</span> <span class="n">NDArray</span><span class="p">(</span><span class="n">NDArrayHandle</span><span class="p">(</span><span class="n">new_args_handle</span><span class="p">[</span><span class="n">i</span><span class="p">]))</span> |
| <span class="k">elif</span> <span class="n">new_args_size</span><span class="o">.</span><span class="n">value</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s1">'Cannot add new args in optimize_for since args is None</span><span class="se">\n</span><span class="s1">'</span> <span class="o">+</span> |
| <span class="s1">'Provide a dictionary to the args argument to optimize_for'</span><span class="p">)</span> |
| |
| <span class="k">if</span> <span class="ow">not</span> <span class="n">aux</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">new_aux_size</span><span class="o">.</span><span class="n">value</span><span class="p">):</span> |
| <span class="n">aux</span><span class="p">[</span><span class="n">py_str</span><span class="p">(</span><span class="n">new_aux_names</span><span class="p">[</span><span class="n">i</span><span class="p">])]</span> <span class="o">=</span> <span class="n">NDArray</span><span class="p">(</span><span class="n">NDArrayHandle</span><span class="p">(</span><span class="n">new_aux_handle</span><span class="p">[</span><span class="n">i</span><span class="p">]))</span> |
| <span class="k">elif</span> <span class="n">new_aux_size</span><span class="o">.</span><span class="n">value</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s1">'Cannot add new aux in optimize_for since aux is None</span><span class="se">\n</span><span class="s1">'</span> <span class="o">+</span> |
| <span class="s1">'Provide a dictionary to the aux argument to optimize_for'</span><span class="p">)</span> |
| |
| <span class="n">new_sym</span> <span class="o">=</span> <span class="n">Symbol</span><span class="p">(</span><span class="n">out</span><span class="p">)</span> |
| |
| <span class="n">arg_names</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">()</span> |
| <span class="n">new_arg_names</span> <span class="o">=</span> <span class="n">new_sym</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">()</span> |
| <span class="n">deleted_arg_names</span> <span class="o">=</span> <span class="nb">set</span><span class="p">([</span><span class="n">item</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">arg_names</span> |
| <span class="k">if</span> <span class="n">item</span> <span class="ow">not</span> <span class="ow">in</span> <span class="nb">set</span><span class="p">(</span><span class="n">new_arg_names</span><span class="p">)])</span> |
| |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">deleted_arg_names</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> |
| <span class="k">if</span> <span class="n">args</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="k">for</span> <span class="n">a_n</span> <span class="ow">in</span> <span class="n">deleted_arg_names</span><span class="p">:</span> |
| <span class="k">if</span> <span class="n">a_n</span> <span class="ow">in</span> <span class="n">args</span><span class="p">:</span> |
| <span class="n">args</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="n">a_n</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s1">'A param was deleted during optimization, but no args dictionary was provided.</span><span class="se">\n</span><span class="s1">'</span> <span class="o">+</span> |
| <span class="s1">'Please ensure that your model weights match the newly optimized model.'</span><span class="p">)</span> |
| |
| <span class="n">aux_names</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">list_auxiliary_states</span><span class="p">()</span> |
| <span class="n">new_aux_names</span> <span class="o">=</span> <span class="n">new_sym</span><span class="o">.</span><span class="n">list_auxiliary_states</span><span class="p">()</span> |
| <span class="n">deleted_aux_names</span> <span class="o">=</span> <span class="nb">set</span><span class="p">([</span><span class="n">item</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">aux_names</span> |
| <span class="k">if</span> <span class="n">item</span> <span class="ow">not</span> <span class="ow">in</span> <span class="nb">set</span><span class="p">(</span><span class="n">new_aux_names</span><span class="p">)])</span> |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">deleted_aux_names</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> |
| <span class="k">if</span> <span class="n">aux</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="k">for</span> <span class="n">a_n</span> <span class="ow">in</span> <span class="n">deleted_aux_names</span><span class="p">:</span> |
| <span class="k">if</span> <span class="n">a_n</span> <span class="ow">in</span> <span class="n">aux</span><span class="p">:</span> |
| <span class="n">aux</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="n">a_n</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s1">'A param was deleted during optimization, but no args dictionary was provided.</span><span class="se">\n</span><span class="s1">'</span> <span class="o">+</span> |
| <span class="s1">'Please ensure that your model weights match the newly optimized model.'</span><span class="p">)</span> |
| |
| <span class="k">return</span> <span class="n">new_sym</span></div> |
| |
| <span class="c1"># pylint: disable=too-many-locals</span> |
| <span class="k">def</span> <span class="nf">_simple_bind</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ctx</span><span class="p">,</span> <span class="n">grad_req</span><span class="o">=</span><span class="s1">'write'</span><span class="p">,</span> <span class="n">type_dict</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">stype_dict</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> |
| <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Bind current symbol to get an executor, allocate all the arguments needed.</span> |
| <span class="sd"> Allows specifying data types.</span> |
| |
| <span class="sd"> This function simplifies the binding procedure. You need to specify only input data shapes.</span> |
| <span class="sd"> Before binding the executor, the function allocates arguments and auxiliary states</span> |
| <span class="sd"> that were not explicitly specified. Allows specifying data types.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> x = mx.sym.Variable('x')</span> |
| <span class="sd"> >>> y = mx.sym.FullyConnected(x, num_hidden=4)</span> |
| <span class="sd"> >>> exe = y.simple_bind(mx.cpu(), x=(5,4), grad_req='null')</span> |
| <span class="sd"> >>> exe.forward()</span> |
| <span class="sd"> [<NDArray 5x4 @cpu(0)>]</span> |
| <span class="sd"> >>> exe.outputs[0].asnumpy()</span> |
| <span class="sd"> array([[ 0., 0., 0., 0.],</span> |
| <span class="sd"> [ 0., 0., 0., 0.],</span> |
| <span class="sd"> [ 0., 0., 0., 0.],</span> |
| <span class="sd"> [ 0., 0., 0., 0.],</span> |
| <span class="sd"> [ 0., 0., 0., 0.]], dtype=float32)</span> |
| <span class="sd"> >>> exe.arg_arrays</span> |
| <span class="sd"> [<NDArray 5x4 @cpu(0)>, <NDArray 4x4 @cpu(0)>, <NDArray 4 @cpu(0)>]</span> |
| <span class="sd"> >>> exe.grad_arrays</span> |
| <span class="sd"> [<NDArray 5x4 @cpu(0)>, <NDArray 4x4 @cpu(0)>, <NDArray 4 @cpu(0)>]</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> ctx : Context</span> |
| <span class="sd"> The device context the generated executor to run on.</span> |
| |
| <span class="sd"> grad_req: string</span> |
| <span class="sd"> {'write', 'add', 'null'}, or list of str or dict of str to str, optional</span> |
| <span class="sd"> To specify how we should update the gradient to the `args_grad`.</span> |
| |
| <span class="sd"> - 'write' means every time gradient is written to specified `args_grad` NDArray.</span> |
| <span class="sd"> - 'add' means every time gradient is added to the specified NDArray.</span> |
| <span class="sd"> - 'null' means no action is taken, the gradient may not be calculated.</span> |
| |
| <span class="sd"> type_dict : Dict of str->numpy.dtype</span> |
| <span class="sd"> Input type dictionary, name->dtype</span> |
| |
| <span class="sd"> stype_dict : Dict of str->str</span> |
| <span class="sd"> Input storage type dictionary, name->storage_type</span> |
| |
| <span class="sd"> kwargs : Dict of str->shape</span> |
| <span class="sd"> Input shape dictionary, name->shape</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> executor : mxnet.Executor</span> |
| <span class="sd"> The generated executor</span> |
| <span class="sd"> """</span> |
| <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">grad_req</span><span class="p">,</span> <span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="nb">dict</span><span class="p">))</span> |
| <span class="c1"># infer shape</span> |
| <span class="n">arg_shapes</span><span class="p">,</span> <span class="n">_</span><span class="p">,</span> <span class="n">aux_shapes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">infer_shape</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> |
| <span class="n">type_dict</span> <span class="o">=</span> <span class="p">{}</span> <span class="k">if</span> <span class="n">type_dict</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="n">type_dict</span> |
| <span class="n">arg_dtypes</span><span class="p">,</span> <span class="n">_</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">arg_dtypes</span><span class="p">,</span> <span class="n">_</span><span class="p">,</span> <span class="n">aux_dtypes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">infer_type</span><span class="p">(</span><span class="o">**</span><span class="n">type_dict</span><span class="p">)</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> <span class="c1"># pylint: disable=broad-except</span> |
| <span class="k">pass</span> |
| <span class="n">args</span> <span class="o">=</span> <span class="p">[</span><span class="kc">None</span><span class="p">]</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">arg_shapes</span><span class="p">)</span> <span class="k">if</span> <span class="n">arg_shapes</span> <span class="k">else</span> <span class="p">[]</span> |
| <span class="n">aux_states</span> <span class="o">=</span> <span class="p">[</span><span class="kc">None</span><span class="p">]</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">aux_shapes</span><span class="p">)</span> <span class="k">if</span> <span class="n">aux_shapes</span> <span class="k">else</span> <span class="p">[]</span> |
| |
| <span class="n">arg_names</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">()</span> |
| <span class="n">aux_names</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">list_auxiliary_states</span><span class="p">()</span> |
| |
| <span class="kn">from</span> <span class="nn">..ndarray</span> <span class="kn">import</span> <span class="n">zeros</span> <span class="k">as</span> <span class="n">nd_zeros</span> |
| <span class="k">if</span> <span class="n">arg_shapes</span><span class="p">:</span> |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">shape</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">arg_shapes</span><span class="p">):</span> |
| <span class="k">if</span> <span class="n">arg_dtypes</span><span class="p">:</span> |
| <span class="n">args</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">nd_zeros</span><span class="p">(</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">arg_dtypes</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">args</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">nd_zeros</span><span class="p">(</span><span class="n">shape</span><span class="p">)</span> |
| <span class="k">if</span> <span class="n">aux_shapes</span><span class="p">:</span> |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">shape</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">aux_shapes</span><span class="p">):</span> |
| <span class="k">if</span> <span class="n">aux_dtypes</span><span class="p">:</span> |
| <span class="n">aux_states</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">nd_zeros</span><span class="p">(</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">aux_dtypes</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">aux_states</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">nd_zeros</span><span class="p">(</span><span class="n">shape</span><span class="p">)</span> |
| |
| <span class="k">if</span> <span class="n">stype_dict</span><span class="p">:</span> |
| <span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">stype</span> <span class="ow">in</span> <span class="n">stype_dict</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> |
| <span class="k">if</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">arg_names</span><span class="p">:</span> |
| <span class="n">index</span> <span class="o">=</span> <span class="n">arg_names</span><span class="o">.</span><span class="n">index</span><span class="p">(</span><span class="n">name</span><span class="p">)</span> |
| <span class="n">args</span><span class="p">[</span><span class="n">index</span><span class="p">]</span> <span class="o">=</span> <span class="n">args</span><span class="p">[</span><span class="n">index</span><span class="p">]</span><span class="o">.</span><span class="n">tostype</span><span class="p">(</span><span class="n">stype</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">assert</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">aux_names</span> |
