| <!DOCTYPE html> |
| |
| <html xmlns="http://www.w3.org/1999/xhtml"> |
| <head> |
| <meta charset="utf-8" /> |
| <meta charset="utf-8"> |
| <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> |
| <meta http-equiv="x-ua-compatible" content="ie=edge"> |
| <style> |
| .dropdown { |
| position: relative; |
| display: inline-block; |
| } |
| |
| .dropdown-content { |
| display: none; |
| position: absolute; |
| background-color: #f9f9f9; |
| min-width: 160px; |
| box-shadow: 0px 8px 16px 0px rgba(0,0,0,0.2); |
| padding: 12px 16px; |
| z-index: 1; |
| text-align: left; |
| } |
| |
| .dropdown:hover .dropdown-content { |
| display: block; |
| } |
| |
| .dropdown-option:hover { |
| color: #FF4500; |
| } |
| |
| .dropdown-option-active { |
| color: #FF4500; |
| font-weight: lighter; |
| } |
| |
| .dropdown-option { |
| color: #000000; |
| font-weight: lighter; |
| } |
| |
| .dropdown-header { |
| color: #FFFFFF; |
| display: inline-flex; |
| } |
| |
| .dropdown-caret { |
| width: 18px; |
| } |
| |
| .dropdown-caret-path { |
| fill: #FFFFFF; |
| } |
| </style> |
| |
| <title>mxnet.operator — Apache MXNet documentation</title> |
| |
| <link rel="stylesheet" href="../../_static/basic.css" type="text/css" /> |
| <link rel="stylesheet" href="../../_static/pygments.css" type="text/css" /> |
| <link rel="stylesheet" type="text/css" href="../../_static/mxnet.css" /> |
| <link rel="stylesheet" href="../../_static/material-design-lite-1.3.0/material.blue-deep_orange.min.css" type="text/css" /> |
| <link rel="stylesheet" href="../../_static/sphinx_materialdesign_theme.css" type="text/css" /> |
| <link rel="stylesheet" href="../../_static/fontawesome/all.css" type="text/css" /> |
| <link rel="stylesheet" href="../../_static/fonts.css" type="text/css" /> |
| <link rel="stylesheet" href="../../_static/feedback.css" type="text/css" /> |
| <script id="documentation_options" data-url_root="../../" src="../../_static/documentation_options.js"></script> |
| <script src="../../_static/jquery.js"></script> |
| <script src="../../_static/underscore.js"></script> |
| <script src="../../_static/doctools.js"></script> |
| <script src="../../_static/language_data.js"></script> |
| <script src="../../_static/matomo_analytics.js"></script> |
| <script src="../../_static/autodoc.js"></script> |
| <script crossorigin="anonymous" integrity="sha256-Ae2Vz/4ePdIu6ZyI/5ZGsYnb+m0JlOmKPjt6XZ9JJkA=" src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.4/require.min.js"></script> |
| <script async="async" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/latest.js?config=TeX-AMS-MML_HTMLorMML"></script> |
| <script type="text/x-mathjax-config">MathJax.Hub.Config({"tex2jax": {"inlineMath": [["$", "$"], ["\\(", "\\)"]], "processEscapes": true, "ignoreClass": "document", "processClass": "math|output_area"}})</script> |
| <link rel="shortcut icon" href="../../_static/mxnet-icon.png"/> |
| <link rel="index" title="Index" href="../../genindex.html" /> |
| <link rel="search" title="Search" href="../../search.html" /> |
| </head> |
| <body><header class="site-header" role="banner"> |
| <div class="wrapper"> |
| <a class="site-title" rel="author" href="/versions/1.9.1/"><img |
| src="../../_static/mxnet_logo.png" class="site-header-logo"></a> |
| <nav class="site-nav"> |
| <input type="checkbox" id="nav-trigger" class="nav-trigger"/> |
| <label for="nav-trigger"> |
| <span class="menu-icon"> |
| <svg viewBox="0 0 18 15" width="18px" height="15px"> |
| <path d="M18,1.484c0,0.82-0.665,1.484-1.484,1.484H1.484C0.665,2.969,0,2.304,0,1.484l0,0C0,0.665,0.665,0,1.484,0 h15.032C17.335,0,18,0.665,18,1.484L18,1.484z M18,7.516C18,8.335,17.335,9,16.516,9H1.484C0.665,9,0,8.335,0,7.516l0,0 c0-0.82,0.665-1.484,1.484-1.484h15.032C17.335,6.031,18,6.696,18,7.516L18,7.516z M18,13.516C18,14.335,17.335,15,16.516,15H1.484 C0.665,15,0,14.335,0,13.516l0,0c0-0.82,0.665-1.483,1.484-1.483h15.032C17.335,12.031,18,12.695,18,13.516L18,13.516z"/> |
| </svg> |
| </span> |
| </label> |
| |
| <div class="trigger"> |
| <a class="page-link" href="/versions/1.9.1/get_started">Get Started</a> |
| <a class="page-link" href="/versions/1.9.1/features">Features</a> |
| <a class="page-link" href="/versions/1.9.1/ecosystem">Ecosystem</a> |
| <a class="page-link page-current" href="/versions/1.9.1/api">Docs & Tutorials</a> |
| <a class="page-link" href="/versions/1.9.1/trusted_by">Trusted By</a> |
| <a class="page-link" href="https://github.com/apache/incubator-mxnet">GitHub</a> |
| <div class="dropdown" style="min-width:100px"> |
| <span class="dropdown-header">Apache |
| <svg class="dropdown-caret" viewBox="0 0 32 32" class="icon icon-caret-bottom" aria-hidden="true"><path class="dropdown-caret-path" d="M24 11.305l-7.997 11.39L8 11.305z"></path></svg> |
| </span> |
| <div class="dropdown-content" style="min-width:250px"> |
| <a href="https://www.apache.org/foundation/">Apache Software Foundation</a> |
| <a href="https://incubator.apache.org/">Apache Incubator</a> |
| <a href="https://www.apache.org/licenses/">License</a> |
| <a href="/versions/1.9.1/api/faq/security.html">Security</a> |
| <a href="https://privacy.apache.org/policies/privacy-policy-public.html">Privacy</a> |
| <a href="https://www.apache.org/events/current-event">Events</a> |
| <a href="https://www.apache.org/foundation/sponsorship.html">Sponsorship</a> |
| <a href="https://www.apache.org/foundation/thanks.html">Thanks</a> |
| </div> |
| </div> |
| <div class="dropdown"> |
| <span class="dropdown-header">1.9.1 |
| <svg class="dropdown-caret" viewBox="0 0 32 32" class="icon icon-caret-bottom" aria-hidden="true"><path class="dropdown-caret-path" d="M24 11.305l-7.997 11.39L8 11.305z"></path></svg> |
| </span> |
| <div class="dropdown-content"> |
| <a class="dropdown-option" href="/">master</a><br> |
| <a class="dropdown-option-active" href="/versions/1.9.1/">1.9.1</a><br> |
| <a class="dropdown-option" href="/versions/1.8.0/">1.8.0</a><br> |
| <a class="dropdown-option" href="/versions/1.7.0/">1.7.0</a><br> |
| <a class="dropdown-option" href="/versions/1.6.0/">1.6.0</a><br> |
| <a class="dropdown-option" href="/versions/1.5.0/">1.5.0</a><br> |
| <a class="dropdown-option" href="/versions/1.4.1/">1.4.1</a><br> |
| <a class="dropdown-option" href="/versions/1.3.1/">1.3.1</a><br> |
| <a class="dropdown-option" href="/versions/1.2.1/">1.2.1</a><br> |
| <a class="dropdown-option" href="/versions/1.1.0/">1.1.0</a><br> |
| <a class="dropdown-option" href="/versions/1.0.0/">1.0.0</a><br> |
| <a class="dropdown-option" href="/versions/0.12.1/">0.12.1</a><br> |
| <a class="dropdown-option" href="/versions/0.11.0/">0.11.0</a> |
| </div> |
| </div> |
| </div> |
| </nav> |
| </div> |
| </header> |
| <div class="mdl-layout mdl-js-layout mdl-layout--fixed-header mdl-layout--fixed-drawer"><header class="mdl-layout__header mdl-layout__header--waterfall "> |
| <div class="mdl-layout__header-row"> |
| |
| <nav class="mdl-navigation breadcrumb"> |
| <a class="mdl-navigation__link" href="../index.html">Module code</a><i class="material-icons">navigate_next</i> |
| <a class="mdl-navigation__link is-active">mxnet.operator</a> |
| </nav> |
| <div class="mdl-layout-spacer"></div> |
| <nav class="mdl-navigation"> |
| |
| <form class="form-inline pull-sm-right" action="../../search.html" method="get"> |
| <div class="mdl-textfield mdl-js-textfield mdl-textfield--expandable mdl-textfield--floating-label mdl-textfield--align-right"> |
| <label id="quick-search-icon" class="mdl-button mdl-js-button mdl-button--icon" for="waterfall-exp"> |
| <i class="material-icons">search</i> |
| </label> |
| <div class="mdl-textfield__expandable-holder"> |
| <input class="mdl-textfield__input" type="text" name="q" id="waterfall-exp" placeholder="Search" /> |
| <input type="hidden" name="check_keywords" value="yes" /> |
| <input type="hidden" name="area" value="default" /> |
| </div> |
| </div> |
| <div class="mdl-tooltip" data-mdl-for="quick-search-icon"> |
| Quick search |
| </div> |
| </form> |
| |
| </nav> |
| </div> |
| <div class="mdl-layout__header-row header-links"> |
| <div class="mdl-layout-spacer"></div> |
| <nav class="mdl-navigation"> |
| </nav> |
| </div> |
| </header><header class="mdl-layout__drawer"> |
| |
| <div class="globaltoc"> |
| <span class="mdl-layout-title toc">Table Of Contents</span> |
| |
| |
| |
| <nav class="mdl-navigation"> |
| <ul> |
| <li class="toctree-l1"><a class="reference internal" href="../../tutorials/index.html">Python Tutorials</a><ul> |
| <li class="toctree-l2"><a class="reference internal" href="../../tutorials/getting-started/index.html">Getting Started</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../tutorials/getting-started/crash-course/index.html">Crash Course</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/1-ndarray.html">Manipulate data with <code class="docutils literal notranslate"><span class="pre">ndarray</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/2-nn.html">Create a neural network</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/3-autograd.html">Automatic differentiation with <code class="docutils literal notranslate"><span class="pre">autograd</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/4-train.html">Train the neural network</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/5-predict.html">Predict with a pre-trained model</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/6-use_gpus.html">Use GPUs</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/image-augmentation.html">Image Augmentation</a></li> |
| <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> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/gluon/image/pretrained_models.html">Using pre-trained models in MXNet</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/ndarray/index.html">NDArray</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/packages/ndarray/01-ndarray-intro.html">An Intro: Manipulate Data the MXNet Way with NDArray</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/packages/ndarray/02-ndarray-operations.html">NDArray Operations</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/packages/ndarray/03-ndarray-contexts.html">NDArray Contexts</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/packages/ndarray/gotchas_numpy_in_mxnet.html">Gotchas using NumPy in Apache MXNet</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/packages/ndarray/sparse/index.html">Tutorials</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/ndarray/sparse/csr.html">CSRNDArray - NDArray in Compressed Sparse Row Storage Format</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/ndarray/sparse/row_sparse.html">RowSparseNDArray - NDArray for Sparse Gradient Updates</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/ndarray/sparse/train.html">Train a Linear Regression Model with Sparse Symbols</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/ndarray/sparse/train_gluon.html">Sparse NDArrays with Gluon</a></li> |
| </ul> |
