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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">Getting started with NP on MXNet</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/1-ndarray.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-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-train.html">Step 4: Train the neural network</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/5-predict.html">Step 5: Predict with a pretrained model</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/6-use_gpus.html">Step 6: Use GPUs to increase efficiency</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/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/custom_layer_beginners.html">Customer Layers (Beginners)</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/data_augmentation.html#Spatial-Augmentation">Spatial Augmentation</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/gluon/data/data_augmentation.html#Color-Augmentation">Color Augmentation</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/gluon/data/data_augmentation.html#Composed-Augmentations">Composed Augmentations</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> |
| <li class="toctree-l6"><a class="reference internal" href="../../tutorials/packages/legacy/ndarray/sparse/train_gluon.html">Sparse NDArrays with Gluon</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/mkldnn/index.html">Intel MKL-DNN</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/performance/backend/mkldnn/mkldnn_readme.html">Install MXNet with MKL-DNN</a></li> |
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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">Getting started with NP on MXNet</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/1-ndarray.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-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-train.html">Step 4: Train the neural network</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/5-predict.html">Step 5: Predict with a pretrained model</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/6-use_gpus.html">Step 6: Use GPUs to increase efficiency</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/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> |
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| <li class="toctree-l3"><a class="reference internal" href="../../tutorials/packages/autograd/index.html">Automatic Differentiation</a></li> |
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| <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/custom_layer_beginners.html">Customer Layers (Beginners)</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/gluon/blocks/hybridize.html">Hybridize</a></li> |
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| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/gluon/blocks/naming.html">Parameter and Block Naming</a></li> |
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| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/gluon/data/data_augmentation.html#Spatial-Augmentation">Spatial Augmentation</a></li> |
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| <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> |
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| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/gluon/image/mnist.html">Handwritten Digit Recognition</a></li> |
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| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/gluon/loss/loss.html">Loss functions</a></li> |
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| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/gluon/text/gnmt.html">Google Neural Machine Translation</a></li> |
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| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/gluon/training/fit_api_tutorial.html">MXNet Gluon Fit API</a></li> |
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| <li class="toctree-l6"><a class="reference internal" href="../../tutorials/packages/gluon/training/learning_rates/learning_rate_finder.html">Learning Rate Finder</a></li> |
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| <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> |
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| <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> |
| <li class="toctree-l6"><a class="reference internal" href="../../tutorials/packages/legacy/ndarray/sparse/train_gluon.html">Sparse NDArrays with Gluon</a></li> |
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| </ul> |
| </li> |
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| <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> |
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| <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> |
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| <li class="toctree-l4"><a class="reference external" href="https://mxnet.apache.org/api/faq/visualize_graph">Visualize networks</a></li> |
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| <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> |
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| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/performance/backend/mkldnn/mkldnn_readme.html">Install MXNet with MKL-DNN</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/performance/backend/tvm.html">Use TVM</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/performance/backend/amp.html">Using AMP: Automatic Mixed Precision</a></li> |
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| <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> |
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| <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> |
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| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ndarray.__itruediv__.html">mxnet.np.ndarray.__itruediv__</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ndarray.__imod__.html">mxnet.np.ndarray.__imod__</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ndarray.__reduce__.html">mxnet.np.ndarray.__reduce__</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ndarray.__setstate__.html">mxnet.np.ndarray.__setstate__</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ndarray.__len__.html">mxnet.np.ndarray.__len__</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ndarray.__getitem__.html">mxnet.np.ndarray.__getitem__</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ndarray.__setitem__.html">mxnet.np.ndarray.__setitem__</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ndarray.__int__.html">mxnet.np.ndarray.__int__</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ndarray.__float__.html">mxnet.np.ndarray.__float__</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ndarray.__str__.html">mxnet.np.ndarray.__str__</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ndarray.__repr__.html">mxnet.np.ndarray.__repr__</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../np/arrays.indexing.html">Indexing</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="../np/routines.array-creation.html">Array creation routines</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.eye.html">mxnet.np.eye</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.empty.html">mxnet.np.empty</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.full.html">mxnet.np.full</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.identity.html">mxnet.np.identity</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ones.html">mxnet.np.ones</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ones_like.html">mxnet.np.ones_like</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.zeros.html">mxnet.np.zeros</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.zeros_like.html">mxnet.np.zeros_like</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.array.html">mxnet.np.array</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.copy.html">mxnet.np.copy</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.arange.html">mxnet.np.arange</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.linspace.html">mxnet.np.linspace</a></li> |