| <span class="n">index</span> <span class="o">=</span> <span class="n">aux_names</span><span class="o">.</span><span class="n">index</span><span class="p">(</span><span class="n">name</span><span class="p">)</span> |
| <span class="n">aux_states</span><span class="p">[</span><span class="n">index</span><span class="p">]</span> <span class="o">=</span> <span class="n">aux_states</span><span class="p">[</span><span class="n">index</span><span class="p">]</span><span class="o">.</span><span class="n">totype</span><span class="p">(</span><span class="n">stype</span><span class="p">)</span> |
| |
| <span class="k">with</span> <span class="n">_profiler_scope</span><span class="p">(</span><span class="s2">"symbol:arg_grad:"</span><span class="p">):</span> |
| <span class="k">if</span> <span class="n">grad_req</span> <span class="o">==</span> <span class="s1">'null'</span><span class="p">:</span> |
| <span class="n">args_grad</span> <span class="o">=</span> <span class="kc">None</span> |
| <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">grad_req</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span> |
| <span class="n">args_grad</span> <span class="o">=</span> <span class="p">{}</span> |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">arg_names</span><span class="p">):</span> |
| <span class="k">if</span> <span class="n">grad_req</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">!=</span> <span class="s1">'null'</span><span class="p">:</span> |
| <span class="n">args_grad</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">args</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">args_grad</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">args</span><span class="p">]</span> |
| <span class="k">return</span> <span class="n">Executor</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ctx</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">args_grad</span><span class="p">,</span> <span class="n">grad_req</span><span class="p">,</span> <span class="n">aux_states</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">_bind</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ctx</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">args_grad</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">grad_req</span><span class="o">=</span><span class="s1">'write'</span><span class="p">,</span> |
| <span class="n">aux_states</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">static_alloc</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Binds the current symbol to an executor and returns it.</span> |
| |
| <span class="sd"> We first declare the computation and then bind to the data to run.</span> |
| <span class="sd"> This function returns an executor which provides method `forward()` method for evaluation</span> |
| <span class="sd"> and a `outputs()` method to get all the results.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> a = mx.sym.Variable('a')</span> |
| <span class="sd"> >>> b = mx.sym.Variable('b')</span> |
| <span class="sd"> >>> c = a + b</span> |
| <span class="sd"> <Symbol _plus1></span> |
| <span class="sd"> >>> ex = c._bind(ctx=mx.cpu(), args={'a' : mx.nd.ones([2,3]), 'b' : mx.nd.ones([2,3])})</span> |
| <span class="sd"> >>> ex.forward()</span> |
| <span class="sd"> [<NDArray 2x3 @cpu(0)>]</span> |
| <span class="sd"> >>> ex.outputs[0].asnumpy()</span> |
| <span class="sd"> [[ 2. 2. 2.]</span> |
| <span class="sd"> [ 2. 2. 2.]]</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> ctx : Context</span> |
| <span class="sd"> The device context the generated executor to run on.</span> |
| |
| <span class="sd"> args : list of NDArray or dict of str to NDArray</span> |
| <span class="sd"> Input arguments to the symbol.</span> |
| |
| <span class="sd"> - If the input type is a list of `NDArray`, the order should be same as the order</span> |
| <span class="sd"> of `list_arguments()`.</span> |
| <span class="sd"> - If the input type is a dict of str to `NDArray`, then it maps the name of arguments</span> |
| <span class="sd"> to the corresponding `NDArray`.</span> |
| <span class="sd"> - In either case, all the arguments must be provided.</span> |
| |
| <span class="sd"> args_grad : list of NDArray or dict of str to `NDArray`, optional</span> |
| <span class="sd"> When specified, `args_grad` provides NDArrays to hold</span> |
| <span class="sd"> the result of gradient value in backward.</span> |
| |
| <span class="sd"> - If the input type is a list of `NDArray`, the order should be same as the order</span> |
| <span class="sd"> of `list_arguments()`.</span> |
| <span class="sd"> - If the input type is a dict of str to `NDArray`, then it maps the name of arguments</span> |
| <span class="sd"> to the corresponding NDArray.</span> |
| <span class="sd"> - When the type is a dict of str to `NDArray`, one only need to provide the dict</span> |
| <span class="sd"> for required argument gradient.</span> |
| <span class="sd"> Only the specified argument gradient will be calculated.</span> |
| |
| <span class="sd"> grad_req : {'write', 'add', 'null'}, or list of str or dict of str to str, optional</span> |
| <span class="sd"> To specify how we should update the gradient to the `args_grad`.</span> |
| |
| <span class="sd"> - 'write' means everytime gradient is write to specified `args_grad` `NDArray`.</span> |
| <span class="sd"> - 'add' means everytime gradient is add to the specified NDArray.</span> |
| <span class="sd"> - 'null' means no action is taken, the gradient may not be calculated.</span> |
| |
| <span class="sd"> aux_states : list of `NDArray`, or dict of str to `NDArray`, optional</span> |
| <span class="sd"> Input auxiliary states to the symbol, only needed when the output of</span> |
| <span class="sd"> `list_auxiliary_states()` is not empty.</span> |
| |
| <span class="sd"> - If the input type is a list of `NDArray`, the order should be same as the order</span> |
| <span class="sd"> of `list_auxiliary_states()`.</span> |
| <span class="sd"> - If the input type is a dict of str to `NDArray`, then it maps the name of</span> |
| <span class="sd"> `auxiliary_states` to the corresponding `NDArray`,</span> |
| <span class="sd"> - In either case, all the auxiliary states need to be provided.</span> |
| |
| <span class="sd"> static_alloc : bool, default False</span> |
| <span class="sd"> Statically allocate memory to improve speed. Memory usage may increase.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> executor : Executor</span> |
| <span class="sd"> The generated executor</span> |
| |
| <span class="sd"> Notes</span> |
| <span class="sd"> -----</span> |
| <span class="sd"> Auxiliary states are the special states of symbols that do not correspond</span> |
| <span class="sd"> to an argument, and do not have gradient but are still useful</span> |
| <span class="sd"> for the specific operations. Common examples of auxiliary states include</span> |
| <span class="sd"> the `moving_mean` and `moving_variance` states in `BatchNorm`.</span> |
| <span class="sd"> Most operators do not have auxiliary states and in those cases,</span> |
| <span class="sd"> this parameter can be safely ignored.</span> |
| |
| <span class="sd"> One can give up gradient by using a dict in `args_grad` and only specify</span> |
| <span class="sd"> gradient they interested in.</span> |
| <span class="sd"> """</span> |
| <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">grad_req</span><span class="p">,</span> <span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="nb">dict</span><span class="p">))</span> |
| <span class="k">return</span> <span class="n">Executor</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ctx</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">args_grad</span><span class="p">,</span> <span class="n">grad_req</span><span class="p">,</span> <span class="n">aux_states</span><span class="p">,</span> <span class="n">static_alloc</span><span class="p">)</span> |
| |
| <div class="viewcode-block" id="Symbol.gradient"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.gradient">[docs]</a> <span class="k">def</span> <span class="nf">gradient</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">wrt</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Gets the autodiff of current symbol.</span> |
| |
| <span class="sd"> This function can only be used if current symbol is a loss function.</span> |
| |
| <span class="sd"> .. note:: This function is currently not implemented.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> wrt : Array of String</span> |
| <span class="sd"> keyword arguments of the symbol that the gradients are taken.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> grad : Symbol</span> |
| <span class="sd"> A gradient Symbol with returns to be the corresponding gradients.</span> |
| <span class="sd"> """</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">c_wrt</span> <span class="o">=</span> <span class="n">c_str_array</span><span class="p">(</span><span class="n">wrt</span><span class="p">)</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolGrad</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> |
| <span class="n">mx_uint</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">wrt</span><span class="p">)),</span> |
| <span class="n">c_wrt</span><span class="p">,</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">handle</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="n">Symbol</span><span class="p">(</span><span class="n">handle</span><span class="p">)</span></div> |
| |
| <span class="c1"># pylint: enable= no-member</span> |
| |
| <div class="viewcode-block" id="Symbol.eval"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.eval">[docs]</a> <span class="k">def</span> <span class="nf">eval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ctx</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Evaluates a symbol given arguments.</span> |
| |
| <span class="sd"> The `eval` method combines a call to `bind` (which returns an executor)</span> |
| <span class="sd"> with a call to `forward` (executor method).</span> |
| <span class="sd"> For the common use case, where you might repeatedly evaluate with same arguments,</span> |
| <span class="sd"> eval is slow.</span> |
| <span class="sd"> In that case, you should call `bind` once and then repeatedly call forward.</span> |
| <span class="sd"> This function allows simpler syntax for less cumbersome introspection.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> a = mx.sym.Variable('a')</span> |
| <span class="sd"> >>> b = mx.sym.Variable('b')</span> |
| <span class="sd"> >>> c = a + b</span> |
| <span class="sd"> >>> ex = c.eval(ctx = mx.cpu(), a = mx.nd.ones([2,3]), b = mx.nd.ones([2,3]))</span> |
| <span class="sd"> >>> ex</span> |
| <span class="sd"> [<NDArray 2x3 @cpu(0)>]</span> |
| <span class="sd"> >>> ex[0].asnumpy()</span> |
| <span class="sd"> array([[ 2., 2., 2.],</span> |
| <span class="sd"> [ 2., 2., 2.]], dtype=float32)</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> ctx : Context</span> |
| <span class="sd"> The device context the generated executor to run on.</span> |
| |
| <span class="sd"> kwargs : Keyword arguments of type `NDArray`</span> |
| <span class="sd"> Input arguments to the symbol. All the arguments must be provided.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> result : a list of NDArrays corresponding to the values taken by each symbol when</span> |
| <span class="sd"> evaluated on given args. When called on a single symbol (not a group),</span> |
| <span class="sd"> the result will be a list with one element.</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="n">ctx</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">ctx</span> <span class="o">=</span> <span class="n">current_device</span><span class="p">()</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_bind</span><span class="p">(</span><span class="n">ctx</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">)</span><span class="o">.</span><span class="n">forward</span><span class="p">()</span></div> |
| |