| </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 internal" href="../../tutorials/packages/onnx/super_resolution.html">Importing an ONNX model into MXNet</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_quantization.html">Quantize with MKL-DNN backend</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/performance/backend/mkldnn/mkldnn_quantization.html#Improving-accuracy-with-Intel®-Neural-Compressor">Improving accuracy with Intel® Neural Compressor</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/performance/backend/mkldnn/mkldnn_readme.html">Install MXNet with MKL-DNN</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/performance/backend/tensorrt/index.html">TensorRT</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/performance/backend/tensorrt/tensorrt.html">Optimizing Deep Learning Computation Graphs with TensorRT</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/performance/backend/tvm.html">Use TVM</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/performance/backend/profiler.html">Profiling MXNet Models</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/performance/backend/amp.html">Using AMP: Automatic Mixed Precision</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../tutorials/deploy/index.html">Deployment</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../tutorials/deploy/export/index.html">Export</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/export/onnx.html">Exporting to ONNX format</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://gluon-cv.mxnet.io/build/examples_deployment/export_network.html">Export Gluon CV Models</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://mxnet.apache.org/api/python/docs/tutorials/packages/gluon/blocks/save_load_params.html">Save / Load Parameters</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../tutorials/deploy/inference/index.html">Inference</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/inference/cpp.html">Deploy into C++</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/inference/image_classification_jetson.html">Image Classication using pretrained ResNet-50 model on Jetson module</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/inference/scala.html">Deploy into a Java or Scala Environment</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/inference/wine_detector.html">Real-time Object Detection with MXNet On The Raspberry Pi</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../tutorials/deploy/run-on-aws/index.html">Run on AWS</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/run-on-aws/use_ec2.html">Run on an EC2 Instance</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/run-on-aws/use_sagemaker.html">Run on Amazon SageMaker</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/run-on-aws/cloud.html">MXNet on the Cloud</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../tutorials/extend/index.html">Extend</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../tutorials/extend/custom_layer.html">Custom Layers</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../tutorials/extend/customop.html">Custom Numpy Operators</a></li> |
| <li class="toctree-l3"><a class="reference external" href="https://mxnet.apache.org/api/faq/new_op">New Operator Creation</a></li> |
| <li class="toctree-l3"><a class="reference external" href="https://mxnet.apache.org/api/faq/add_op_in_backend">New Operator in MXNet Backend</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l1"><a class="reference internal" href="../../api/index.html">Python API</a><ul> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/ndarray/index.html">mxnet.ndarray</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/ndarray.html">ndarray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/contrib/index.html">ndarray.contrib</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/image/index.html">ndarray.image</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/linalg/index.html">ndarray.linalg</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/op/index.html">ndarray.op</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/random/index.html">ndarray.random</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/register/index.html">ndarray.register</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/sparse/index.html">ndarray.sparse</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/utils/index.html">ndarray.utils</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/gluon/index.html">mxnet.gluon</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/block.html">gluon.Block</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/hybrid_block.html">gluon.HybridBlock</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/symbol_block.html">gluon.SymbolBlock</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/constant.html">gluon.Constant</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/parameter.html">gluon.Parameter</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/parameter_dict.html">gluon.ParameterDict</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/trainer.html">gluon.Trainer</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/contrib/index.html">gluon.contrib</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/data/index.html">gluon.data</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../api/gluon/data/vision/index.html">data.vision</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../api/gluon/data/vision/datasets/index.html">vision.datasets</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../api/gluon/data/vision/transforms/index.html">vision.transforms</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/loss/index.html">gluon.loss</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/model_zoo/index.html">gluon.model_zoo.vision</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/nn/index.html">gluon.nn</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/rnn/index.html">gluon.rnn</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/utils/index.html">gluon.utils</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/autograd/index.html">mxnet.autograd</a></li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/initializer/index.html">mxnet.initializer</a></li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/optimizer/index.html">mxnet.optimizer</a></li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/lr_scheduler/index.html">mxnet.lr_scheduler</a></li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/metric/index.html">mxnet.metric</a></li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/kvstore/index.html">mxnet.kvstore</a></li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/symbol/index.html">mxnet.symbol</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/symbol.html">symbol</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/contrib/index.html">symbol.contrib</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/image/index.html">symbol.image</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/linalg/index.html">symbol.linalg</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/op/index.html">symbol.op</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/random/index.html">symbol.random</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/register/index.html">symbol.register</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/sparse/index.html">symbol.sparse</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/module/index.html">mxnet.module</a></li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/contrib/index.html">mxnet.contrib</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/autograd/index.html">contrib.autograd</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/io/index.html">contrib.io</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/ndarray/index.html">contrib.ndarray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/onnx/index.html">contrib.onnx</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/quantization/index.html">contrib.quantization</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/symbol/index.html">contrib.symbol</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/tensorboard/index.html">contrib.tensorboard</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/tensorrt/index.html">contrib.tensorrt</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/text/index.html">contrib.text</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/mxnet/index.html">mxnet</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/attribute/index.html">mxnet.attribute</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/base/index.html">mxnet.base</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/callback/index.html">mxnet.callback</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/context/index.html">mxnet.context</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/engine/index.html">mxnet.engine</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/executor/index.html">mxnet.executor</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/executor_manager/index.html">mxnet.executor_manager</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/image/index.html">mxnet.image</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/io/index.html">mxnet.io</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/kvstore_server/index.html">mxnet.kvstore_server</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/libinfo/index.html">mxnet.libinfo</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/log/index.html">mxnet.log</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/model/index.html">mxnet.model</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/monitor/index.html">mxnet.monitor</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/name/index.html">mxnet.name</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/notebook/index.html">mxnet.notebook</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/operator/index.html">mxnet.operator</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/profiler/index.html">mxnet.profiler</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/random/index.html">mxnet.random</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/recordio/index.html">mxnet.recordio</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/registry/index.html">mxnet.registry</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/rtc/index.html">mxnet.rtc</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/runtime/index.html">mxnet.runtime</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/test_utils/index.html">mxnet.test_utils</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/torch/index.html">mxnet.torch</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/util/index.html">mxnet.util</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/visualization/index.html">mxnet.visualization</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| </ul> |
| |
| </nav> |
| |
| </div> |
| |
| </header> |
| <main class="mdl-layout__content" tabIndex="0"> |
| |
| <script type="text/javascript" src="../../_static/sphinx_materialdesign_theme.js "></script> |
| <script type="text/javascript" src="../../_static/feedback.js"></script> |
| <header class="mdl-layout__drawer"> |
| |
| <div class="globaltoc"> |
| <span class="mdl-layout-title toc">Table Of Contents</span> |
| |
| |
| |
| <nav class="mdl-navigation"> |
| <ul> |
| <li class="toctree-l1"><a class="reference internal" href="../../tutorials/index.html">Python Tutorials</a><ul> |