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| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.meshgrid.html">mxnet.np.meshgrid</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.tril.html">mxnet.np.tril</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../np/routines.array-manipulation.html">Array manipulation routines</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.reshape.html">mxnet.np.reshape</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ravel.html">mxnet.np.ravel</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ndarray.flatten.html">mxnet.np.ndarray.flatten</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.swapaxes.html">mxnet.np.swapaxes</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ndarray.T.html">mxnet.np.ndarray.T</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.transpose.html">mxnet.np.transpose</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.moveaxis.html">mxnet.np.moveaxis</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.expand_dims.html">mxnet.np.expand_dims</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.squeeze.html">mxnet.np.squeeze</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.broadcast_to.html">mxnet.np.broadcast_to</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.broadcast_arrays.html">mxnet.np.broadcast_arrays</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.concatenate.html">mxnet.np.concatenate</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.stack.html">mxnet.np.stack</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.dstack.html">mxnet.np.dstack</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.vstack.html">mxnet.np.vstack</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.split.html">mxnet.np.split</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.hsplit.html">mxnet.np.hsplit</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.vsplit.html">mxnet.np.vsplit</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.tile.html">mxnet.np.tile</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.repeat.html">mxnet.np.repeat</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.unique.html">mxnet.np.unique</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.reshape.html">mxnet.np.reshape</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.flip.html">mxnet.np.flip</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.roll.html">mxnet.np.roll</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.rot90.html">mxnet.np.rot90</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../np/routines.io.html">Input and output</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.genfromtxt.html">mxnet.np.genfromtxt</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../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="../np/generated/mxnet.np.dot.html">mxnet.np.dot</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.vdot.html">mxnet.np.vdot</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.inner.html">mxnet.np.inner</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.outer.html">mxnet.np.outer</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.tensordot.html">mxnet.np.tensordot</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.einsum.html">mxnet.np.einsum</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.linalg.svd.html">mxnet.np.linalg.svd</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.linalg.norm.html">mxnet.np.linalg.norm</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.trace.html">mxnet.np.trace</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../np/routines.math.html">Mathematical functions</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.sin.html">mxnet.np.sin</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.cos.html">mxnet.np.cos</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.tan.html">mxnet.np.tan</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.arcsin.html">mxnet.np.arcsin</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.arccos.html">mxnet.np.arccos</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.arctan.html">mxnet.np.arctan</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.degrees.html">mxnet.np.degrees</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.radians.html">mxnet.np.radians</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.hypot.html">mxnet.np.hypot</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.arctan2.html">mxnet.np.arctan2</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.deg2rad.html">mxnet.np.deg2rad</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.rad2deg.html">mxnet.np.rad2deg</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.sinh.html">mxnet.np.sinh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.cosh.html">mxnet.np.cosh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.tanh.html">mxnet.np.tanh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.arcsinh.html">mxnet.np.arcsinh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.arccosh.html">mxnet.np.arccosh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.arctanh.html">mxnet.np.arctanh</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.rint.html">mxnet.np.rint</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.fix.html">mxnet.np.fix</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.floor.html">mxnet.np.floor</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ceil.html">mxnet.np.ceil</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.trunc.html">mxnet.np.trunc</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.around.html">mxnet.np.around</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.sum.html">mxnet.np.sum</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.prod.html">mxnet.np.prod</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.cumsum.html">mxnet.np.cumsum</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.exp.html">mxnet.np.exp</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.expm1.html">mxnet.np.expm1</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.log.html">mxnet.np.log</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.log10.html">mxnet.np.log10</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.log2.html">mxnet.np.log2</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.log1p.html">mxnet.np.log1p</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.ldexp.html">mxnet.np.ldexp</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.lcm.html">mxnet.np.lcm</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.add.html">mxnet.np.add</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.reciprocal.html">mxnet.np.reciprocal</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.negative.html">mxnet.np.negative</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.divide.html">mxnet.np.divide</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.power.html">mxnet.np.power</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.subtract.html">mxnet.np.subtract</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.mod.html">mxnet.np.mod</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.multiply.html">mxnet.np.multiply</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.true_divide.html">mxnet.np.true_divide</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.remainder.html">mxnet.np.remainder</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.clip.html">mxnet.np.clip</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.sqrt.html">mxnet.np.sqrt</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.cbrt.html">mxnet.np.cbrt</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.square.html">mxnet.np.square</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.absolute.html">mxnet.np.absolute</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.sign.html">mxnet.np.sign</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.maximum.html">mxnet.np.maximum</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.minimum.html">mxnet.np.minimum</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../np/random/index.html">np.random</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../np/routines.sort.html">Sorting, searching, and