| <div class="viewcode-block" id="Symbol.reshape"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.reshape">[docs]</a> <span class="k">def</span> <span class="nf">reshape</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`reshape`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`reshape`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.reshape_like"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.reshape_like">[docs]</a> <span class="k">def</span> <span class="nf">reshape_like</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`reshape_like`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`reshape_like`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">reshape_like</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.astype"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.astype">[docs]</a> <span class="k">def</span> <span class="nf">astype</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`cast`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`cast`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">cast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.zeros_like"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.zeros_like">[docs]</a> <span class="k">def</span> <span class="nf">zeros_like</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`zeros_like`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`zeros_like`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">zeros_like</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.ones_like"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.ones_like">[docs]</a> <span class="k">def</span> <span class="nf">ones_like</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`ones_like`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`ones_like`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">ones_like</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.broadcast_axes"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.broadcast_axes">[docs]</a> <span class="k">def</span> <span class="nf">broadcast_axes</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`broadcast_axes`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`broadcast_axes`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">broadcast_axes</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.repeat"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.repeat">[docs]</a> <span class="k">def</span> <span class="nf">repeat</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`repeat`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`repeat`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">repeat</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.pad"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.pad">[docs]</a> <span class="k">def</span> <span class="nf">pad</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`pad`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`pad`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">pad</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.swapaxes"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.swapaxes">[docs]</a> <span class="k">def</span> <span class="nf">swapaxes</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`swapaxes`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`swapaxes`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">swapaxes</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.split"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.split">[docs]</a> <span class="k">def</span> <span class="nf">split</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`split`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`split`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.split_v2"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.split_v2">[docs]</a> <span class="k">def</span> <span class="nf">split_v2</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`split_v2`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`split_v2`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">split_v2</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.slice"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.slice">[docs]</a> <span class="k">def</span> <span class="nf">slice</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`slice`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`slice`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">slice</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.slice_axis"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.slice_axis">[docs]</a> <span class="k">def</span> <span class="nf">slice_axis</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`slice_axis`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`slice_axis`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">slice_axis</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.slice_like"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.slice_like">[docs]</a> <span class="k">def</span> <span class="nf">slice_like</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`slice_like`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`slice_like`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">slice_like</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.take"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.take">[docs]</a> <span class="k">def</span> <span class="nf">take</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`take`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`take`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">take</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.one_hot"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.one_hot">[docs]</a> <span class="k">def</span> <span class="nf">one_hot</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`one_hot`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`one_hot`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">one_hot</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.pick"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.pick">[docs]</a> <span class="k">def</span> <span class="nf">pick</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`pick`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`pick`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">pick</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.sort"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.sort">[docs]</a> <span class="k">def</span> <span class="nf">sort</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`sort`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`sort`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">sort</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.topk"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.topk">[docs]</a> <span class="k">def</span> <span class="nf">topk</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`topk`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`topk`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">topk</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.argsort"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.argsort">[docs]</a> <span class="k">def</span> <span class="nf">argsort</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`argsort`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`argsort`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">argsort</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.argmax"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.argmax">[docs]</a> <span class="k">def</span> <span class="nf">argmax</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`argmax`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`argmax`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.argmax_channel"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.argmax_channel">[docs]</a> <span class="k">def</span> <span class="nf">argmax_channel</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`argmax_channel`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`argmax_channel`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">argmax_channel</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.argmin"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.argmin">[docs]</a> <span class="k">def</span> <span class="nf">argmin</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`argmin`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`argmin`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">argmin</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.clip"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.clip">[docs]</a> <span class="k">def</span> <span class="nf">clip</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`clip`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`clip`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">clip</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.abs"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.abs">[docs]</a> <span class="k">def</span> <span class="nf">abs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`abs`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`abs`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.sign"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.sign">[docs]</a> <span class="k">def</span> <span class="nf">sign</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`sign`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`sign`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">sign</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.flatten"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.flatten">[docs]</a> <span class="k">def</span> <span class="nf">flatten</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> <span class="c1"># pylint: disable=unused-argument</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`flatten`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`flatten`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">flatten</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.shape_array"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.shape_array">[docs]</a> <span class="k">def</span> <span class="nf">shape_array</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`shape_array`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`shape_op`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">shape_array</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.size_array"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.size_array">[docs]</a> <span class="k">def</span> <span class="nf">size_array</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`size_array`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`size_array`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">size_array</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.expand_dims"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.expand_dims">[docs]</a> <span class="k">def</span> <span class="nf">expand_dims</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> <span class="c1"># pylint: disable=unused-argument</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`expand_dims`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`expand_dims`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">expand_dims</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="n">axis</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.broadcast_to"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.broadcast_to">[docs]</a> <span class="k">def</span> <span class="nf">broadcast_to</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`broadcast_to`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`broadcast_to`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">broadcast_to</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.broadcast_like"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.broadcast_like">[docs]</a> <span class="k">def</span> <span class="nf">broadcast_like</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`broadcast_like`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`broadcast_like`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">broadcast_like</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.tile"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.tile">[docs]</a> <span class="k">def</span> <span class="nf">tile</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`tile`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`tile`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">tile</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.transpose"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.transpose">[docs]</a> <span class="k">def</span> <span class="nf">transpose</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`transpose`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`transpose`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.flip"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.flip">[docs]</a> <span class="k">def</span> <span class="nf">flip</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`flip`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`flip`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">flip</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.depth_to_space"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.depth_to_space">[docs]</a> <span class="k">def</span> <span class="nf">depth_to_space</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`depth_to_space`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`depth_to_space`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">depth_to_space</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.space_to_depth"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.space_to_depth">[docs]</a> <span class="k">def</span> <span class="nf">space_to_depth</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`space_to_depth`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`space_to_depth`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">space_to_depth</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.diag"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.diag">[docs]</a> <span class="k">def</span> <span class="nf">diag</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`diag`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`diag`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">diag</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.sum"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.sum">[docs]</a> <span