| <li class="toctree-l2"><a class="reference internal" href="../../tutorials/getting-started/index.html">Getting Started</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../tutorials/getting-started/crash-course/index.html">Crash Course</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/1-ndarray.html">Manipulate data with <code class="docutils literal notranslate"><span class="pre">ndarray</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/2-nn.html">Create a neural network</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/3-autograd.html">Automatic differentiation with <code class="docutils literal notranslate"><span class="pre">autograd</span></code></a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/4-train.html">Train the neural network</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/5-predict.html">Predict with a pre-trained model</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/getting-started/crash-course/6-use_gpus.html">Use GPUs</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/image-augmentation.html">Image Augmentation</a></li> |
| <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> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/gluon/image/pretrained_models.html">Using pre-trained models in MXNet</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/ndarray/index.html">NDArray</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/packages/ndarray/01-ndarray-intro.html">An Intro: Manipulate Data the MXNet Way with NDArray</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/packages/ndarray/02-ndarray-operations.html">NDArray Operations</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/packages/ndarray/03-ndarray-contexts.html">NDArray Contexts</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/packages/ndarray/gotchas_numpy_in_mxnet.html">Gotchas using NumPy in Apache MXNet</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/packages/ndarray/sparse/index.html">Tutorials</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/ndarray/sparse/csr.html">CSRNDArray - NDArray in Compressed Sparse Row Storage Format</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/ndarray/sparse/row_sparse.html">RowSparseNDArray - NDArray for Sparse Gradient Updates</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/ndarray/sparse/train.html">Train a Linear Regression Model with Sparse Symbols</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/packages/ndarray/sparse/train_gluon.html">Sparse NDArrays with Gluon</a></li> |
| </ul> |
| </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 internal" href="../../tutorials/packages/onnx/super_resolution.html">Importing an ONNX model into MXNet</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_quantization.html">Quantize with MKL-DNN backend</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/performance/backend/mkldnn/mkldnn_quantization.html#Improving-accuracy-with-Intel®-Neural-Compressor">Improving accuracy with Intel® Neural Compressor</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/performance/backend/mkldnn/mkldnn_readme.html">Install MXNet with MKL-DNN</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/performance/backend/tensorrt/index.html">TensorRT</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../tutorials/performance/backend/tensorrt/tensorrt.html">Optimizing Deep Learning Computation Graphs with TensorRT</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/performance/backend/tvm.html">Use TVM</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/performance/backend/profiler.html">Profiling MXNet Models</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/performance/backend/amp.html">Using AMP: Automatic Mixed Precision</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../tutorials/deploy/index.html">Deployment</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../tutorials/deploy/export/index.html">Export</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/export/onnx.html">Exporting to ONNX format</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://gluon-cv.mxnet.io/build/examples_deployment/export_network.html">Export Gluon CV Models</a></li> |
| <li class="toctree-l4"><a class="reference external" href="https://mxnet.apache.org/api/python/docs/tutorials/packages/gluon/blocks/save_load_params.html">Save / Load Parameters</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../tutorials/deploy/inference/index.html">Inference</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/inference/cpp.html">Deploy into C++</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/inference/image_classification_jetson.html">Image Classication using pretrained ResNet-50 model on Jetson module</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/inference/scala.html">Deploy into a Java or Scala Environment</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/inference/wine_detector.html">Real-time Object Detection with MXNet On The Raspberry Pi</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../tutorials/deploy/run-on-aws/index.html">Run on AWS</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/run-on-aws/use_ec2.html">Run on an EC2 Instance</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/run-on-aws/use_sagemaker.html">Run on Amazon SageMaker</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="../../tutorials/deploy/run-on-aws/cloud.html">MXNet on the Cloud</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../tutorials/extend/index.html">Extend</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../tutorials/extend/custom_layer.html">Custom Layers</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../tutorials/extend/customop.html">Custom Numpy Operators</a></li> |
| <li class="toctree-l3"><a class="reference external" href="https://mxnet.apache.org/api/faq/new_op">New Operator Creation</a></li> |
| <li class="toctree-l3"><a class="reference external" href="https://mxnet.apache.org/api/faq/add_op_in_backend">New Operator in MXNet Backend</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l1"><a class="reference internal" href="../../api/index.html">Python API</a><ul> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/ndarray/index.html">mxnet.ndarray</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/ndarray.html">ndarray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/contrib/index.html">ndarray.contrib</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/image/index.html">ndarray.image</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/linalg/index.html">ndarray.linalg</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/op/index.html">ndarray.op</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/random/index.html">ndarray.random</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/register/index.html">ndarray.register</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/sparse/index.html">ndarray.sparse</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/ndarray/utils/index.html">ndarray.utils</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/gluon/index.html">mxnet.gluon</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/block.html">gluon.Block</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/hybrid_block.html">gluon.HybridBlock</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/symbol_block.html">gluon.SymbolBlock</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/constant.html">gluon.Constant</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/parameter.html">gluon.Parameter</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/parameter_dict.html">gluon.ParameterDict</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/trainer.html">gluon.Trainer</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/contrib/index.html">gluon.contrib</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/data/index.html">gluon.data</a><ul> |
| <li class="toctree-l4"><a class="reference internal" href="../../api/gluon/data/vision/index.html">data.vision</a><ul> |
| <li class="toctree-l5"><a class="reference internal" href="../../api/gluon/data/vision/datasets/index.html">vision.datasets</a></li> |
| <li class="toctree-l5"><a class="reference internal" href="../../api/gluon/data/vision/transforms/index.html">vision.transforms</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/loss/index.html">gluon.loss</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/model_zoo/index.html">gluon.model_zoo.vision</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/nn/index.html">gluon.nn</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/rnn/index.html">gluon.rnn</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/gluon/utils/index.html">gluon.utils</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/autograd/index.html">mxnet.autograd</a></li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/initializer/index.html">mxnet.initializer</a></li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/optimizer/index.html">mxnet.optimizer</a></li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/lr_scheduler/index.html">mxnet.lr_scheduler</a></li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/metric/index.html">mxnet.metric</a></li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/kvstore/index.html">mxnet.kvstore</a></li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/symbol/index.html">mxnet.symbol</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/symbol.html">symbol</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/contrib/index.html">symbol.contrib</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/image/index.html">symbol.image</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/linalg/index.html">symbol.linalg</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/op/index.html">symbol.op</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/random/index.html">symbol.random</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/register/index.html">symbol.register</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/symbol/sparse/index.html">symbol.sparse</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/module/index.html">mxnet.module</a></li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/contrib/index.html">mxnet.contrib</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/autograd/index.html">contrib.autograd</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/io/index.html">contrib.io</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/ndarray/index.html">contrib.ndarray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/onnx/index.html">contrib.onnx</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/quantization/index.html">contrib.quantization</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/symbol/index.html">contrib.symbol</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/tensorboard/index.html">contrib.tensorboard</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/tensorrt/index.html">contrib.tensorrt</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/contrib/text/index.html">contrib.text</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l2"><a class="reference