counting</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.argmax.html">mxnet.np.argmax</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.argmin.html">mxnet.np.argmin</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../np/routines.statistics.html">Statistics</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.min.html">mxnet.np.min</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.max.html">mxnet.np.max</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.mean.html">mxnet.np.mean</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.std.html">mxnet.np.std</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.var.html">mxnet.np.var</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../np/generated/mxnet.np.histogram.html">mxnet.np.histogram</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../npx/index.html">NPX: NumPy Neural Network Extension</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.set_np.html">mxnet.npx.set_np</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.reset_np.html">mxnet.npx.reset_np</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.cpu.html">mxnet.npx.cpu</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.cpu_pinned.html">mxnet.npx.cpu_pinned</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.gpu.html">mxnet.npx.gpu</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.gpu_memory_info.html">mxnet.npx.gpu_memory_info</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.current_context.html">mxnet.npx.current_context</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.num_gpus.html">mxnet.npx.num_gpus</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.activation.html">mxnet.npx.activation</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.batch_norm.html">mxnet.npx.batch_norm</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.convolution.html">mxnet.npx.convolution</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.dropout.html">mxnet.npx.dropout</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.embedding.html">mxnet.npx.embedding</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.fully_connected.html">mxnet.npx.fully_connected</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.layer_norm.html">mxnet.npx.layer_norm</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.pooling.html">mxnet.npx.pooling</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.rnn.html">mxnet.npx.rnn</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.leaky_relu.html">mxnet.npx.leaky_relu</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.multibox_detection.html">mxnet.npx.multibox_detection</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.multibox_prior.html">mxnet.npx.multibox_prior</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.multibox_target.html">mxnet.npx.multibox_target</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.roi_pooling.html">mxnet.npx.roi_pooling</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../npx/generated/mxnet.npx.sigmoid.html">mxnet.npx.sigmoid</a></li> |
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| |
| <div class="section" id="gluon-symbolblock"> |
| <h1>gluon.SymbolBlock<a class="headerlink" href="#gluon-symbolblock" title="Permalink to this headline">¶</a></h1> |
| <dl class="class"> |
| <dt id="mxnet.gluon.SymbolBlock"> |
| <em class="property">class </em><code class="sig-prename descclassname">mxnet.gluon.</code><code class="sig-name descname">SymbolBlock</code><span class="sig-paren">(</span><em class="sig-param">outputs</em>, <em class="sig-param">inputs</em>, <em class="sig-param">params=None</em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/mxnet/gluon/block.html#SymbolBlock"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.gluon.SymbolBlock" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">mxnet.gluon.block.HybridBlock</span></code></p> |
| <p>Construct block from symbol. This is useful for using pre-trained models |
| as feature extractors. For example, you may want to extract the output |
| from fc2 layer in AlexNet.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>outputs</strong> (<a class="reference internal" href="../legacy/symbol/symbol.html#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a><em> or </em><em>list of Symbol</em>) – The desired output for SymbolBlock.</p></li> |
| <li><p><strong>inputs</strong> (<a class="reference internal" href="../legacy/symbol/symbol.html#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a><em> or </em><em>list of Symbol</em>) – The Variables in output’s argument that should be used as inputs.</p></li> |
| <li><p><strong>params</strong> (<em>dict</em>) – Parameter dictionary for arguments and auxililary states of outputs |
| that are not inputs.</p></li> |
| </ul> |
| </dd> |
| </dl> |
| <p><strong>Methods</strong></p> |
| <table class="longtable docutils align-default"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.apply" title="mxnet.gluon.SymbolBlock.apply"><code class="xref py py-obj docutils literal notranslate"><span class="pre">apply</span></code></a>(fn)</p></td> |
| <td><p>Applies <code class="docutils literal notranslate"><span class="pre">fn</span></code> recursively to every child block as well as self.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.cast" title="mxnet.gluon.SymbolBlock.cast"><code class="xref py py-obj docutils literal notranslate"><span class="pre">cast</span></code></a>(dtype)</p></td> |
| <td><p>Cast this Block to use another data type.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.collect_params" title="mxnet.gluon.SymbolBlock.collect_params"><code class="xref py py-obj docutils literal notranslate"><span class="pre">collect_params</span></code></a>([select])</p></td> |
| <td><p>Returns a <code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code> containing this <code class="xref py py-class docutils literal notranslate"><span class="pre">Block</span></code> and all of its children’s Parameters(default), also can returns the select <code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code> which match some given regular expressions.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.export" title="mxnet.gluon.SymbolBlock.export"><code class="xref py py-obj docutils literal notranslate"><span class="pre">export</span></code></a>(path[, epoch, remove_amp_cast])</p></td> |
| <td><p>Export HybridBlock to json format that can be loaded by <cite>gluon.SymbolBlock.imports</cite> or the C++ interface.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.forward" title="mxnet.gluon.SymbolBlock.forward"><code class="xref py py-obj docutils literal notranslate"><span class="pre">forward</span></code></a>(x, *args)</p></td> |
| <td><p>Defines the forward computation.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.hybrid_forward" title="mxnet.gluon.SymbolBlock.hybrid_forward"><code class="xref py py-obj docutils literal notranslate"><span class="pre">hybrid_forward</span></code></a>(F, x, *args, **kwargs)</p></td> |
| <td><p>Overrides to construct symbolic graph for this <cite>Block</cite>.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.hybridize" title="mxnet.gluon.SymbolBlock.hybridize"><code class="xref py py-obj docutils literal notranslate"><span class="pre">hybridize</span></code></a>([active, backend, backend_opts, clear])</p></td> |
| <td><p>Activates or deactivates <code class="xref py py-class docutils literal notranslate"><span class="pre">HybridBlock</span></code> s recursively.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.imports" title="mxnet.gluon.SymbolBlock.imports"><code class="xref py py-obj docutils literal notranslate"><span class="pre">imports</span></code></a>(symbol_file, input_names[, …])</p></td> |
| <td><p>Import model previously saved by <cite>gluon.HybridBlock.export</cite> as a <cite>gluon.SymbolBlock</cite> for use in Gluon.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.infer_shape" title="mxnet.gluon.SymbolBlock.infer_shape"><code class="xref py py-obj docutils literal notranslate"><span class="pre">infer_shape</span></code></a>(*args)</p></td> |