class="k">def</span> <span class="nf">sum</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`sum`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`sum`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.nansum"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.nansum">[docs]</a> <span class="k">def</span> <span class="nf">nansum</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`nansum`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`nansum`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">nansum</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.prod"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.prod">[docs]</a> <span class="k">def</span> <span class="nf">prod</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`prod`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`prod`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">prod</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.nanprod"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.nanprod">[docs]</a> <span class="k">def</span> <span class="nf">nanprod</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`nanprod`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`nanprod`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">nanprod</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.mean"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.mean">[docs]</a> <span class="k">def</span> <span class="nf">mean</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`mean`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`mean`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.max"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.max">[docs]</a> <span class="k">def</span> <span class="nf">max</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`max`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`max`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.min"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.min">[docs]</a> <span class="k">def</span> <span class="nf">min</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`min`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`min`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">min</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.norm"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.norm">[docs]</a> <span class="k">def</span> <span class="nf">norm</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`norm`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`norm`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">norm</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.round"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.round">[docs]</a> <span class="k">def</span> <span class="nf">round</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`round`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`round`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.rint"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.rint">[docs]</a> <span class="k">def</span> <span class="nf">rint</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`rint`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`rint`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">rint</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.fix"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.fix">[docs]</a> <span class="k">def</span> <span class="nf">fix</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`fix`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`fix`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">fix</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.floor"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.floor">[docs]</a> <span class="k">def</span> <span class="nf">floor</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`floor`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`floor`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">floor</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.ceil"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.ceil">[docs]</a> <span class="k">def</span> <span class="nf">ceil</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`ceil`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`ceil`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.trunc"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.trunc">[docs]</a> <span class="k">def</span> <span class="nf">trunc</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`trunc`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`trunc`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">trunc</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.sin"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.sin">[docs]</a> <span class="k">def</span> <span class="nf">sin</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`sin`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`sin`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.cos"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.cos">[docs]</a> <span class="k">def</span> <span class="nf">cos</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`cos`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`cos`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">cos</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.tan"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.tan">[docs]</a> <span class="k">def</span> <span class="nf">tan</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`tan`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`tan`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">tan</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.arcsin"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.arcsin">[docs]</a> <span class="k">def</span> <span class="nf">arcsin</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`arcsin`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`arcsin`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">arcsin</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.arccos"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.arccos">[docs]</a> <span class="k">def</span> <span class="nf">arccos</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`arccos`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`arccos`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">arccos</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.arctan"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.arctan">[docs]</a> <span class="k">def</span> <span class="nf">arctan</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`arctan`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`arctan`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">arctan</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.degrees"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.degrees">[docs]</a> <span class="k">def</span> <span class="nf">degrees</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`degrees`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`degrees`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">degrees</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.radians"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.radians">[docs]</a> <span class="k">def</span> <span class="nf">radians</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`radians`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`radians`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">radians</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.sinh"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.sinh">[docs]</a> <span class="k">def</span> <span class="nf">sinh</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`sinh`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`sinh`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">sinh</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.cosh"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.cosh">[docs]</a> <span class="k">def</span> <span class="nf">cosh</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`cosh`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`cosh`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">cosh</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.tanh"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.tanh">[docs]</a> <span class="k">def</span> <span class="nf">tanh</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`tanh`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`tanh`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">tanh</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.arcsinh"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.arcsinh">[docs]</a> <span class="k">def</span> <span class="nf">arcsinh</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`arcsinh`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`arcsinh`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">arcsinh</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.arccosh"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.arccosh">[docs]</a> <span class="k">def</span> <span class="nf">arccosh</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`arccosh`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`arccosh`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">arccosh</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.arctanh"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.arctanh">[docs]</a> <span class="k">def</span> <span class="nf">arctanh</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`arctanh`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`arctanh`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">arctanh</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.exp"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.exp">[docs]</a> <span class="k">def</span> <span class="nf">exp</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`exp`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`exp`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.expm1"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.expm1">[docs]</a> <span class="k">def</span> <span class="nf">expm1</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`expm1`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`expm1`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">expm1</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.log"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.log">[docs]</a> <span class="k">def</span> <span class="nf">log</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`log`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`log`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.log10"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.log10">[docs]</a> <span class="k">def</span> <span class="nf">log10</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`log10`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`log10`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">log10</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.log2"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.log2">[docs]</a> <span class="k">def</span> <span class="nf">log2</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`log2`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`log2`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">log2</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.log1p"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.log1p">[docs]</a> <span class="k">def</span> <span class="nf">log1p</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`log1p`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`log1p`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">log1p</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.log_sigmoid"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.log_sigmoid">[docs]</a> <span class="k">def</span> <span class="nf">log_sigmoid</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`log_sigmoid`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`log_sigmoid`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">log_sigmoid</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.mish"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.mish">[docs]</a> <span class="k">def</span> <span class="nf">mish</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`mish`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`mish`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">mish</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.sqrt"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.sqrt">[docs]</a> <span class="k">def</span> <span class="nf">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`sqrt`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`sqrt`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.rsqrt"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.rsqrt">[docs]</a> <span class="k">def</span> <span class="nf">rsqrt</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`rsqrt`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`rsqrt`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">rsqrt</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.cbrt"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.cbrt">[docs]</a> <span class="k">def</span> <span