internal" href="../../api/mxnet/index.html">mxnet</a><ul> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/attribute/index.html">mxnet.attribute</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/base/index.html">mxnet.base</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/callback/index.html">mxnet.callback</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/context/index.html">mxnet.context</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/engine/index.html">mxnet.engine</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/executor/index.html">mxnet.executor</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/executor_manager/index.html">mxnet.executor_manager</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/image/index.html">mxnet.image</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/io/index.html">mxnet.io</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/kvstore_server/index.html">mxnet.kvstore_server</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/libinfo/index.html">mxnet.libinfo</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/log/index.html">mxnet.log</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/model/index.html">mxnet.model</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/monitor/index.html">mxnet.monitor</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/name/index.html">mxnet.name</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/notebook/index.html">mxnet.notebook</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/operator/index.html">mxnet.operator</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/profiler/index.html">mxnet.profiler</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/random/index.html">mxnet.random</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/recordio/index.html">mxnet.recordio</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/registry/index.html">mxnet.registry</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/rtc/index.html">mxnet.rtc</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/runtime/index.html">mxnet.runtime</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/test_utils/index.html">mxnet.test_utils</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/torch/index.html">mxnet.torch</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/util/index.html">mxnet.util</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="../../api/mxnet/visualization/index.html">mxnet.visualization</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| </ul> |
| |
| </nav> |
| |
| </div> |
| |
| </header> |
| |
| <div class="document"> |
| <div class="page-content" role="main"> |
| |
| <h1>Source code for mxnet.operator</h1><div class="highlight"><pre> |
| <span></span><span class="c1"># Licensed to the Apache Software Foundation (ASF) under one</span> |
| <span class="c1"># or more contributor license agreements. See the NOTICE file</span> |
| <span class="c1"># distributed with this work for additional information</span> |
| <span class="c1"># regarding copyright ownership. The ASF licenses this file</span> |
| <span class="c1"># to you under the Apache License, Version 2.0 (the</span> |
| <span class="c1"># "License"); you may not use this file except in compliance</span> |
| <span class="c1"># with the License. You may obtain a copy of the License at</span> |
| <span class="c1">#</span> |
| <span class="c1"># http://www.apache.org/licenses/LICENSE-2.0</span> |
| <span class="c1">#</span> |
| <span class="c1"># Unless required by applicable law or agreed to in writing,</span> |
| <span class="c1"># software distributed under the License is distributed on an</span> |
| <span class="c1"># "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY</span> |
| <span class="c1"># KIND, either express or implied. See the License for the</span> |
| <span class="c1"># specific language governing permissions and limitations</span> |
| <span class="c1"># under the License.</span> |
| |
| <span class="c1"># coding: utf-8</span> |
| <span class="c1"># pylint: disable=invalid-name, protected-access, too-many-arguments, no-self-use, too-many-locals, broad-except, too-many-lines, unnecessary-pass</span> |
| <span class="sd">"""numpy interface for operators."""</span> |
| |
| <span class="kn">import</span> <span class="nn">traceback</span> |
| <span class="kn">import</span> <span class="nn">warnings</span> |
| <span class="kn">import</span> <span class="nn">collections</span> |
| |
| <span class="kn">from</span> <span class="nn">array</span> <span class="kn">import</span> <span class="n">array</span> |
| <span class="kn">from</span> <span class="nn">threading</span> <span class="kn">import</span> <span class="n">Lock</span> |
| <span class="kn">import</span> <span class="nn">ctypes</span> |
| <span class="kn">from</span> <span class="nn">ctypes</span> <span class="kn">import</span> <span class="n">CFUNCTYPE</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">,</span> <span class="n">Structure</span><span class="p">,</span> <span class="n">pointer</span> |
| <span class="kn">from</span> <span class="nn">ctypes</span> <span class="kn">import</span> <span class="n">c_void_p</span><span class="p">,</span> <span class="n">c_int</span><span class="p">,</span> <span class="n">c_char</span><span class="p">,</span> <span class="n">c_char_p</span><span class="p">,</span> <span class="n">cast</span><span class="p">,</span> <span class="n">c_bool</span> |
| |
| <span class="kn">from</span> <span class="nn">.base</span> <span class="kn">import</span> <span class="n">_LIB</span><span class="p">,</span> <span class="n">check_call</span><span class="p">,</span> <span class="n">MXCallbackList</span><span class="p">,</span> <span class="n">c_array</span><span class="p">,</span> <span class="n">c_array_buf</span><span class="p">,</span> <span class="n">mx_int</span><span class="p">,</span> <span class="n">OpHandle</span> |
| <span class="kn">from</span> <span class="nn">.base</span> <span class="kn">import</span> <span class="n">c_str</span><span class="p">,</span> <span class="n">mx_uint</span><span class="p">,</span> <span class="n">mx_float</span><span class="p">,</span> <span class="n">ctypes2numpy_shared</span><span class="p">,</span> <span class="n">NDArrayHandle</span><span class="p">,</span> <span class="n">py_str</span> |
| <span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">symbol</span><span class="p">,</span> <span class="n">context</span> |
| <span class="kn">from</span> <span class="nn">.ndarray</span> <span class="kn">import</span> <span class="n">NDArray</span><span class="p">,</span> <span class="n">_DTYPE_NP_TO_MX</span><span class="p">,</span> <span class="n">_DTYPE_MX_TO_NP</span> |
| <span class="kn">from</span> <span class="nn">.ndarray.ndarray</span> <span class="kn">import</span> <span class="n">_STORAGE_TYPE_STR_TO_ID</span><span class="p">,</span> <span class="n">_STORAGE_TYPE_ID_TO_STR</span> |
| <span class="kn">from</span> <span class="nn">.ndarray.ndarray</span> <span class="kn">import</span> <span class="n">_STORAGE_TYPE_UNDEFINED</span><span class="p">,</span> <span class="n">_STORAGE_TYPE_DEFAULT</span> |
| <span class="kn">from</span> <span class="nn">.ndarray.ndarray</span> <span class="kn">import</span> <span class="n">_STORAGE_TYPE_CSR</span><span class="p">,</span> <span class="n">_STORAGE_TYPE_ROW_SPARSE</span> |
| <span class="kn">from</span> <span class="nn">.ndarray</span> <span class="kn">import</span> <span class="n">_ndarray_cls</span> |
| <span class="kn">from</span> <span class="nn">.numpy.multiarray</span> <span class="kn">import</span> <span class="n">_np_ndarray_cls</span> |
| <span class="kn">from</span> <span class="nn">.util</span> <span class="kn">import</span> <span class="n">is_np_array</span> |
| |
| <span class="n">c_int_p</span> <span class="o">=</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int</span><span class="p">)</span> |
| |
| |
| <div class="viewcode-block" id="PythonOp"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.PythonOp">[docs]</a><span class="k">class</span> <span class="nc">PythonOp</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span> |
| <span class="sd">"""Base class for operators implemented in Python.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> need_top_grad : bool</span> |
| <span class="sd"> the default need_top_grad() function returns this value.</span> |
| <span class="sd"> """</span> |
| <span class="n">_ref_holder</span> <span class="o">=</span> <span class="p">[]</span> |
| |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">need_top_grad</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">info_</span> <span class="o">=</span> <span class="kc">None</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">need_top_grad_</span> <span class="o">=</span> <span class="n">need_top_grad</span> |
| <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s1">'PythonOp has been deprecated. Please use CustomOp'</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="fm">__call__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_symbol</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> |
| |
| <div class="viewcode-block" id="PythonOp.get_symbol"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.PythonOp.get_symbol">[docs]</a> <span class="k">def</span> <span class="nf">get_symbol</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="sd">"""Create a symbol from numpy operator.</span> |
| <span class="sd"> This should only be called once per instance if the operator contains</span> |
| <span class="sd"> internal states.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> args : list</span> |
| <span class="sd"> a list of input arguments (symbols).</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> sym : mxnet.symbol.Symbol</span> |
| <span class="sd"> """</span> |
| <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s2">"Must override this"</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="PythonOp.forward"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.PythonOp.forward">[docs]</a> <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">in_data</span><span class="p">,</span> <span class="n">out_data</span><span class="p">):</span> |
| <span class="sd">"""Forward interface. Override to create new operators.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> in_data, out_data: list</span> |
| <span class="sd"> input and output for forward. See document for</span> |
| <span class="sd"> corresponding arguments of Operator::Forward</span> |
| <span class="sd"> """</span> |
| <span class="n">out_data</span><span class="p">[</span><span class="mi">0</span><span class="p">][:]</span> <span class="o">=</span> <span class="n">in_data</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span></div> |
| |
| <div class="viewcode-block" id="PythonOp.backward"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.PythonOp.backward">[docs]</a> <span class="k">def</span> <span class="nf">backward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">out_grad</span><span class="p">,</span> <span class="n">in_data</span><span class="p">,</span> <span class="n">out_data</span><span class="p">,</span> <span class="n">in_grad</span><span class="p">):</span> |
| <span class="sd">"""Backward interface. Can override when creating new operators.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> out_grad, in_data, out_data, in_grad : list</span> |
| <span class="sd"> input and output for backward. See document for</span> |
| <span class="sd"> corresponding arguments of Operator::Backward</span> |
| <span class="sd"> """</span> |
| <span class="c1"># pylint: disable=W0613</span> |