| <td><p>Infers shape of Parameters from inputs.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.infer_type" title="mxnet.gluon.SymbolBlock.infer_type"><code class="xref py py-obj docutils literal notranslate"><span class="pre">infer_type</span></code></a>(*args)</p></td> |
| <td><p>Infers data type of Parameters from inputs.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.initialize" title="mxnet.gluon.SymbolBlock.initialize"><code class="xref py py-obj docutils literal notranslate"><span class="pre">initialize</span></code></a>([init, ctx, verbose, force_reinit])</p></td> |
| <td><p>Initializes <code class="xref py py-class docutils literal notranslate"><span class="pre">Parameter</span></code> s of this <code class="xref py py-class docutils literal notranslate"><span class="pre">Block</span></code> and its children.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.load_dict" title="mxnet.gluon.SymbolBlock.load_dict"><code class="xref py py-obj docutils literal notranslate"><span class="pre">load_dict</span></code></a>(param_dict[, ctx, allow_missing, …])</p></td> |
| <td><p>Load parameters from dict</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.load_parameters" title="mxnet.gluon.SymbolBlock.load_parameters"><code class="xref py py-obj docutils literal notranslate"><span class="pre">load_parameters</span></code></a>(filename[, ctx, …])</p></td> |
| <td><p>Load parameters from file previously saved by <cite>save_parameters</cite>.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.optimize_for" title="mxnet.gluon.SymbolBlock.optimize_for"><code class="xref py py-obj docutils literal notranslate"><span class="pre">optimize_for</span></code></a>(x, *args[, backend, …])</p></td> |
| <td><p>Partitions the current HybridBlock and optimizes it for a given backend without executing a forward pass.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.register_child" title="mxnet.gluon.SymbolBlock.register_child"><code class="xref py py-obj docutils literal notranslate"><span class="pre">register_child</span></code></a>(block[, name])</p></td> |
| <td><p>Registers block as a child of self.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.register_forward_hook" title="mxnet.gluon.SymbolBlock.register_forward_hook"><code class="xref py py-obj docutils literal notranslate"><span class="pre">register_forward_hook</span></code></a>(hook)</p></td> |
| <td><p>Registers a forward hook on the block.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.register_forward_pre_hook" title="mxnet.gluon.SymbolBlock.register_forward_pre_hook"><code class="xref py py-obj docutils literal notranslate"><span class="pre">register_forward_pre_hook</span></code></a>(hook)</p></td> |
| <td><p>Registers a forward pre-hook on the block.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.register_op_hook" title="mxnet.gluon.SymbolBlock.register_op_hook"><code class="xref py py-obj docutils literal notranslate"><span class="pre">register_op_hook</span></code></a>(callback[, monitor_all])</p></td> |
| <td><p>Install op hook for block recursively.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.reset_ctx" title="mxnet.gluon.SymbolBlock.reset_ctx"><code class="xref py py-obj docutils literal notranslate"><span class="pre">reset_ctx</span></code></a>(ctx)</p></td> |
| <td><p>Re-assign all Parameters to other contexts.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.save_parameters" title="mxnet.gluon.SymbolBlock.save_parameters"><code class="xref py py-obj docutils literal notranslate"><span class="pre">save_parameters</span></code></a>(filename[, deduplicate])</p></td> |
| <td><p>Save parameters to file.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.setattr" title="mxnet.gluon.SymbolBlock.setattr"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setattr</span></code></a>(name, value)</p></td> |
| <td><p>Set an attribute to a new value for all Parameters.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.share_parameters" title="mxnet.gluon.SymbolBlock.share_parameters"><code class="xref py py-obj docutils literal notranslate"><span class="pre">share_parameters</span></code></a>(shared)</p></td> |
| <td><p>Share parameters recursively inside the model.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.summary" title="mxnet.gluon.SymbolBlock.summary"><code class="xref py py-obj docutils literal notranslate"><span class="pre">summary</span></code></a>(*inputs)</p></td> |
| <td><p>Print the summary of the model’s output and parameters.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.zero_grad" title="mxnet.gluon.SymbolBlock.zero_grad"><code class="xref py py-obj docutils literal notranslate"><span class="pre">zero_grad</span></code></a>()</p></td> |
| <td><p>Sets all Parameters’ gradient buffer to 0.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <p><strong>Attributes</strong></p> |
| <table class="longtable docutils align-default"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock.params" title="mxnet.gluon.SymbolBlock.params"><code class="xref py py-obj docutils literal notranslate"><span class="pre">params</span></code></a></p></td> |
| <td><p>Returns this <code class="xref py py-class docutils literal notranslate"><span class="pre">Block</span></code>’s parameter dictionary (does not include its children’s parameters).</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># To extract the feature from fc1 and fc2 layers of AlexNet:</span> |
| <span class="gp">>>> </span><span class="n">alexnet</span> <span class="o">=</span> <span class="n">gluon</span><span class="o">.</span><span class="n">model_zoo</span><span class="o">.</span><span class="n">vision</span><span class="o">.</span><span class="n">alexnet</span><span class="p">(</span><span class="n">pretrained</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">ctx</span><span class="o">=</span><span class="n">mx</span><span class="o">.</span><span class="n">cpu</span><span class="p">())</span> |
| <span class="gp">>>> </span><span class="n">inputs</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">var</span><span class="p">(</span><span class="s1">'data'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">out</span> <span class="o">=</span> <span class="n">alexnet</span><span class="p">(</span><span class="n">inputs</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">internals</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">get_internals</span><span class="p">()</span> |
| <span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">internals</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">())</span> |
| <span class="go">['data', ..., 'features_9_act_fwd_output', ..., 'features_11_act_fwd_output', ...]</span> |
| <span class="gp">>>> </span><span class="n">outputs</span> <span class="o">=</span> <span class="p">[</span><span class="n">internals</span><span class="p">[</span><span class="s1">'features_9_act_fwd_output'</span><span class="p">],</span> |
| <span class="go"> internals['features_11_act_fwd_output']]</span> |
| <span class="gp">>>> </span><span class="c1"># Create SymbolBlock that shares parameters with alexnet</span> |
| <span class="gp">>>> </span><span class="n">feat_model</span> <span class="o">=</span> <span class="n">gluon</span><span class="o">.</span><span class="n">SymbolBlock</span><span class="p">(</span><span class="n">outputs</span><span class="p">,</span> <span class="n">inputs</span><span class="p">,</span> <span class="n">params</span><span class="o">=</span><span class="n">alexnet</span><span class="o">.</span><span class="n">collect_params</span><span class="p">())</span> |
| <span class="gp">>>> </span><span class="n">x</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">normal</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">16</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">224</span><span class="p">,</span> <span class="mi">224</span><span class="p">))</span> |
| <span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">feat_model</span><span class="p">(</span><span class="n">x</span><span class="p">))</span> |
| </pre></div> |
| </div> |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.apply"> |