class="nf">cbrt</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`cbrt`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`cbrt`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">cbrt</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.rcbrt"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.rcbrt">[docs]</a> <span class="k">def</span> <span class="nf">rcbrt</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`rcbrt`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`rcbrt`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">rcbrt</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.square"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.square">[docs]</a> <span class="k">def</span> <span class="nf">square</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`square`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`square`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">square</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.reciprocal"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.reciprocal">[docs]</a> <span class="k">def</span> <span class="nf">reciprocal</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`reciprocal`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`reciprocal`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">reciprocal</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.relu"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.relu">[docs]</a> <span class="k">def</span> <span class="nf">relu</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`relu`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`relu`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.sigmoid"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.sigmoid">[docs]</a> <span class="k">def</span> <span class="nf">sigmoid</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`sigmoid`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`sigmoid`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">sigmoid</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.softmax"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.softmax">[docs]</a> <span class="k">def</span> <span class="nf">softmax</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`softmax`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`softmax`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">softmax</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.log_softmax"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.log_softmax">[docs]</a> <span class="k">def</span> <span class="nf">log_softmax</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`log_softmax`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`log_softmax`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">log_softmax</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.softmin"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.softmin">[docs]</a> <span class="k">def</span> <span class="nf">softmin</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`softmin`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`softmin`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">softmin</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.squeeze"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.squeeze">[docs]</a> <span class="k">def</span> <span class="nf">squeeze</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> <span class="c1"># pylint: disable=unused-argument</span> |
| <span class="w"> </span><span class="sd">"""Convenience fluent method for :py:func:`squeeze`.</span> |
| |
| <span class="sd"> The arguments are the same as for :py:func:`squeeze`, with</span> |
| <span class="sd"> this array as data.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">op</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="n">axis</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Symbol.get_backend_symbol"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.get_backend_symbol">[docs]</a> <span class="k">def</span> <span class="nf">get_backend_symbol</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">backend</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Return symbol for target backend.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> backend : str</span> |
| <span class="sd"> The backend names.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> out : Symbol</span> |
| <span class="sd"> The created Symbol for target backend.</span> |
| <span class="sd"> """</span> |
| <span class="n">out</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXGenBackendSubgraph</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> <span class="n">c_str</span><span class="p">(</span><span class="n">backend</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">out</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="n">Symbol</span><span class="p">(</span><span class="n">out</span><span class="p">)</span></div> |
| |
| <span class="k">def</span> <span class="nf">wait_to_read</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">NotImplementedForSymbol</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">wait_to_read</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">asnumpy</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">NotImplementedForSymbol</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">asscalar</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">NotImplementedForSymbol</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">asscalar</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">copy</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">NotImplementedForSymbol</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">copy</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">as_in_context</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">NotImplementedForSymbol</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">as_in_context</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">detach</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">NotImplementedForSymbol</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">detach</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">backward</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">NotImplementedForSymbol</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">backward</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> |
| |
| |
| <div class="viewcode-block" id="Symbol.has_dynamic_shape_op"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Symbol.has_dynamic_shape_op">[docs]</a> <span class="k">def</span> <span class="nf">has_dynamic_shape_op</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Check if any dynamic shape op is present in the symbol.</span> |
| <span class="sd"> """</span> |
| <span class="n">has_dynamic_shape</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_bool</span><span class="p">(</span><span class="kc">False</span><span class="p">)</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXCheckDynamicShapeOp</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">handle</span><span class="p">,</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">has_dynamic_shape</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="n">has_dynamic_shape</span><span class="o">.</span><span class="n">value</span></div></div> |
| |
| <div class="viewcode-block" id="var"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.var">[docs]</a><span class="k">def</span> <span class="nf">var</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">attr</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">lr_mult</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">wd_mult</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> |
| <span class="n">init</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">stype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">profiler_scope</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Creates a symbolic variable with specified name.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> data = mx.sym.Variable('data', attr={'a': 'b'})</span> |
| <span class="sd"> >>> data</span> |
| <span class="sd"> <Symbol data></span> |
| <span class="sd"> >>> csr_data = mx.sym.Variable('csr_data', stype='csr')</span> |
| <span class="sd"> >>> csr_data</span> |
| <span class="sd"> <Symbol csr_data></span> |
| <span class="sd"> >>> row_sparse_weight = mx.sym.Variable('weight', stype='row_sparse')</span> |
| <span class="sd"> >>> row_sparse_weight</span> |
| <span class="sd"> <Symbol weight></span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> name : str</span> |
| <span class="sd"> Variable name.</span> |
| <span class="sd"> attr : Dict of strings</span> |
| <span class="sd"> Additional attributes to set on the variable. Format {string : string}.</span> |
| <span class="sd"> shape : tuple</span> |
| <span class="sd"> The shape of a variable. If specified, this will be used during the shape inference.</span> |
| <span class="sd"> If one has specified a different shape for this variable using</span> |
| <span class="sd"> a keyword argument when calling shape inference, this shape information will be ignored.</span> |
| <span class="sd"> lr_mult : float</span> |
| <span class="sd"> The learning rate multiplier for input variable.</span> |
| <span class="sd"> wd_mult : float</span> |
| <span class="sd"> Weight decay multiplier for input variable.</span> |
| <span class="sd"> dtype : str or numpy.dtype</span> |
| <span class="sd"> The dtype for input variable. If not specified, this value will be inferred.</span> |
| <span class="sd"> init : initializer (mxnet.init.*)</span> |
| <span class="sd"> Initializer for this variable to (optionally) override the default initializer.</span> |
| <span class="sd"> stype : str</span> |
| <span class="sd"> The storage type of the variable, such as 'row_sparse', 'csr', 'default', etc</span> |
| <span class="sd"> profiler_scope : str</span> |
| <span class="sd"> The profiler scope for input variable.</span> |
| <span class="sd"> kwargs : Additional attribute variables</span> |
| <span class="sd"> Additional attributes must start and end with double underscores.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> variable : Symbol</span> |
| <span class="sd"> A symbol corresponding to an input to the computation graph.</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">string_types</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">'Expect a string for variable `name`'</span><span class="p">)</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolCreateVariable</span><span class="p">(</span><span class="n">c_str</span><span class="p">(</span><span class="n">name</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">handle</span><span class="p">)))</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">Symbol</span><span class="p">(</span><span class="n">handle</span><span class="p">)</span> |
| <span class="n">attr</span> <span class="o">=</span> <span class="n">attribute</span><span class="o">.</span><span class="n">current</span><span class="p">()</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">attr</span><span class="p">)</span> |
| <span class="n">attr</span> <span class="o">=</span> <span class="p">{}</span> <span class="k">if</span> <span class="n">attr</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="n">attr</span> |
| <span class="k">if</span> <span class="n">shape</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">attr</span><span class="p">[</span><span class="s1">'__shape__'</span><span class="p">]</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">shape</span><span class="p">)</span> |
| <span class="k">if</span> <span class="n">lr_mult</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">attr</span><span class="p">[</span><span class="s1">'__lr_mult__'</span><span class="p">]</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">lr_mult</span><span class="p">)</span> |
| <span class="k">if</span> <span class="n">wd_mult</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">attr</span><span class="p">[</span><span class="s1">'__wd_mult__'</span><span class="p">]</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">wd_mult</span><span class="p">)</span> |
| <span class="k">if</span> <span class="n">dtype</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">attr</span><span class="p">[</span><span class="s1">'__dtype__'</span><span class="p">]</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">dtype_np_to_mx</span><span class="p">(</span><span class="n">dtype</span><span class="p">))</span> |
| <span class="k">if</span> <span class="n">init</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">init</span><span class="p">,</span> <span class="n">string_types</span><span class="p">):</span> |
| <span class="n">init</span> <span class="o">=</span> <span class="n">init</span><span class="o">.</span><span class="n">dumps</span><span class="p">()</span> |
| <span class="n">attr</span><span class="p">[</span><span class="s1">'__init__'</span><span class="p">]</span> <span class="o">=</span> <span class="n">init</span> |
| <span class="k">if</span> <span class="n">stype</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">attr</span><span class="p">[</span><span class="s1">'__storage_type__'</span><span class="p">]</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">_STORAGE_TYPE_STR_TO_ID</span><span class="p">[</span><span class="n">stype</span><span class="p">])</span> |