| <span class="n">in_grad</span><span class="p">[</span><span class="mi">0</span><span class="p">][:]</span> <span class="o">=</span> <span class="mf">1.0</span></div> |
| |
| <div class="viewcode-block" id="PythonOp.infer_shape"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.PythonOp.infer_shape">[docs]</a> <span class="k">def</span> <span class="nf">infer_shape</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">in_shape</span><span class="p">):</span> |
| <span class="sd">"""Interface for ``infer_shape``. Can override when creating new operators.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> in_shape : list</span> |
| <span class="sd"> List of argument shapes in the same order as</span> |
| <span class="sd"> declared in list_arguments.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> in_shape : list</span> |
| <span class="sd"> List of argument shapes. Can be modified from in_shape.</span> |
| <span class="sd"> out_shape : list</span> |
| <span class="sd"> List of output shapes calculated from in_shape,</span> |
| <span class="sd"> in the same order as declared in list_arguments.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">in_shape</span><span class="p">,</span> <span class="p">[</span><span class="n">in_shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span></div> |
| |
| <div class="viewcode-block" id="PythonOp.list_outputs"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.PythonOp.list_outputs">[docs]</a> <span class="k">def</span> <span class="nf">list_outputs</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="sd">"""Interface for ``list_outputs``. Can override when creating new operators.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> outputs : list</span> |
| <span class="sd"> List of output blob names.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="p">[</span><span class="s1">'output'</span><span class="p">]</span></div> |
| |
| <div class="viewcode-block" id="PythonOp.list_arguments"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.PythonOp.list_arguments">[docs]</a> <span class="k">def</span> <span class="nf">list_arguments</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="sd">"""Interface for ``list_arguments``. Can override when creating new operators.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> in_shape : list</span> |
| <span class="sd"> list of argument shapes in the same order as</span> |
| <span class="sd"> declared in list_arguments.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="p">[</span><span class="s1">'data'</span><span class="p">]</span></div> |
| |
| <div class="viewcode-block" id="PythonOp.need_top_grad"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.PythonOp.need_top_grad">[docs]</a> <span class="k">def</span> <span class="nf">need_top_grad</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="sd">"""Whether this operator needs out_grad for backward.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> need_top_grad : bool</span> |
| <span class="sd"> Whether this operator needs out_grad for backward.</span> |
| <span class="sd"> Should be set to False for loss layers.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">need_top_grad_</span></div></div> |
| |
| |
| <div class="viewcode-block" id="NumpyOp"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.NumpyOp">[docs]</a><span class="k">class</span> <span class="nc">NumpyOp</span><span class="p">(</span><span class="n">PythonOp</span><span class="p">):</span> |
| <span class="sd">"""Base class for numpy operators. numpy operators allow parts</span> |
| <span class="sd"> of computation in symbolic graph to be writen in numpy. This feature</span> |
| <span class="sd"> is intended for quickly hacking out a solution for non performance</span> |
| <span class="sd"> critical parts. Please consider write a c++ implementation if it becomes</span> |
| <span class="sd"> a bottleneck.</span> |
| <span class="sd"> Note that if your operator contains internal states (like arrays),</span> |
| <span class="sd"> it cannot be used for multi-gpu training.</span> |
| <span class="sd"> """</span> |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">need_top_grad</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> |
| <span class="nb">super</span><span class="p">(</span><span class="n">NumpyOp</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">need_top_grad</span><span class="p">)</span> |
| <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s1">'NumpyOp has been deprecated. Please use CustomOp'</span><span class="p">)</span> |
| |
| <div class="viewcode-block" id="NumpyOp.get_symbol"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.NumpyOp.get_symbol">[docs]</a> <span class="k">def</span> <span class="nf">get_symbol</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="n">fb_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="kc">None</span><span class="p">,</span> <span class="n">c_int</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_float</span><span class="p">)),</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_uint</span><span class="p">)),</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> <span class="n">c_void_p</span><span class="p">)</span> |
| <span class="n">infer_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="kc">None</span><span class="p">,</span> <span class="n">c_int</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int</span><span class="p">)),</span> <span class="n">c_void_p</span><span class="p">)</span> |
| <span class="n">list_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="kc">None</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">c_char</span><span class="p">))),</span> <span class="n">c_void_p</span><span class="p">)</span> |
| |
| <span class="k">class</span> <span class="nc">NumpyOpInfo</span><span class="p">(</span><span class="n">Structure</span><span class="p">):</span> |
| <span class="sd">"""Structure that holds Callback information. Passed to NumpyOpProp"""</span> |
| <span class="n">_fields_</span> <span class="o">=</span> <span class="p">[</span> |
| <span class="p">(</span><span class="s1">'forward'</span><span class="p">,</span> <span class="n">fb_functype</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'backward'</span><span class="p">,</span> <span class="n">fb_functype</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'infer_shape'</span><span class="p">,</span> <span class="n">infer_functype</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'list_outputs'</span><span class="p">,</span> <span class="n">list_functype</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'list_arguments'</span><span class="p">,</span> <span class="n">list_functype</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'p_forward'</span><span class="p">,</span> <span class="n">c_void_p</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'p_backward'</span><span class="p">,</span> <span class="n">c_void_p</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'p_infer_shape'</span><span class="p">,</span> <span class="n">c_void_p</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'p_list_outputs'</span><span class="p">,</span> <span class="n">c_void_p</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'p_list_arguments'</span><span class="p">,</span> <span class="n">c_void_p</span><span class="p">),</span> |
| <span class="p">]</span> |
| |
| <span class="k">def</span> <span class="nf">forward_entry</span><span class="p">(</span><span class="n">num_tensor</span><span class="p">,</span> <span class="n">tensor_ptrs</span><span class="p">,</span> <span class="n">tensor_dims</span><span class="p">,</span> |
| <span class="n">tensor_shapes</span><span class="p">,</span> <span class="n">tensor_tags</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for NumpyOp::Forward"""</span> |
| <span class="n">tensors</span> <span class="o">=</span> <span class="p">[[]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">4</span><span class="p">)]</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_tensor</span><span class="p">):</span> |
| <span class="n">shape</span> <span class="o">=</span> <span class="p">[</span><span class="n">tensor_shapes</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="n">j</span><span class="p">]</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">tensor_dims</span><span class="p">[</span><span class="n">i</span><span class="p">])]</span> |
| <span class="n">buff</span> <span class="o">=</span> <span class="n">ctypes2numpy_shared</span><span class="p">(</span><span class="n">tensor_ptrs</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">shape</span><span class="p">)</span> |
| <span class="n">tensors</span><span class="p">[</span><span class="n">tensor_tags</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">buff</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="n">in_data</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">out_data</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span> |
| |
| <span class="k">def</span> <span class="nf">backward_entry</span><span class="p">(</span><span class="n">num_tensor</span><span class="p">,</span> <span class="n">tensor_ptrs</span><span class="p">,</span> <span class="n">tensor_dims</span><span class="p">,</span> |
| <span class="n">tensor_shapes</span><span class="p">,</span> <span class="n">tensor_tags</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for NumpyOp::Backward"""</span> |
| <span class="n">tensors</span> <span class="o">=</span> <span class="p">[[]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">4</span><span class="p">)]</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_tensor</span><span class="p">):</span> |
| <span class="n">shape</span> <span class="o">=</span> <span class="p">[</span><span class="n">tensor_shapes</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="n">j</span><span class="p">]</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">tensor_dims</span><span class="p">[</span><span class="n">i</span><span class="p">])]</span> |
| <span class="n">buff</span> <span class="o">=</span> <span class="n">ctypes2numpy_shared</span><span class="p">(</span><span class="n">tensor_ptrs</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">shape</span><span class="p">)</span> |
| <span class="n">tensors</span><span class="p">[</span><span class="n">tensor_tags</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">buff</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">backward</span><span class="p">(</span><span class="n">in_data</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">out_data</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> |
| <span class="n">in_grad</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">out_grad</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">3</span><span class="p">])</span> |
| |
| <span class="k">def</span> <span class="nf">infer_shape_entry</span><span class="p">(</span><span class="n">num_tensor</span><span class="p">,</span> <span class="n">tensor_dims</span><span class="p">,</span> |
| <span class="n">tensor_shapes</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for NumpyOpProp::InferShape"""</span> |
| <span class="n">n_in</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">())</span> |
| <span class="n">n_out</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">())</span> |