| <code class="sig-name descname">apply</code><span class="sig-paren">(</span><em class="sig-param">fn</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.apply" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Applies <code class="docutils literal notranslate"><span class="pre">fn</span></code> recursively to every child block as well as self.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>fn</strong> (<em>callable</em>) – Function to be applied to each submodule, of form <cite>fn(block)</cite>.</p> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p></p> |
| </dd> |
| <dt class="field-odd">Return type</dt> |
| <dd class="field-odd"><p>this block</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.cast"> |
| <code class="sig-name descname">cast</code><span class="sig-paren">(</span><em class="sig-param">dtype</em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/mxnet/gluon/block.html#SymbolBlock.cast"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.gluon.SymbolBlock.cast" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Cast this Block to use another data type.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>dtype</strong> (<em>str</em><em> or </em><em>numpy.dtype</em>) – The new data type.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.collect_params"> |
| <code class="sig-name descname">collect_params</code><span class="sig-paren">(</span><em class="sig-param">select=None</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.collect_params" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns a <code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code> containing this <a class="reference internal" href="block.html#mxnet.gluon.Block" title="mxnet.gluon.Block"><code class="xref py py-class docutils literal notranslate"><span class="pre">Block</span></code></a> and all of its |
| children’s Parameters(default), also can returns the select <code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code> |
| which match some given regular expressions.</p> |
| <p>For example, collect the specified parameters in [‘conv1.weight’, ‘conv1.bias’, ‘fc.weight’, |
| ‘fc.bias’]:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">model</span><span class="o">.</span><span class="n">collect_params</span><span class="p">(</span><span class="s1">'conv1.weight|conv1.bias|fc.weight|fc.bias'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>or collect all parameters whose names end with ‘weight’ or ‘bias’, this can be done |
| using regular expressions:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">model</span><span class="o">.</span><span class="n">collect_params</span><span class="p">(</span><span class="s1">'.*weight|.*bias'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>select</strong> (<em>str</em>) – regular expressions</p> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p></p> |
| </dd> |
| <dt class="field-odd">Return type</dt> |
| <dd class="field-odd"><p>The selected <code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code></p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.export"> |
| <code class="sig-name descname">export</code><span class="sig-paren">(</span><em class="sig-param">path</em>, <em class="sig-param">epoch=0</em>, <em class="sig-param">remove_amp_cast=True</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.export" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Export HybridBlock to json format that can be loaded by |
| <cite>gluon.SymbolBlock.imports</cite> or the C++ interface.</p> |
| <div class="admonition note"> |
| <p class="admonition-title">Note</p> |
| <p>When there are only one input, it will have name <cite>data</cite>. When there |
| Are more than one inputs, they will be named as <cite>data0</cite>, <cite>data1</cite>, etc.</p> |
| </div> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>path</strong> (<em>str</em><em> or </em><em>None</em>) – Path to save model. Two files <cite>path-symbol.json</cite> and <cite>path-xxxx.params</cite> |
| will be created, where xxxx is the 4 digits epoch number. |
| If None, do not export to file but return Python Symbol object and |
| corresponding dictionary of parameters.</p></li> |
| <li><p><strong>epoch</strong> (<em>int</em>) – Epoch number of saved model.</p></li> |
| <li><p><strong>remove_amp_cast</strong> (<em>bool</em><em>, </em><em>optional</em>) – Whether to remove the amp_cast and amp_multicast operators, before saving the model.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><ul class="simple"> |
| <li><p><strong>symbol_filename</strong> (<em>str</em>) – Filename to which model symbols were saved, including <cite>path</cite> prefix.</p></li> |
| <li><p><strong>params_filename</strong> (<em>str</em>) – Filename to which model parameters were saved, including <cite>path</cite> prefix.</p></li> |
| </ul> |
| </p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.forward"> |
| <code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param">x</em>, <em class="sig-param">*args</em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/mxnet/gluon/block.html#SymbolBlock.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.gluon.SymbolBlock.forward" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Defines the forward computation. Arguments can be either |
| <code class="xref py py-class docutils literal notranslate"><span class="pre">NDArray</span></code> or <code class="xref py py-class docutils literal notranslate"><span class="pre">Symbol</span></code>.</p> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.hybrid_forward"> |
| <code class="sig-name descname">hybrid_forward</code><span class="sig-paren">(</span><em class="sig-param">F</em>, <em class="sig-param">x</em>, <em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/mxnet/gluon/block.html#SymbolBlock.hybrid_forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.gluon.SymbolBlock.hybrid_forward" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Overrides to construct symbolic graph for this <cite>Block</cite>.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>x</strong> (<a class="reference internal" href="../legacy/symbol/symbol.html#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a><em> or </em><a class="reference internal" href="../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The first input tensor.</p></li> |
| <li><p><strong>*args</strong> (<em>list of Symbol</em><em> or </em><em>list of NDArray</em>) – Additional input tensors.</p></li> |
| </ul> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.hybridize"> |
| <code class="sig-name descname">hybridize</code><span class="sig-paren">(</span><em class="sig-param">active=True</em>, <em class="sig-param">backend=None</em>, <em class="sig-param">backend_opts=None</em>, <em class="sig-param">clear=True</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.hybridize" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Activates or deactivates <a class="reference internal" href="hybrid_block.html#mxnet.gluon.HybridBlock" title="mxnet.gluon.HybridBlock"><code class="xref py py-class docutils literal notranslate"><span class="pre">HybridBlock</span></code></a> s recursively. Has no effect on |
| non-hybrid children.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>active</strong> (<em>bool</em><em>, </em><em>default True</em>) – Whether to turn hybrid on or off.</p></li> |
| <li><p><strong>backend</strong> (<em>str</em>) – The name of backend, as registered in <cite>SubgraphBackendRegistry</cite>, default None</p></li> |
| <li><p><strong>backend_opts</strong> (<em>dict of user-specified options to pass to the backend for partitioning</em><em>, </em><em>optional</em>) – Passed on to <cite>PrePartition</cite> and <cite>PostPartition</cite> functions of <cite>SubgraphProperty</cite></p></li> |
| <li><p><strong>clear</strong> (<em>clears any previous optimizations</em>) – </p></li> |
| <li><p><strong>static_alloc</strong> (<em>bool</em><em>, </em><em>default False</em>) – Statically allocate memory to improve speed. Memory usage may increase.</p></li> |
| <li><p><strong>static_shape</strong> (<em>bool</em><em>, </em><em>default False</em>) – Optimize for invariant input shapes between iterations. Must also |