| <span class="k">if</span> <span class="n">profiler_scope</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">attr</span><span class="p">[</span><span class="s1">'__profiler_scope__'</span><span class="p">]</span> <span class="o">=</span> <span class="n">profiler_scope</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">attr</span><span class="p">[</span><span class="s1">'__profiler_scope__'</span><span class="p">]</span> <span class="o">=</span> <span class="n">_current_profiler_scope</span><span class="o">.</span><span class="n">get</span><span class="p">()</span> |
| <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> |
| <span class="k">if</span> <span class="n">k</span><span class="o">.</span><span class="n">startswith</span><span class="p">(</span><span class="s1">'__'</span><span class="p">)</span> <span class="ow">and</span> <span class="n">k</span><span class="o">.</span><span class="n">endswith</span><span class="p">(</span><span class="s1">'__'</span><span class="p">):</span> |
| <span class="n">attr</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">v</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Attribute name=</span><span class="si">{</span><span class="n">k</span><span class="si">}</span><span class="s1"> is not supported.'</span> |
| <span class="s1">' Additional attributes must start and end with double underscores,'</span> |
| <span class="s1">' e.g, __yourattr__'</span><span class="p">)</span> |
| <span class="n">ret</span><span class="o">.</span><span class="n">_set_attr</span><span class="p">(</span><span class="o">**</span><span class="n">attr</span><span class="p">)</span> |
| <span class="k">return</span> <span class="n">ret</span></div> |
| |
| |
| <span class="c1"># for back compatibility</span> |
| <span class="n">Variable</span> <span class="o">=</span> <span class="n">var</span> |
| |
| |
| <div class="viewcode-block" id="Group"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.Group">[docs]</a><span class="k">def</span> <span class="nf">Group</span><span class="p">(</span><span class="n">symbols</span><span class="p">,</span> <span class="n">create_fn</span><span class="o">=</span><span class="n">Symbol</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Creates a symbol that contains a collection of other symbols, grouped together.</span> |
| <span class="sd"> A classic symbol (`mx.sym.Symbol`) will be returned if all the symbols in the list</span> |
| <span class="sd"> are of that type; a numpy symbol (`mx.sym.np._Symbol`) will be returned if all the</span> |
| <span class="sd"> symbols in the list are of that type. A type error will be raised if a list of mixed</span> |
| <span class="sd"> classic and numpy symbols are provided.</span> |
| |
| <span class="sd"> Example</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> >>> a = mx.sym.Variable('a')</span> |
| <span class="sd"> >>> b = mx.sym.Variable('b')</span> |
| <span class="sd"> >>> mx.sym.Group([a,b])</span> |
| <span class="sd"> <Symbol Grouped></span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> symbols : list</span> |
| <span class="sd"> List of symbols to be grouped.</span> |
| |
| <span class="sd"> create_fn : mx.sym.Symbol or mx.sym.np._Symbol</span> |
| <span class="sd"> Symbol class for creating the grouped symbol.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> sym : Symbol</span> |
| <span class="sd"> A group symbol.</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="n">symbols</span> <span class="ow">or</span> <span class="nb">any</span><span class="p">(</span><span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">sym</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">)</span> <span class="k">for</span> <span class="n">sym</span> <span class="ow">in</span> <span class="n">symbols</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">'Expected a list of symbols as input'</span><span class="p">)</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolCreateGroup</span><span class="p">(</span> |
| <span class="n">mx_uint</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">symbols</span><span class="p">)),</span> |
| <span class="n">c_handle_array</span><span class="p">(</span><span class="n">symbols</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">handle</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="n">create_fn</span><span class="p">(</span><span class="n">handle</span><span class="p">)</span></div> |
| |
| |
| <div class="viewcode-block" id="load"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.load">[docs]</a><span class="k">def</span> <span class="nf">load</span><span class="p">(</span><span class="n">fname</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Loads symbol from a JSON file.</span> |
| |
| <span class="sd"> You can also use pickle to do the job if you only work on python.</span> |
| <span class="sd"> The advantage of load/save is the file is language agnostic.</span> |
| <span class="sd"> This means the file saved using save can be loaded by other language binding of mxnet.</span> |
| <span class="sd"> You also get the benefit being able to directly load/save from cloud storage(S3, HDFS).</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> fname : str</span> |
| <span class="sd"> The name of the file, examples:</span> |
| |
| <span class="sd"> - `s3://my-bucket/path/my-s3-symbol`</span> |
| <span class="sd"> - `hdfs://my-bucket/path/my-hdfs-symbol`</span> |
| <span class="sd"> - `/path-to/my-local-symbol`</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> sym : Symbol</span> |
| <span class="sd"> The loaded symbol.</span> |
| |
| <span class="sd"> See Also</span> |
| <span class="sd"> --------</span> |
| <span class="sd"> Symbol.save : Used to save symbol into file.</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">fname</span><span class="p">,</span> <span class="n">string_types</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">'fname need to be string'</span><span class="p">)</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolCreateFromFile</span><span class="p">(</span><span class="n">c_str</span><span class="p">(</span><span class="n">fname</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">handle</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="n">Symbol</span><span class="p">(</span><span class="n">handle</span><span class="p">)</span></div> |
| |
| |
| <div class="viewcode-block" id="fromjson"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.fromjson">[docs]</a><span class="k">def</span> <span class="nf">fromjson</span><span class="p">(</span><span class="n">json_str</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Loads symbol from json string.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> json_str : str</span> |
| <span class="sd"> A JSON string.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> sym : Symbol</span> |
| <span class="sd"> The loaded symbol.</span> |
| |
| <span class="sd"> See Also</span> |
| <span class="sd"> --------</span> |
| <span class="sd"> Symbol.tojson : Used to save symbol into json string.</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">json_str</span><span class="p">,</span> <span class="n">string_types</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">'fname required to be string'</span><span class="p">)</span> |
| <span class="n">handle</span> <span class="o">=</span> <span class="n">SymbolHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolCreateFromJSON</span><span class="p">(</span><span class="n">c_str</span><span class="p">(</span><span class="n">json_str</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">handle</span><span class="p">)))</span> |
| <span class="k">return</span> <span class="n">Symbol</span><span class="p">(</span><span class="n">handle</span><span class="p">)</span></div> |
| |
| |
| <span class="c1"># pylint: disable=no-member</span> |
| <span class="c1"># pylint: disable=redefined-builtin</span> |
| <div class="viewcode-block" id="pow"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.pow">[docs]</a><span class="k">def</span> <span class="nf">pow</span><span class="p">(</span><span class="n">base</span><span class="p">,</span> <span class="n">exp</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Returns element-wise result of base element raised to powers from exp element.</span> |
| |
| <span class="sd"> Both inputs can be Symbol or scalar number.</span> |
| <span class="sd"> Broadcasting is not supported. Use `broadcast_pow` instead.</span> |
| |
| <span class="sd"> `sym.pow` is being deprecated, please use `sym.power` instead.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ---------</span> |
| <span class="sd"> base : Symbol or scalar</span> |
| <span class="sd"> The base symbol</span> |
| <span class="sd"> exp : Symbol or scalar</span> |
| <span class="sd"> The exponent symbol</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> Symbol or scalar</span> |
| <span class="sd"> The bases in x raised to the exponents in y.</span> |
| |
| <span class="sd"> Examples</span> |
| <span class="sd"> --------</span> |
| <span class="sd"> >>> mx.sym.pow(2, 3)</span> |
| <span class="sd"> 8</span> |
| <span class="sd"> >>> x = mx.sym.Variable('x')</span> |
| <span class="sd"> >>> y = mx.sym.Variable('y')</span> |
| <span class="sd"> >>> z = mx.sym.pow(x, 2)</span> |
| <span class="sd"> >>> z.eval(x=mx.nd.array([1,2]))[0].asnumpy()</span> |
| <span class="sd"> array([ 1., 4.], dtype=float32)</span> |
| <span class="sd"> >>> z = mx.sym.pow(3, y)</span> |
| <span class="sd"> >>> z.eval(y=mx.nd.array([2,3]))[0].asnumpy()</span> |
| <span class="sd"> array([ 9., 27.], dtype=float32)</span> |
| <span class="sd"> >>> z = mx.sym.pow(x, y)</span> |
| <span class="sd"> >>> z.eval(x=mx.nd.array([3,4]), y=mx.nd.array([2,3]))[0].asnumpy()</span> |
| <span class="sd"> array([ 9., 64.], dtype=float32)</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">base</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">exp</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_Power</span><span class="p">(</span><span class="n">base</span><span class="p">,</span> <span class="n">exp</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">base</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">exp</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_PowerScalar</span><span class="p">(</span><span class="n">base</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">exp</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">base</span><span class="p">,</span> <span class="n">Number</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">exp</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_RPowerScalar</span><span class="p">(</span><span class="n">exp</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">base</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">base</span><span class="p">,</span> <span class="n">Number</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">exp</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">base</span><span class="o">**</span><span class="n">exp</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'types (</span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">base</span><span class="p">))</span><span class="si">}</span><span class="s1">, </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">exp</span><span class="p">))</span><span class="si">}</span><span class="s1">) not supported'</span><span class="p">)</span></div> |
| |
| |
| <div class="viewcode-block" id="power"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.power">[docs]</a><span class="k">def</span> <span class="nf">power</span><span class="p">(</span><span class="n">base</span><span class="p">,</span> <span class="n">exp</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Returns element-wise result of base element raised to powers from exp element.</span> |
| |
| <span class="sd"> Both inputs can be Symbol or scalar number.</span> |
| <span class="sd"> Broadcasting is not supported. Use `broadcast_pow` instead.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ---------</span> |
| <span class="sd"> base : Symbol or scalar</span> |
| <span class="sd"> The base symbol</span> |
| <span class="sd"> exp : Symbol or scalar</span> |
| <span class="sd"> The exponent symbol</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> Symbol or scalar</span> |
| <span class="sd"> The bases in x raised to the exponents in y.</span> |
| |
| <span class="sd"> Examples</span> |
| <span class="sd"> --------</span> |
| <span class="sd"> >>> mx.sym.power(2, 3)</span> |
| <span class="sd"> 8</span> |
| <span class="sd"> >>> x = mx.sym.Variable('x')</span> |
| <span class="sd"> >>> y = mx.sym.Variable('y')</span> |
| <span class="sd"> >>> z = mx.sym.power(x, 2)</span> |
| <span class="sd"> >>> z.eval(x=mx.nd.array([1,2]))[0].asnumpy()</span> |
| <span class="sd"> array([ 1., 4.], dtype=float32)</span> |
| <span class="sd"> >>> z = mx.sym.power(3, y)</span> |
| <span class="sd"> >>> z.eval(y=mx.nd.array([2,3]))[0].asnumpy()</span> |
| <span class="sd"> array([ 9., 27.], dtype=float32)</span> |
| <span class="sd"> >>> z = mx.sym.power(x, y)</span> |