| <span class="k">assert</span> <span class="n">num_tensor</span> <span class="o">==</span> <span class="n">n_in</span> <span class="o">+</span> <span class="n">n_out</span> |
| |
| <span class="n">shapes</span> <span class="o">=</span> <span class="p">[[</span><span class="n">tensor_shapes</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="n">j</span><span class="p">]</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">tensor_dims</span><span class="p">[</span><span class="n">i</span><span class="p">])]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_in</span><span class="p">)]</span> |
| <span class="n">ishape</span><span class="p">,</span> <span class="n">oshape</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">infer_shape</span><span class="p">(</span><span class="n">shapes</span><span class="p">)</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">oshape</span><span class="p">)</span> <span class="o">==</span> <span class="n">n_out</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">ishape</span><span class="p">)</span> <span class="o">==</span> <span class="n">n_in</span> |
| <span class="n">rshape</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">ishape</span><span class="p">)</span> <span class="o">+</span> <span class="nb">list</span><span class="p">(</span><span class="n">oshape</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_in</span><span class="o">+</span><span class="n">n_out</span><span class="p">):</span> |
| <span class="n">tensor_shapes</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">c_array_buf</span><span class="p">(</span><span class="n">mx_int</span><span class="p">,</span> |
| <span class="n">array</span><span class="p">(</span><span class="s1">'i'</span><span class="p">,</span> <span class="n">rshape</span><span class="p">[</span><span class="n">i</span><span class="p">])),</span> |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int</span><span class="p">))</span> |
| <span class="n">tensor_dims</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">rshape</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> |
| |
| <span class="k">def</span> <span class="nf">list_outputs_entry</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for NumpyOpProp::ListOutputs"""</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">()</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="p">[</span><span class="n">c_str</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">ret</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="n">c_char_p</span><span class="p">(</span><span class="mi">0</span><span class="p">)]</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">c_array</span><span class="p">(</span><span class="n">c_char_p</span><span class="p">,</span> <span class="n">ret</span><span class="p">)</span> |
| <span class="n">out</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">ret</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">c_char</span><span class="p">)))</span> |
| |
| <span class="k">def</span> <span class="nf">list_arguments_entry</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for NumpyOpProp::ListArguments"""</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">()</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="p">[</span><span class="n">c_str</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">ret</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="n">c_char_p</span><span class="p">(</span><span class="mi">0</span><span class="p">)]</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">c_array</span><span class="p">(</span><span class="n">c_char_p</span><span class="p">,</span> <span class="n">ret</span><span class="p">)</span> |
| <span class="n">out</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">ret</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">c_char</span><span class="p">)))</span> |
| |
| <span class="bp">self</span><span class="o">.</span><span class="n">info_</span> <span class="o">=</span> <span class="n">NumpyOpInfo</span><span class="p">(</span><span class="n">fb_functype</span><span class="p">(</span><span class="n">forward_entry</span><span class="p">),</span> |
| <span class="n">fb_functype</span><span class="p">(</span><span class="n">backward_entry</span><span class="p">),</span> |
| <span class="n">infer_functype</span><span class="p">(</span><span class="n">infer_shape_entry</span><span class="p">),</span> |
| <span class="n">list_functype</span><span class="p">(</span><span class="n">list_outputs_entry</span><span class="p">),</span> |
| <span class="n">list_functype</span><span class="p">(</span><span class="n">list_arguments_entry</span><span class="p">),</span> |
| <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> |
| <span class="n">cb_ptr</span> <span class="o">=</span> <span class="nb">format</span><span class="p">(</span><span class="n">cast</span><span class="p">(</span><span class="n">pointer</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">info_</span><span class="p">),</span> <span class="n">c_void_p</span><span class="p">)</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="s1">'x'</span><span class="p">)</span> |
| <span class="c1"># pylint: disable=E1101</span> |
| <span class="n">sym</span> <span class="o">=</span> <span class="n">symbol</span><span class="o">.</span><span class="n">_internal</span><span class="o">.</span><span class="n">_Native</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> |
| <span class="n">info</span><span class="o">=</span><span class="n">cb_ptr</span><span class="p">,</span> |
| <span class="n">need_top_grad</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">need_top_grad</span><span class="p">(),</span> |
| <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> |
| <span class="c1"># keep a reference of ourself in PythonOp so we don't get garbage collected.</span> |
| <span class="n">PythonOp</span><span class="o">.</span><span class="n">_ref_holder</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> |
| <span class="k">return</span> <span class="n">sym</span></div></div> |
| |
| |
| <div class="viewcode-block" id="NDArrayOp"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.NDArrayOp">[docs]</a><span class="k">class</span> <span class="nc">NDArrayOp</span><span class="p">(</span><span class="n">PythonOp</span><span class="p">):</span> |
| <span class="sd">"""Base class for numpy operators. numpy operators allow parts</span> |
| <span class="sd"> of computation in symbolic graph to be writen in numpy. This feature</span> |
| <span class="sd"> is intended for quickly hacking out a solution for non performance</span> |
| <span class="sd"> critical parts. Please consider write a c++ implementation if it becomes</span> |
| <span class="sd"> a bottleneck.</span> |
| <span class="sd"> Note that if your operator contains internal states (like arrays),</span> |
| <span class="sd"> it cannot be used for multi-gpu training.</span> |
| <span class="sd"> """</span> |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">need_top_grad</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> |
| <span class="nb">super</span><span class="p">(</span><span class="n">NDArrayOp</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">need_top_grad</span><span class="p">)</span> |
| <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s1">'NDArrayOp has been deprecated. Please use CustomOp'</span><span class="p">)</span> |
| |
| <div class="viewcode-block" id="NDArrayOp.get_symbol"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.NDArrayOp.get_symbol">[docs]</a> <span class="k">def</span> <span class="nf">get_symbol</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> |
| <span class="n">fb_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_bool</span><span class="p">,</span> <span class="n">c_int</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_void_p</span><span class="p">),</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> <span class="n">c_void_p</span><span class="p">)</span> |
| <span class="n">infer_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_bool</span><span class="p">,</span> <span class="n">c_int</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int</span><span class="p">)),</span> <span class="n">c_void_p</span><span class="p">)</span> |
| <span class="n">list_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_bool</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">c_char</span><span class="p">))),</span> <span class="n">c_void_p</span><span class="p">)</span> |
| <span class="n">deps_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_bool</span><span class="p">,</span> <span class="n">c_int_p</span><span class="p">,</span> <span class="n">c_int_p</span><span class="p">,</span> <span class="n">c_int_p</span><span class="p">,</span> |
| <span class="n">c_int_p</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int_p</span><span class="p">),</span> <span class="n">c_void_p</span><span class="p">)</span> |
| <span class="k">class</span> <span class="nc">NDArrayOpInfo</span><span class="p">(</span><span class="n">Structure</span><span class="p">):</span> |
| <span class="sd">"""Structure that holds Callback information. Passed to NDArrayOpProp"""</span> |
| <span class="n">_fields_</span> <span class="o">=</span> <span class="p">[</span> |
| <span class="p">(</span><span class="s1">'forward'</span><span class="p">,</span> <span class="n">fb_functype</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'backward'</span><span class="p">,</span> <span class="n">fb_functype</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'infer_shape'</span><span class="p">,</span> <span class="n">infer_functype</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'list_outputs'</span><span class="p">,</span> <span class="n">list_functype</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'list_arguments'</span><span class="p">,</span> <span class="n">list_functype</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'declare_backward_dependency'</span><span class="p">,</span> <span class="n">deps_functype</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'p_forward'</span><span class="p">,</span> <span class="n">c_void_p</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'p_backward'</span><span class="p">,</span> <span class="n">c_void_p</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'p_infer_shape'</span><span class="p">,</span> <span class="n">c_void_p</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'p_list_outputs'</span><span class="p">,</span> <span class="n">c_void_p</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'p_list_arguments'</span><span class="p">,</span> <span class="n">c_void_p</span><span class="p">),</span> |
| <span class="p">(</span><span class="s1">'p_declare_backward_dependency'</span><span class="p">,</span> <span class="n">c_void_p</span><span class="p">)</span> |
| <span class="p">]</span> |
| <span class="k">def</span> <span class="nf">forward_entry</span><span class="p">(</span><span class="n">num_ndarray</span><span class="p">,</span> <span class="n">ndarraies</span><span class="p">,</span> <span class="n">tags</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for NDArrayOp::Forward"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">tensors</span> <span class="o">=</span> <span class="p">[[]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">4</span><span class="p">)]</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_ndarray</span><span class="p">):</span> |