| set static_alloc to True. Change of input shapes is still allowed |
| but slower.</p></li> |
| </ul> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.imports"> |
| <em class="property">static </em><code class="sig-name descname">imports</code><span class="sig-paren">(</span><em class="sig-param">symbol_file</em>, <em class="sig-param">input_names</em>, <em class="sig-param">param_file=None</em>, <em class="sig-param">ctx=None</em>, <em class="sig-param">allow_missing=False</em>, <em class="sig-param">ignore_extra=False</em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/mxnet/gluon/block.html#SymbolBlock.imports"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.gluon.SymbolBlock.imports" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Import model previously saved by <cite>gluon.HybridBlock.export</cite> |
| as a <cite>gluon.SymbolBlock</cite> for use in Gluon.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>symbol_file</strong> (<em>str</em>) – Path to symbol file.</p></li> |
| <li><p><strong>input_names</strong> (<em>list of str</em>) – List of input variable names</p></li> |
| <li><p><strong>param_file</strong> (<em>str</em><em>, </em><em>optional</em>) – Path to parameter file.</p></li> |
| <li><p><strong>ctx</strong> (<a class="reference internal" href="../context/index.html#mxnet.context.Context" title="mxnet.context.Context"><em>Context</em></a><em>, </em><em>default None</em>) – The context to initialize <cite>gluon.SymbolBlock</cite> on.</p></li> |
| <li><p><strong>allow_missing</strong> (<em>bool</em><em>, </em><em>default False</em>) – Whether to silently skip loading parameters not represents in the file.</p></li> |
| <li><p><strong>ignore_extra</strong> (<em>bool</em><em>, </em><em>default False</em>) – Whether to silently ignore parameters from the file that are not |
| present in this Block.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><cite>gluon.SymbolBlock</cite> loaded from symbol and parameter files.</p> |
| </dd> |
| <dt class="field-odd">Return type</dt> |
| <dd class="field-odd"><p><a class="reference internal" href="#mxnet.gluon.SymbolBlock" title="mxnet.gluon.SymbolBlock">gluon.SymbolBlock</a></p> |
| </dd> |
| </dl> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">net1</span> <span class="o">=</span> <span class="n">gluon</span><span class="o">.</span><span class="n">model_zoo</span><span class="o">.</span><span class="n">vision</span><span class="o">.</span><span class="n">resnet18_v1</span><span class="p">(</span><span class="n">pretrained</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">net1</span><span class="o">.</span><span class="n">hybridize</span><span class="p">()</span> |
| <span class="gp">>>> </span><span class="n">x</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">normal</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">32</span><span class="p">,</span> <span class="mi">32</span><span class="p">))</span> |
| <span class="gp">>>> </span><span class="n">out1</span> <span class="o">=</span> <span class="n">net1</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">net1</span><span class="o">.</span><span class="n">export</span><span class="p">(</span><span class="s1">'net1'</span><span class="p">,</span> <span class="n">epoch</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> |
| <span class="go">>>></span> |
| <span class="gp">>>> </span><span class="n">net2</span> <span class="o">=</span> <span class="n">gluon</span><span class="o">.</span><span class="n">SymbolBlock</span><span class="o">.</span><span class="n">imports</span><span class="p">(</span> |
| <span class="gp">... </span> <span class="s1">'net1-symbol.json'</span><span class="p">,</span> <span class="p">[</span><span class="s1">'data'</span><span class="p">],</span> <span class="s1">'net1-0001.params'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">out2</span> <span class="o">=</span> <span class="n">net2</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.infer_shape"> |
| <code class="sig-name descname">infer_shape</code><span class="sig-paren">(</span><em class="sig-param">*args</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.infer_shape" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Infers shape of Parameters from inputs.</p> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.infer_type"> |
| <code class="sig-name descname">infer_type</code><span class="sig-paren">(</span><em class="sig-param">*args</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.infer_type" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Infers data type of Parameters from inputs.</p> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.initialize"> |
| <code class="sig-name descname">initialize</code><span class="sig-paren">(</span><em class="sig-param">init=<mxnet.initializer.Uniform object></em>, <em class="sig-param">ctx=None</em>, <em class="sig-param">verbose=False</em>, <em class="sig-param">force_reinit=False</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.initialize" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Initializes <a class="reference internal" href="parameter.html#mxnet.gluon.Parameter" title="mxnet.gluon.Parameter"><code class="xref py py-class docutils literal notranslate"><span class="pre">Parameter</span></code></a> s of this <a class="reference internal" href="block.html#mxnet.gluon.Block" title="mxnet.gluon.Block"><code class="xref py py-class docutils literal notranslate"><span class="pre">Block</span></code></a> and its children.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>init</strong> (<a class="reference internal" href="../initializer/index.html#mxnet.initializer.Initializer" title="mxnet.initializer.Initializer"><em>Initializer</em></a>) – Global default Initializer to be used when <code class="xref py py-meth docutils literal notranslate"><span class="pre">Parameter.init()</span></code> is <code class="docutils literal notranslate"><span class="pre">None</span></code>. |
| Otherwise, <code class="xref py py-meth docutils literal notranslate"><span class="pre">Parameter.init()</span></code> takes precedence.</p></li> |
| <li><p><strong>ctx</strong> (<a class="reference internal" href="../context/index.html#mxnet.context.Context" title="mxnet.context.Context"><em>Context</em></a><em> or </em><em>list of Context</em>) – Keeps a copy of Parameters on one or many context(s).</p></li> |
| <li><p><strong>verbose</strong> (<em>bool</em><em>, </em><em>default False</em>) – Whether to verbosely print out details on initialization.</p></li> |
| <li><p><strong>force_reinit</strong> (<em>bool</em><em>, </em><em>default False</em>) – Whether to force re-initialization if parameter is already initialized.</p></li> |
| </ul> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.load_dict"> |
| <code class="sig-name descname">load_dict</code><span class="sig-paren">(</span><em class="sig-param">param_dict</em>, <em class="sig-param">ctx=None</em>, <em class="sig-param">allow_missing=False</em>, <em class="sig-param">ignore_extra=False</em>, <em class="sig-param">cast_dtype=False</em>, <em class="sig-param">dtype_source='current'</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.load_dict" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Load parameters from dict</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>param_dict</strong> (<em>dict</em>) – Dictionary containing model parameters</p></li> |
| <li><p><strong>ctx</strong> (<a class="reference internal" href="../context/index.html#mxnet.context.Context" title="mxnet.context.Context"><em>Context</em></a><em> or </em><em>list of Context</em>) – Context(s) initialize loaded parameters on.</p></li> |
| <li><p><strong>allow_missing</strong> (<em>bool</em><em>, </em><em>default False</em>) – Whether to silently skip loading parameters not represented in the file.</p></li> |
| <li><p><strong>ignore_extra</strong> (<em>bool</em><em>, </em><em>default False</em>) – Whether to silently ignore parameters from the file that are not |
| present in this dict.</p></li> |