| <span class="sd"> >>> z.eval(x=mx.nd.array([3,4]), y=mx.nd.array([2,3]))[0].asnumpy()</span> |
| <span class="sd"> array([ 9., 64.], dtype=float32)</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="nb">pow</span><span class="p">(</span><span class="n">base</span><span class="p">,</span> <span class="n">exp</span><span class="p">)</span></div> |
| |
| |
| <span class="c1"># pylint: disable=no-member</span> |
| <span class="c1"># pylint: disable=redefined-builtin</span> |
| <div class="viewcode-block" id="maximum"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.maximum">[docs]</a><span class="k">def</span> <span class="nf">maximum</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">right</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Returns element-wise maximum of the input elements.</span> |
| |
| <span class="sd"> Both inputs can be Symbol or scalar number. Broadcasting is not supported.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ---------</span> |
| <span class="sd"> left : Symbol or scalar</span> |
| <span class="sd"> First symbol to be compared.</span> |
| <span class="sd"> right : Symbol or scalar</span> |
| <span class="sd"> Second symbol to be compared.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> Symbol or scalar</span> |
| <span class="sd"> The element-wise maximum of the input symbols.</span> |
| |
| <span class="sd"> Examples</span> |
| <span class="sd"> --------</span> |
| <span class="sd"> >>> mx.sym.maximum(2, 3.5)</span> |
| <span class="sd"> 3.5</span> |
| <span class="sd"> >>> x = mx.sym.Variable('x')</span> |
| <span class="sd"> >>> y = mx.sym.Variable('y')</span> |
| <span class="sd"> >>> z = mx.sym.maximum(x, 4)</span> |
| <span class="sd"> >>> z.eval(x=mx.nd.array([3,5,2,10]))[0].asnumpy()</span> |
| <span class="sd"> array([ 4., 5., 4., 10.], dtype=float32)</span> |
| <span class="sd"> >>> z = mx.sym.maximum(x, y)</span> |
| <span class="sd"> >>> z.eval(x=mx.nd.array([3,4]), y=mx.nd.array([10,2]))[0].asnumpy()</span> |
| <span class="sd"> array([ 10., 4.], dtype=float32)</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">right</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_Maximum</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">right</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">right</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_MaximumScalar</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">right</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">Number</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">right</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_MaximumScalar</span><span class="p">(</span><span class="n">right</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">left</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">Number</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">right</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">left</span> <span class="k">if</span> <span class="n">left</span> <span class="o">></span> <span class="n">right</span> <span class="k">else</span> <span class="n">right</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'types (</span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">left</span><span class="p">))</span><span class="si">}</span><span class="s1">, </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">right</span><span class="p">))</span><span class="si">}</span><span class="s1">) not supported'</span><span class="p">)</span></div> |
| |
| |
| <span class="c1"># pylint: disable=no-member</span> |
| <span class="c1"># pylint: disable=redefined-builtin</span> |
| <div class="viewcode-block" id="minimum"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.minimum">[docs]</a><span class="k">def</span> <span class="nf">minimum</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">right</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Returns element-wise minimum of the input elements.</span> |
| |
| <span class="sd"> Both inputs can be Symbol or scalar number. Broadcasting is not supported.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ---------</span> |
| <span class="sd"> left : Symbol or scalar</span> |
| <span class="sd"> First symbol to be compared.</span> |
| <span class="sd"> right : Symbol or scalar</span> |
| <span class="sd"> Second symbol to be compared.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> Symbol or scalar</span> |
| <span class="sd"> The element-wise minimum of the input symbols.</span> |
| |
| <span class="sd"> Examples</span> |
| <span class="sd"> --------</span> |
| <span class="sd"> >>> mx.sym.minimum(2, 3.5)</span> |
| <span class="sd"> 2</span> |
| <span class="sd"> >>> x = mx.sym.Variable('x')</span> |
| <span class="sd"> >>> y = mx.sym.Variable('y')</span> |
| <span class="sd"> >>> z = mx.sym.minimum(x, 4)</span> |
| <span class="sd"> >>> z.eval(x=mx.nd.array([3,5,2,10]))[0].asnumpy()</span> |
| <span class="sd"> array([ 3., 4., 2., 4.], dtype=float32)</span> |
| <span class="sd"> >>> z = mx.sym.minimum(x, y)</span> |
| <span class="sd"> >>> z.eval(x=mx.nd.array([3,4]), y=mx.nd.array([10,2]))[0].asnumpy()</span> |
| <span class="sd"> array([ 3., 2.], dtype=float32)</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">right</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_Minimum</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">right</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">right</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_MinimumScalar</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">right</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">Number</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">right</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_MinimumScalar</span><span class="p">(</span><span class="n">right</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">left</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">Number</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">right</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">left</span> <span class="k">if</span> <span class="n">left</span> <span class="o"><</span> <span class="n">right</span> <span class="k">else</span> <span class="n">right</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'types (</span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">left</span><span class="p">))</span><span class="si">}</span><span class="s1">, </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">right</span><span class="p">))</span><span class="si">}</span><span class="s1">) not supported'</span><span class="p">)</span></div> |
| |
| |
| <span class="c1"># pylint: disable=no-member</span> |
| <span class="c1"># pylint: disable=redefined-builtin</span> |
| <div class="viewcode-block" id="hypot"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.hypot">[docs]</a><span class="k">def</span> <span class="nf">hypot</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">right</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Given the "legs" of a right triangle, returns its hypotenuse.</span> |
| |
| <span class="sd"> Equivalent to :math:`\\sqrt(left^2 + right^2)`, element-wise.</span> |
| <span class="sd"> Both inputs can be Symbol or scalar number. Broadcasting is not supported.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ---------</span> |
| <span class="sd"> left : Symbol or scalar</span> |
| <span class="sd"> First leg of the triangle(s).</span> |
| <span class="sd"> right : Symbol or scalar</span> |
| <span class="sd"> Second leg of the triangle(s).</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> Symbol or scalar</span> |
| <span class="sd"> The hypotenuse of the triangle(s)</span> |
| |
| <span class="sd"> Examples</span> |
| <span class="sd"> --------</span> |
| <span class="sd"> >>> mx.sym.hypot(3, 4)</span> |
| <span class="sd"> 5.0</span> |
| <span class="sd"> >>> x = mx.sym.Variable('x')</span> |
| <span class="sd"> >>> y = mx.sym.Variable('y')</span> |
| <span class="sd"> >>> z = mx.sym.hypot(x, 4)</span> |
| <span class="sd"> >>> z.eval(x=mx.nd.array([3,5,2]))[0].asnumpy()</span> |
| <span class="sd"> array([ 5., 6.40312433, 4.47213602], dtype=float32)</span> |
| <span class="sd"> >>> z = mx.sym.hypot(x, y)</span> |
| <span class="sd"> >>> z.eval(x=mx.nd.array([3,4]), y=mx.nd.array([10,2]))[0].asnumpy()</span> |
| <span class="sd"> array([ 10.44030666, 4.47213602], dtype=float32)</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">right</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_Hypot</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">right</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">right</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_HypotScalar</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">right</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">Number</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">right</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_HypotScalar</span><span class="p">(</span><span class="n">right</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="n">left</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">Number</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">right</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_numpy</span><span class="o">.</span><span class="n">hypot</span><span class="p">(</span><span class="n">left</span><span class="p">,</span> <span class="n">right</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'types (</span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">left</span><span class="p">))</span><span class="si">}</span><span class="s1">, </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">right</span><span class="p">))</span><span class="si">}</span><span class="s1">) not supported'</span><span class="p">)</span></div> |
| |
| |
| <div class="viewcode-block" id="eye"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.eye">[docs]</a><span class="k">def</span> <span class="nf">eye</span><span class="p">(</span><span class="n">N</span><span class="p">,</span> <span class="n">M</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Returns a new symbol of 2-D shpae, filled with ones on the diagonal and zeros elsewhere.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> N: int</span> |
| <span class="sd"> Number of rows in the output.</span> |
| <span class="sd"> M: int, optional</span> |
| <span class="sd"> Number of columns in the output. If 0, defaults to N.</span> |
| <span class="sd"> k: int, optional</span> |
| <span class="sd"> Index of the diagonal: 0 (the default) refers to the main diagonal,</span> |
| <span class="sd"> a positive value refers to an upper diagonal,</span> |
| <span class="sd"> and a negative value to a lower diagonal.</span> |
| <span class="sd"> dtype : str or numpy.dtype, optional</span> |
| <span class="sd"> The value type of the inner value, default to ``np.float32``.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> out : Symbol</span> |
| <span class="sd"> The created Symbol.</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="n">dtype</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">dtype</span> <span class="o">=</span> <span class="n">_numpy</span><span class="o">.</span><span class="n">float32</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_eye</span><span class="p">(</span><span class="n">N</span><span class="p">,</span> <span class="n">M</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="zeros"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.zeros">[docs]</a><span class="k">def</span> <span class="nf">zeros</span><span class="p">(</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Returns a new symbol of given shape and type, filled with zeros.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> shape : int or sequence of ints</span> |
| <span class="sd"> Shape of the new array.</span> |
| <span class="sd"> dtype : str or numpy.dtype, optional</span> |
| <span class="sd"> The value type of the inner value, default to ``np.float32``.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> out : Symbol</span> |
| <span class="sd"> The created Symbol.</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="n">dtype</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">dtype</span> <span class="o">=</span> <span class="n">_numpy</span><span class="o">.</span><span class="n">float32</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_zeros</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| |
| <div class="viewcode-block" id="ones"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.ones">[docs]</a><span class="k">def</span> <span class="nf">ones</span><span class="p">(</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Returns a new symbol of given shape and type, filled with ones.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> shape : int or sequence of ints</span> |
| <span class="sd"> Shape of the new array.</span> |
| <span class="sd"> dtype : str or numpy.dtype, optional</span> |
| <span class="sd"> The value type of the inner value, default to ``np.float32``.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> out : Symbol</span> |