| <span class="k">if</span> <span class="n">tags</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span> |
| <span class="n">tensors</span><span class="p">[</span><span class="n">tags</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">NDArray</span><span class="p">(</span><span class="n">cast</span><span class="p">(</span><span class="n">ndarraies</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">NDArrayHandle</span><span class="p">),</span> |
| <span class="n">writable</span><span class="o">=</span><span class="kc">True</span><span class="p">))</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">tensors</span><span class="p">[</span><span class="n">tags</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">NDArray</span><span class="p">(</span><span class="n">cast</span><span class="p">(</span><span class="n">ndarraies</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">NDArrayHandle</span><span class="p">),</span> |
| <span class="n">writable</span><span class="o">=</span><span class="kc">False</span><span class="p">))</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="n">in_data</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">out_data</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in NDArrayOp.forward: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">())</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="k">def</span> <span class="nf">backward_entry</span><span class="p">(</span><span class="n">num_ndarray</span><span class="p">,</span> <span class="n">ndarraies</span><span class="p">,</span> <span class="n">tags</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for NDArrayOp::Backward"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">tensors</span> <span class="o">=</span> <span class="p">[[]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">4</span><span class="p">)]</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_ndarray</span><span class="p">):</span> |
| <span class="k">if</span> <span class="n">tags</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span> |
| <span class="n">tensors</span><span class="p">[</span><span class="n">tags</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">NDArray</span><span class="p">(</span><span class="n">cast</span><span class="p">(</span><span class="n">ndarraies</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">NDArrayHandle</span><span class="p">),</span> |
| <span class="n">writable</span><span class="o">=</span><span class="kc">True</span><span class="p">))</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">tensors</span><span class="p">[</span><span class="n">tags</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">NDArray</span><span class="p">(</span><span class="n">cast</span><span class="p">(</span><span class="n">ndarraies</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">NDArrayHandle</span><span class="p">),</span> |
| <span class="n">writable</span><span class="o">=</span><span class="kc">False</span><span class="p">))</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">backward</span><span class="p">(</span><span class="n">in_data</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">out_data</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> |
| <span class="n">in_grad</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">out_grad</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">3</span><span class="p">])</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in NDArrayOp.backward: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">())</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="k">def</span> <span class="nf">infer_shape_entry</span><span class="p">(</span><span class="n">num_tensor</span><span class="p">,</span> <span class="n">tensor_dims</span><span class="p">,</span> |
| <span class="n">tensor_shapes</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for NDArrayOpProp::InferShape"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">n_in</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">())</span> |
| <span class="n">n_out</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">())</span> |
| <span class="k">assert</span> <span class="n">num_tensor</span> <span class="o">==</span> <span class="n">n_in</span> <span class="o">+</span> <span class="n">n_out</span> |
| |
| <span class="n">shapes</span> <span class="o">=</span> <span class="p">[[</span><span class="n">tensor_shapes</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="n">j</span><span class="p">]</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">tensor_dims</span><span class="p">[</span><span class="n">i</span><span class="p">])]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_in</span><span class="p">)]</span> |
| <span class="n">ishape</span><span class="p">,</span> <span class="n">oshape</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">infer_shape</span><span class="p">(</span><span class="n">shapes</span><span class="p">)</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">oshape</span><span class="p">)</span> <span class="o">==</span> <span class="n">n_out</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">ishape</span><span class="p">)</span> <span class="o">==</span> <span class="n">n_in</span> |
| <span class="n">rshape</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">ishape</span><span class="p">)</span> <span class="o">+</span> <span class="nb">list</span><span class="p">(</span><span class="n">oshape</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_in</span><span class="o">+</span><span class="n">n_out</span><span class="p">):</span> |
| <span class="n">tensor_shapes</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">c_array_buf</span><span class="p">(</span><span class="n">mx_int</span><span class="p">,</span> |
| <span class="n">array</span><span class="p">(</span><span class="s1">'i'</span><span class="p">,</span> <span class="n">rshape</span><span class="p">[</span><span class="n">i</span><span class="p">])),</span> |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int</span><span class="p">))</span> |
| <span class="n">tensor_dims</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">rshape</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in NDArrayOp.infer_shape: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">())</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="k">def</span> <span class="nf">list_outputs_entry</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for NDArrayOpProp::ListOutputs"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">()</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="p">[</span><span class="n">c_str</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">ret</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="n">c_char_p</span><span class="p">(</span><span class="mi">0</span><span class="p">)]</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">c_array</span><span class="p">(</span><span class="n">c_char_p</span><span class="p">,</span> <span class="n">ret</span><span class="p">)</span> |
| <span class="n">out</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">ret</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">c_char</span><span class="p">)))</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in NDArrayOp.list_outputs: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">())</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="k">def</span> <span class="nf">list_arguments_entry</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for NDArrayOpProp::ListArguments"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">()</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="p">[</span><span class="n">c_str</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">ret</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="n">c_char_p</span><span class="p">(</span><span class="mi">0</span><span class="p">)]</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">c_array</span><span class="p">(</span><span class="n">c_char_p</span><span class="p">,</span> <span class="n">ret</span><span class="p">)</span> |
| <span class="n">out</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">ret</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">c_char</span><span class="p">)))</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in NDArrayOp.list_arguments: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">())</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="k">def</span> <span class="nf">declare_backward_dependency</span><span class="p">(</span><span class="n">out_grad</span><span class="p">,</span> <span class="n">in_data</span><span class="p">,</span> <span class="n">out_data</span><span class="p">,</span> <span class="n">num_dep</span><span class="p">,</span> <span class="n">deps</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for NDArrayOpProp::DeclareBacwardDependency"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">out_grad</span> <span class="o">=</span> <span class="p">[</span><span class="n">out_grad</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">()))]</span> |
| <span class="n">in_data</span> <span class="o">=</span> <span class="p">[</span><span class="n">in_data</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">()))]</span> |
| <span class="n">out_data</span> <span class="o">=</span> <span class="p">[</span><span class="n">out_data</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">()))]</span> |
| <span class="n">rdeps</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">declare_backward_dependency</span><span class="p">(</span><span class="n">out_grad</span><span class="p">,</span> <span class="n">in_data</span><span class="p">,</span> <span class="n">out_data</span><span class="p">)</span> |
| <span class="n">num_dep</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">rdeps</span><span class="p">)</span> |
| <span class="n">rdeps</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">c_array_buf</span><span class="p">(</span><span class="n">c_int</span><span class="p">,</span> <span class="n">array</span><span class="p">(</span><span class="s1">'i'</span><span class="p">,</span> <span class="n">rdeps</span><span class="p">)),</span> <span class="n">c_int_p</span><span class="p">)</span> |
| <span class="n">deps</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">rdeps</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in NDArrayOp.declare_backward_dependency: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">())</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="bp">self</span><span class="o">.</span><span class="n">info_</span> <span class="o">=</span> <span class="n">NDArrayOpInfo</span><span class="p">(</span><span class="n">fb_functype</span><span class="p">(</span><span class="n">forward_entry</span><span class="p">),</span> |
| <span class="n">fb_functype</span><span class="p">(</span><span class="n">backward_entry</span><span class="p">),</span> |
| <span class="n">infer_functype</span><span class="p">(</span><span class="n">infer_shape_entry</span><span class="p">),</span> |