| <li><p><strong>cast_dtype</strong> (<em>bool</em><em>, </em><em>default False</em>) – Cast the data type of the NDArray loaded from the checkpoint to the dtype |
| provided by the Parameter if any</p></li> |
| <li><p><strong>dtype_source</strong> (<em>str</em><em>, </em><em>default 'current'</em>) – must be in {‘current’, ‘saved’} |
| Only valid if cast_dtype=True, specify the source of the dtype for casting |
| the parameters</p></li> |
| </ul> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.load_parameters"> |
| <code class="sig-name descname">load_parameters</code><span class="sig-paren">(</span><em class="sig-param">filename</em>, <em class="sig-param">ctx=None</em>, <em class="sig-param">allow_missing=False</em>, <em class="sig-param">ignore_extra=False</em>, <em class="sig-param">cast_dtype=False</em>, <em class="sig-param">dtype_source='current'</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.load_parameters" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Load parameters from file previously saved by <cite>save_parameters</cite>.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>filename</strong> (<em>str</em>) – Path to parameter file.</p></li> |
| <li><p><strong>ctx</strong> (<a class="reference internal" href="../context/index.html#mxnet.context.Context" title="mxnet.context.Context"><em>Context</em></a><em> or </em><em>list of Context</em><em>, </em><em>default cpu</em><em>(</em><em>)</em>) – Context(s) to initialize loaded parameters on.</p></li> |
| <li><p><strong>allow_missing</strong> (<em>bool</em><em>, </em><em>default False</em>) – Whether to silently skip loading parameters not represents in the file.</p></li> |
| <li><p><strong>ignore_extra</strong> (<em>bool</em><em>, </em><em>default False</em>) – Whether to silently ignore parameters from the file that are not |
| present in this Block.</p></li> |
| <li><p><strong>cast_dtype</strong> (<em>bool</em><em>, </em><em>default False</em>) – Cast the data type of the NDArray loaded from the checkpoint to the dtype |
| provided by the Parameter if any.</p></li> |
| <li><p><strong>dtype_source</strong> (<em>str</em><em>, </em><em>default 'current'</em>) – must be in {‘current’, ‘saved’} |
| Only valid if cast_dtype=True, specify the source of the dtype for casting |
| the parameters</p></li> |
| </ul> |
| </dd> |
| </dl> |
| <p class="rubric">References</p> |
| <p><a class="reference external" href="https://mxnet.apache.org/api/python/docs/tutorials/packages/gluon/blocks/save_load_params.html">Saving and Loading Gluon Models</a></p> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.optimize_for"> |
| <code class="sig-name descname">optimize_for</code><span class="sig-paren">(</span><em class="sig-param">x</em>, <em class="sig-param">*args</em>, <em class="sig-param">backend=None</em>, <em class="sig-param">backend_opts=None</em>, <em class="sig-param">clear=True</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.optimize_for" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Partitions the current HybridBlock and optimizes it for a given backend |
| without executing a forward pass. Modifies the HybridBlock in-place.</p> |
| <p>Immediately partitions a HybridBlock using the specified backend. Combines |
| the work done in the hybridize API with part of the work done in the forward |
| pass without calling the CachedOp. Can be used in place of hybridize, |
| afterwards <cite>export</cite> can be called or inference can be run. See README.md in |
| example/extensions/lib_subgraph/README.md for more details.</p> |
| <p class="rubric">Examples</p> |
| <p># partition and then export to file |
| block.optimize_for(x, backend=’myPart’) |
| block.export(‘partitioned’)</p> |
| <p># partition and then run inference |
| block.optimize_for(x, backend=’myPart’) |
| block(x)</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>x</strong> (<a class="reference internal" href="../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – first input to model</p></li> |
| <li><p><strong>*args</strong> (<a class="reference internal" href="../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – other inputs to model</p></li> |
| <li><p><strong>backend</strong> (<em>str</em>) – The name of backend, as registered in <cite>SubgraphBackendRegistry</cite>, default None</p></li> |
| <li><p><strong>backend_opts</strong> (<em>dict of user-specified options to pass to the backend for partitioning</em><em>, </em><em>optional</em>) – Passed on to <cite>PrePartition</cite> and <cite>PostPartition</cite> functions of <cite>SubgraphProperty</cite></p></li> |
| <li><p><strong>clear</strong> (<em>clears any previous optimizations</em>) – </p></li> |
| <li><p><strong>static_alloc</strong> (<em>bool</em><em>, </em><em>default False</em>) – Statically allocate memory to improve speed. Memory usage may increase.</p></li> |
| <li><p><strong>static_shape</strong> (<em>bool</em><em>, </em><em>default False</em>) – Optimize for invariant input shapes between iterations. Must also |
| set static_alloc to True. Change of input shapes is still allowed |
| but slower.</p></li> |
| </ul> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.params"> |
| <em class="property">property </em><code class="sig-name descname">params</code><a class="headerlink" href="#mxnet.gluon.SymbolBlock.params" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns this <a class="reference internal" href="block.html#mxnet.gluon.Block" title="mxnet.gluon.Block"><code class="xref py py-class docutils literal notranslate"><span class="pre">Block</span></code></a>’s parameter dictionary (does not include its |
| children’s parameters).</p> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.register_child"> |
| <code class="sig-name descname">register_child</code><span class="sig-paren">(</span><em class="sig-param">block</em>, <em class="sig-param">name=None</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.register_child" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Registers block as a child of self. <a class="reference internal" href="block.html#mxnet.gluon.Block" title="mxnet.gluon.Block"><code class="xref py py-class docutils literal notranslate"><span class="pre">Block</span></code></a> s assigned to self as |
| attributes will be registered automatically.</p> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.register_forward_hook"> |
| <code class="sig-name descname">register_forward_hook</code><span class="sig-paren">(</span><em class="sig-param">hook</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.register_forward_hook" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Registers a forward hook on the block.</p> |
| <p>The hook function is called immediately after <a class="reference internal" href="#mxnet.gluon.SymbolBlock.forward" title="mxnet.gluon.SymbolBlock.forward"><code class="xref py py-func docutils literal notranslate"><span class="pre">forward()</span></code></a>. |
| It should not modify the input or output.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>hook</strong> (<em>callable</em>) – The forward hook function of form <cite>hook(block, input, output) -> None</cite>.</p> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p></p> |
| </dd> |
| <dt class="field-odd">Return type</dt> |
| <dd class="field-odd"><p><code class="xref py py-class docutils literal notranslate"><span class="pre">mxnet.gluon.utils.HookHandle</span></code></p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.register_forward_pre_hook"> |
| <code class="sig-name descname">register_forward_pre_hook</code><span class="sig-paren">(</span><em class="sig-param">hook</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.register_forward_pre_hook" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Registers a forward pre-hook on the block.</p> |
| <p>The hook function is called immediately before <a class="reference internal" href="#mxnet.gluon.SymbolBlock.forward" title="mxnet.gluon.SymbolBlock.forward"><code class="xref py py-func docutils literal notranslate"><span class="pre">forward()</span></code></a>. |