| <span class="sd"> The created Symbol</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="n">dtype</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">dtype</span> <span class="o">=</span> <span class="n">_numpy</span><span class="o">.</span><span class="n">float32</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_ones</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| |
| <div class="viewcode-block" id="full"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.full">[docs]</a><span class="k">def</span> <span class="nf">full</span><span class="p">(</span><span class="n">shape</span><span class="p">,</span> <span class="n">val</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Returns a new array of given shape and type, filled with the given value `val`.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> shape : int or sequence of ints</span> |
| <span class="sd"> Shape of the new array.</span> |
| <span class="sd"> val : scalar</span> |
| <span class="sd"> Fill value.</span> |
| <span class="sd"> dtype : str or numpy.dtype, optional</span> |
| <span class="sd"> The value type of the inner value, default to ``np.float32``.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> out : Symbol</span> |
| <span class="sd"> The created Symbol</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="n">dtype</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">dtype</span> <span class="o">=</span> <span class="n">_numpy</span><span class="o">.</span><span class="n">float32</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_full</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span> <span class="n">value</span><span class="o">=</span><span class="nb">float</span><span class="p">(</span><span class="n">val</span><span class="p">),</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div> |
| |
| <span class="c1"># pylint: disable=redefined-outer-name</span> |
| <div class="viewcode-block" id="arange"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.arange">[docs]</a><span class="k">def</span> <span class="nf">arange</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">stop</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">repeat</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">infer_range</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Returns evenly spaced values within a given interval.</span> |
| |
| <span class="sd"> Values are generated within the half-open interval [`start`, `stop`). In other</span> |
| <span class="sd"> words, the interval includes `start` but excludes `stop`. The function is</span> |
| <span class="sd"> similar to the built-in Python function `range` and to `numpy.arange`,</span> |
| <span class="sd"> but returns a `Symbol`.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> start : number, optional</span> |
| <span class="sd"> Start of interval. The interval includes this value. The default start value is 0.</span> |
| <span class="sd"> stop : number</span> |
| <span class="sd"> End of interval. The interval does not include this value.</span> |
| <span class="sd"> step : number, optional</span> |
| <span class="sd"> Spacing between values.</span> |
| <span class="sd"> repeat : int, optional</span> |
| <span class="sd"> "The repeating time of all elements.</span> |
| <span class="sd"> E.g repeat=3, the element a will be repeated three times --> a, a, a.</span> |
| <span class="sd"> infer_range : boolean, optional</span> |
| <span class="sd"> When set to True, infer the stop position from the start, step,</span> |
| <span class="sd"> repeat, and output tensor size.</span> |
| <span class="sd"> dtype : str or numpy.dtype, optional</span> |
| <span class="sd"> The value type of the inner value, default to ``np.float32``.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> out : Symbol</span> |
| <span class="sd"> The created Symbol</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="n">dtype</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">dtype</span> <span class="o">=</span> <span class="n">_numpy</span><span class="o">.</span><span class="n">float32</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_arange</span><span class="p">(</span><span class="n">start</span><span class="o">=</span><span class="n">start</span><span class="p">,</span> <span class="n">stop</span><span class="o">=</span><span class="n">stop</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="n">step</span><span class="p">,</span> <span class="n">repeat</span><span class="o">=</span><span class="n">repeat</span><span class="p">,</span> |
| <span class="n">infer_range</span><span class="o">=</span><span class="n">infer_range</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="linspace"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.linspace">[docs]</a><span class="k">def</span> <span class="nf">linspace</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">stop</span><span class="p">,</span> <span class="n">num</span><span class="p">,</span> <span class="n">endpoint</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Return evenly spaced numbers within a specified interval.</span> |
| |
| <span class="sd"> Values are generated within the half-open interval [`start`, `stop`) or</span> |
| <span class="sd"> closed interval [start, stop] depending on whether `endpoint` is True or</span> |
| <span class="sd"> False. The function is similar to `numpy.linspace`, but returns a `Symbol`.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> start : number</span> |
| <span class="sd"> Start of interval.</span> |
| <span class="sd"> stop : number</span> |
| <span class="sd"> End of interval, unless endpoint is set to False. In that case,</span> |
| <span class="sd"> the sequence consists of all but the last of `num + 1` evenly spaced</span> |
| <span class="sd"> samples, so that stop is excluded. Note that the step size changes</span> |
| <span class="sd"> when endpoint is False.</span> |
| <span class="sd"> num : number</span> |
| <span class="sd"> Number of samples to generate. Must be non-negative.</span> |
| <span class="sd"> endpoint : bool</span> |
| <span class="sd"> If True, stop is the last sample. Otherwise, it is not included.</span> |
| <span class="sd"> The default is True.</span> |
| <span class="sd"> dtype : str or numpy.dtype, optional</span> |
| <span class="sd"> The data type of the `NDArray`. The default datatype is `np.float32`.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> out : Symbol</span> |
| <span class="sd"> The created Symbol</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="n">dtype</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">dtype</span> <span class="o">=</span> <span class="n">_numpy</span><span class="o">.</span><span class="n">float32</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_linspace</span><span class="p">(</span><span class="n">start</span><span class="o">=</span><span class="n">start</span><span class="p">,</span> <span class="n">stop</span><span class="o">=</span><span class="n">stop</span><span class="p">,</span> <span class="n">num</span><span class="o">=</span><span class="n">num</span><span class="p">,</span> <span class="n">endpoint</span><span class="o">=</span><span class="n">endpoint</span><span class="p">,</span> |
| <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="histogram"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.histogram">[docs]</a><span class="k">def</span> <span class="nf">histogram</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="nb">range</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Compute the histogram of the input data.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> a : NDArray</span> |
| <span class="sd"> Input data. The histogram is computed over the flattened array.</span> |
| <span class="sd"> bins : int or sequence of scalars</span> |
| <span class="sd"> If bins is an int, it defines the number of equal-width bins in the</span> |
| <span class="sd"> given range (10, by default). If bins is a sequence, it defines the bin edges,</span> |
| <span class="sd"> including the rightmost edge, allowing for non-uniform bin widths.</span> |
| <span class="sd"> range : (float, float), required if bins is an integer</span> |
| <span class="sd"> The lower and upper range of the bins. If not provided, range is simply (a.min(), a.max()).</span> |
| <span class="sd"> Values outside the range are ignored. The first element of the range must be less than or</span> |
| <span class="sd"> equal to the second. range affects the automatic bin computation as well, the range will</span> |
| <span class="sd"> be equally divided by the number of bins.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> out : Symbol</span> |
| <span class="sd"> The created Symbol</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">bins</span><span class="p">,</span> <span class="n">Symbol</span><span class="p">):</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_histogram</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">a</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="n">bins</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> |
| <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">bins</span><span class="p">,</span> <span class="n">integer_types</span><span class="p">):</span> |
| <span class="k">if</span> <span class="nb">range</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"null range is not supported in symbol mode"</span><span class="p">)</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_histogram</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">a</span><span class="p">,</span> <span class="n">bin_cnt</span><span class="o">=</span><span class="n">bins</span><span class="p">,</span> <span class="nb">range</span><span class="o">=</span><span class="nb">range</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> |
| <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"bins argument should be either an integer or an NDArray"</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="split_v2"><a class="viewcode-back" href="../../../api/legacy/symbol/symbol.html#mxnet.symbol.split_v2">[docs]</a><span class="k">def</span> <span class="nf">split_v2</span><span class="p">(</span><span class="n">ary</span><span class="p">,</span> <span class="n">indices_or_sections</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">squeeze_axis</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Split an array into multiple sub-arrays.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> ary : NDArray</span> |
| <span class="sd"> Array to be divided into sub-arrays.</span> |
| <span class="sd"> indices_or_sections : int or tuple of ints</span> |
| <span class="sd"> If `indices_or_sections` is an integer, N, the array will be divided</span> |
| <span class="sd"> into N equal arrays along `axis`. If such a split is not possible,</span> |
| <span class="sd"> an error is raised.</span> |
| <span class="sd"> If `indices_or_sections` is a 1-D array of sorted integers, the entries</span> |
| <span class="sd"> indicate where along `axis` the array is split. For example,</span> |
| <span class="sd"> ``[2, 3]`` would, for ``axis=0``, result in</span> |
| <span class="sd"> - ary[:2]</span> |
| <span class="sd"> - ary[2:3]</span> |
| <span class="sd"> - ary[3:]</span> |
| <span class="sd"> If an index exceeds the dimension of the array along `axis`,</span> |
| <span class="sd"> an empty sub-array is returned correspondingly.</span> |
| <span class="sd"> axis : int, optional</span> |
| <span class="sd"> The axis along which to split, default is 0.</span> |
| <span class="sd"> squeeze_axis: boolean, optional</span> |
| <span class="sd"> Whether to squeeze the axis of sub-arrays or not, only useful when size</span> |
| <span class="sd"> of the sub-arrays are 1 on the `axis`. Default is False.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> out : Symbol</span> |
| <span class="sd"> The created Symbol</span> |
| <span class="sd"> """</span> |
| <span class="n">indices</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="n">sections</span> <span class="o">=</span> <span class="mi">0</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">indices_or_sections</span><span class="p">,</span> <span class="nb">int</span><span class="p">):</span> |
| <span class="n">sections</span> <span class="o">=</span> <span class="n">indices_or_sections</span> |
| <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">indices_or_sections</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span> |
| <span class="n">indices</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="nb">list</span><span class="p">(</span><span class="n">indices_or_sections</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'indices_or_sections must either int or tuple of ints'</span><span class="p">)</span> |
| <span class="k">return</span> <span class="n">_internal</span><span class="o">.</span><span class="n">_split_v2</span><span class="p">(</span><span class="n">ary</span><span class="p">,</span> <span class="n">indices</span><span class="p">,</span> <span class="n">axis</span><span class="p">,</span> <span class="n">squeeze_axis</span><span class="p">,</span> <span class="n">sections</span><span class="p">)</span></div> |
| |
| <span class="n">_set_symbol_class</span><span class="p">(</span><span class="n">Symbol</span><span class="p">)</span> |
| </pre></div> |
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