| It should not modify the input or output.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>hook</strong> (<em>callable</em>) – The forward hook function of form <cite>hook(block, input) -> None</cite>.</p> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p></p> |
| </dd> |
| <dt class="field-odd">Return type</dt> |
| <dd class="field-odd"><p><code class="xref py py-class docutils literal notranslate"><span class="pre">mxnet.gluon.utils.HookHandle</span></code></p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.register_op_hook"> |
| <code class="sig-name descname">register_op_hook</code><span class="sig-paren">(</span><em class="sig-param">callback</em>, <em class="sig-param">monitor_all=False</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.register_op_hook" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Install op hook for block recursively.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>callback</strong> (<em>function</em>) – Function called to inspect the values of the intermediate outputs |
| of blocks after hybridization. It takes 3 parameters: |
| name of the tensor being inspected (str) |
| name of the operator producing or consuming that tensor (str) |
| tensor being inspected (NDArray).</p></li> |
| <li><p><strong>monitor_all</strong> (<em>bool</em><em>, </em><em>default False</em>) – If True, monitor both input and output, otherwise monitor output only.</p></li> |
| </ul> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.reset_ctx"> |
| <code class="sig-name descname">reset_ctx</code><span class="sig-paren">(</span><em class="sig-param">ctx</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.reset_ctx" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Re-assign all Parameters to other contexts. If the Block is hybridized, it will reset the _cached_op_args.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>ctx</strong> (Context or list of Context, default <code class="xref py py-meth docutils literal notranslate"><span class="pre">context.current_context()</span></code>.) – Assign Parameter to given context. If ctx is a list of Context, a |
| copy will be made for each context.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.save_parameters"> |
| <code class="sig-name descname">save_parameters</code><span class="sig-paren">(</span><em class="sig-param">filename</em>, <em class="sig-param">deduplicate=False</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.save_parameters" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Save parameters to file.</p> |
| <p>Saved parameters can only be loaded with <cite>load_parameters</cite>. Note that this |
| method only saves parameters, not model structure. If you want to save |
| model structures, please use <a class="reference internal" href="hybrid_block.html#mxnet.gluon.HybridBlock.export" title="mxnet.gluon.HybridBlock.export"><code class="xref py py-meth docutils literal notranslate"><span class="pre">HybridBlock.export()</span></code></a>.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>filename</strong> (<em>str</em>) – Path to file.</p></li> |
| <li><p><strong>deduplicate</strong> (<em>bool</em><em>, </em><em>default False</em>) – If True, save shared parameters only once. Otherwise, if a Block |
| contains multiple sub-blocks that share parameters, each of the |
| shared parameters will be separately saved for every sub-block.</p></li> |
| </ul> |
| </dd> |
| </dl> |
| <p class="rubric">References</p> |
| <p><a class="reference external" href="https://mxnet.apache.org/api/python/docs/tutorials/packages/gluon/blocks/save_load_params.html">Saving and Loading Gluon Models</a></p> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.setattr"> |
| <code class="sig-name descname">setattr</code><span class="sig-paren">(</span><em class="sig-param">name</em>, <em class="sig-param">value</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.setattr" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Set an attribute to a new value for all Parameters.</p> |
| <p>For example, set grad_req to null if you don’t need gradient w.r.t a |
| model’s Parameters:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">model</span><span class="o">.</span><span class="n">setattr</span><span class="p">(</span><span class="s1">'grad_req'</span><span class="p">,</span> <span class="s1">'null'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>or change the learning rate multiplier:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">model</span><span class="o">.</span><span class="n">setattr</span><span class="p">(</span><span class="s1">'lr_mult'</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>name</strong> (<em>str</em>) – Name of the attribute.</p></li> |
| <li><p><strong>value</strong> (<em>valid type for attribute name</em>) – The new value for the attribute.</p></li> |
| </ul> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.share_parameters"> |
| <code class="sig-name descname">share_parameters</code><span class="sig-paren">(</span><em class="sig-param">shared</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.share_parameters" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Share parameters recursively inside the model.</p> |
| <p>For example, if you want <code class="docutils literal notranslate"><span class="pre">dense1</span></code> to share <code class="docutils literal notranslate"><span class="pre">dense0</span></code>’s weights, you can do:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">dense0</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Dense</span><span class="p">(</span><span class="mi">20</span><span class="p">)</span> |
| <span class="n">dense1</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Dense</span><span class="p">(</span><span class="mi">20</span><span class="p">)</span> |
| <span class="n">dense1</span><span class="o">.</span><span class="n">share_parameters</span><span class="p">(</span><span class="n">dense0</span><span class="o">.</span><span class="n">collect_params</span><span class="p">())</span> |
| </pre></div> |
| </div> |
| <dl class="simple"> |
| <dt>which equals to</dt><dd><p>dense1.weight = dense0.weight |
| dense1.bias = dense0.bias</p> |
| </dd> |
| </dl> |
| <p>Note that unlike the <cite>load_parameters</cite> or <cite>load_dict</cite> functions, |
| <cite>share_parameters</cite> results in the <cite>Parameter</cite> object being shared (or |
| tied) between the models, whereas <cite>load_parameters</cite> or <cite>load_dict</cite> only |
| set the value of the data dictionary of a model. If you call |
| <cite>load_parameters</cite> or <cite>load_dict</cite> after <cite>share_parameters</cite>, the loaded |
| value will be reflected in all networks that use the shared (or tied) |
| <cite>Parameter</cite> object.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>shared</strong> (<em>Dict</em>) – Dict of the shared parameters.</p> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p></p> |
| </dd> |
| <dt class="field-odd">Return type</dt> |
| <dd class="field-odd"><p>this block</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.summary"> |
| <code class="sig-name descname">summary</code><span class="sig-paren">(</span><em class="sig-param">*inputs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.summary" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Print the summary of the model’s output and parameters.</p> |
| <p>The network must have been initialized, and must not have been hybridized.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>inputs</strong> (<em>object</em>) – Any input that the model supports. For any tensor in the input, only |
| <a class="reference internal" href="../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" title="mxnet.ndarray.NDArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">mxnet.ndarray.NDArray</span></code></a> is supported.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="mxnet.gluon.SymbolBlock.zero_grad"> |
| <code class="sig-name descname">zero_grad</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.gluon.SymbolBlock.zero_grad" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Sets all Parameters’ gradient buffer to 0.</p> |
| </dd></dl> |
| |
| </dd></dl> |
| |
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