| <span class="n">list_functype</span><span class="p">(</span><span class="n">list_outputs_entry</span><span class="p">),</span> |
| <span class="n">list_functype</span><span class="p">(</span><span class="n">list_arguments_entry</span><span class="p">),</span> |
| <span class="n">deps_functype</span><span class="p">(</span><span class="n">declare_backward_dependency</span><span class="p">),</span> |
| <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> |
| <span class="n">cb_ptr</span> <span class="o">=</span> <span class="nb">format</span><span class="p">(</span><span class="n">cast</span><span class="p">(</span><span class="n">pointer</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">info_</span><span class="p">),</span> <span class="n">c_void_p</span><span class="p">)</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="s1">'x'</span><span class="p">)</span> |
| <span class="c1"># pylint: disable=E1101</span> |
| <span class="n">sym</span> <span class="o">=</span> <span class="n">symbol</span><span class="o">.</span><span class="n">_internal</span><span class="o">.</span><span class="n">_NDArray</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> |
| <span class="n">info</span><span class="o">=</span><span class="n">cb_ptr</span><span class="p">,</span> |
| <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> |
| <span class="c1"># keep a reference of ourself in PythonOp so we don't get garbage collected.</span> |
| <span class="n">PythonOp</span><span class="o">.</span><span class="n">_ref_holder</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> |
| <span class="k">return</span> <span class="n">sym</span></div> |
| |
| <div class="viewcode-block" id="NDArrayOp.declare_backward_dependency"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.NDArrayOp.declare_backward_dependency">[docs]</a> <span class="k">def</span> <span class="nf">declare_backward_dependency</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">out_grad</span><span class="p">,</span> <span class="n">in_data</span><span class="p">,</span> <span class="n">out_data</span><span class="p">):</span> |
| <span class="sd">"""Declare dependencies of this operator for backward pass.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> out_grad : list of int</span> |
| <span class="sd"> ids of out_grad blobs.</span> |
| <span class="sd"> in_data : list of int</span> |
| <span class="sd"> ids of in_data blobs.</span> |
| <span class="sd"> out_data: list of int</span> |
| <span class="sd"> ids of out_data blobs.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> deps : list of int</span> |
| <span class="sd"> ids of the needed blobs.</span> |
| <span class="sd"> """</span> |
| <span class="n">deps</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">need_top_grad</span><span class="p">():</span> |
| <span class="n">deps</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">out_grad</span><span class="p">)</span> |
| <span class="n">deps</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">in_data</span><span class="p">)</span> |
| <span class="n">deps</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">out_data</span><span class="p">)</span> |
| <span class="k">return</span> <span class="n">deps</span></div></div> |
| |
| |
| <div class="viewcode-block" id="CustomOp"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.CustomOp">[docs]</a><span class="k">class</span> <span class="nc">CustomOp</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span> |
| <span class="sd">"""Base class for operators implemented in python"""</span> |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">pass</span> |
| |
| <div class="viewcode-block" id="CustomOp.forward"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.CustomOp.forward">[docs]</a> <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">is_train</span><span class="p">,</span> <span class="n">req</span><span class="p">,</span> <span class="n">in_data</span><span class="p">,</span> <span class="n">out_data</span><span class="p">,</span> <span class="n">aux</span><span class="p">):</span> |
| <span class="sd">"""Forward interface. Can override when creating new operators.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> is_train : bool</span> |
| <span class="sd"> whether this is for training</span> |
| <span class="sd"> req : list of str</span> |
| <span class="sd"> how to assign to out_data. can be 'null', 'write', or 'add'.</span> |
| <span class="sd"> You can optionally use self.assign(dst, req, src) to handle this.</span> |
| <span class="sd"> in_data, out_data, aux: list of NDArrays</span> |
| <span class="sd"> input, output, and auxiliary states for forward. See document for</span> |
| <span class="sd"> corresponding arguments of Operator::Forward</span> |
| <span class="sd"> """</span> |
| <span class="c1"># pylint: disable=W0613</span> |
| <span class="k">pass</span></div> |
| |
| <div class="viewcode-block" id="CustomOp.backward"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.CustomOp.backward">[docs]</a> <span class="k">def</span> <span class="nf">backward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">req</span><span class="p">,</span> <span class="n">out_grad</span><span class="p">,</span> <span class="n">in_data</span><span class="p">,</span> <span class="n">out_data</span><span class="p">,</span> <span class="n">in_grad</span><span class="p">,</span> <span class="n">aux</span><span class="p">):</span> |
| <span class="sd">"""Backward interface. Can override when creating new operators.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> req : list of str</span> |
| <span class="sd"> how to assign to in_grad. can be 'null', 'write', or 'add'.</span> |
| <span class="sd"> You can optionally use self.assign(dst, req, src) to handle this.</span> |
| <span class="sd"> out_grad, in_data, out_data, in_grad, aux : list of NDArrays</span> |
| <span class="sd"> input and output for backward. See document for</span> |
| <span class="sd"> corresponding arguments of Operator::Backward</span> |
| <span class="sd"> """</span> |
| <span class="c1"># pylint: disable=W0613</span> |
| <span class="k">pass</span></div> |
| |
| <div class="viewcode-block" id="CustomOp.assign"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.CustomOp.assign">[docs]</a> <span class="k">def</span> <span class="nf">assign</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">dst</span><span class="p">,</span> <span class="n">req</span><span class="p">,</span> <span class="n">src</span><span class="p">):</span> |
| <span class="sd">"""Helper function for assigning into dst depending on requirements."""</span> |
| <span class="k">if</span> <span class="n">req</span> <span class="o">==</span> <span class="s1">'null'</span><span class="p">:</span> |
| <span class="k">return</span> |
| <span class="k">elif</span> <span class="n">req</span> <span class="ow">in</span> <span class="p">(</span><span class="s1">'write'</span><span class="p">,</span> <span class="s1">'inplace'</span><span class="p">):</span> |
| <span class="k">if</span> <span class="n">is_np_array</span><span class="p">():</span> |
| <span class="n">dst</span><span class="p">[()]</span> <span class="o">=</span> <span class="n">src</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">dst</span><span class="p">[:]</span> <span class="o">=</span> <span class="n">src</span> |
| <span class="k">elif</span> <span class="n">req</span> <span class="o">==</span> <span class="s1">'add'</span><span class="p">:</span> |
| <span class="k">if</span> <span class="n">is_np_array</span><span class="p">():</span> |
| <span class="n">dst</span><span class="p">[()]</span> <span class="o">+=</span> <span class="n">src</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">dst</span><span class="p">[:]</span> <span class="o">+=</span> <span class="n">src</span></div></div> |
| |
| |
| <div class="viewcode-block" id="CustomOpProp"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.CustomOpProp">[docs]</a><span class="k">class</span> <span class="nc">CustomOpProp</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span> |
| <span class="sd">"""Base class for operator property class implemented in python.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> need_top_grad : bool</span> |
| <span class="sd"> The default declare_backward_dependency function. Use this value</span> |
| <span class="sd"> to determine whether this operator needs gradient input.</span> |
| <span class="sd"> """</span> |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">need_top_grad</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">need_top_grad_</span> <span class="o">=</span> <span class="n">need_top_grad</span> |
| |
| <div class="viewcode-block" id="CustomOpProp.infer_shape"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.CustomOpProp.infer_shape">[docs]</a> <span class="k">def</span> <span class="nf">infer_shape</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">in_shape</span><span class="p">):</span> |
| <span class="sd">"""infer_shape interface. Can override when creating new operators.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> in_shape : list</span> |
| <span class="sd"> List of argument shapes in the same order as</span> |
| <span class="sd"> declared in list_arguments.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> in_shape : list</span> |
| <span class="sd"> List of argument shapes. Can be modified from in_shape.</span> |
| <span class="sd"> out_shape : list</span> |
| <span class="sd"> List of output shapes calculated from in_shape,</span> |
| <span class="sd"> in the same order as declared in list_outputs.</span> |
| <span class="sd"> aux_shape : Optional, list</span> |
| <span class="sd"> List of aux shapes calculated from in_shape,</span> |
| <span class="sd"> in the same order as declared in list_auxiliary_states.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">in_shape</span><span class="p">,</span> <span class="p">(</span><span class="n">in_shape</span><span class="p">[</span><span class="mi">0</span><span class="p">],)</span><span class="o">*</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">()),</span> <span class="p">()</span></div> |
| |
| <div class="viewcode-block" id="CustomOpProp.infer_type"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.CustomOpProp.infer_type">[docs]</a> <span class="k">def</span> <span class="nf">infer_type</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">in_type</span><span class="p">):</span> |
| <span class="sd">"""infer_type interface. override to create new operators</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> in_type : list of np.dtype</span> |
| <span class="sd"> list of argument types in the same order as</span> |
| <span class="sd"> declared in list_arguments.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> in_type : list</span> |
| <span class="sd"> list of argument types. Can be modified from in_type.</span> |
| <span class="sd"> out_type : list</span> |
| <span class="sd"> list of output types calculated from in_type,</span> |
| <span class="sd"> in the same order as declared in list_outputs.</span> |
| <span class="sd"> aux_type : Optional, list</span> |
| <span class="sd"> list of aux types calculated from in_type,</span> |
| <span class="sd"> in the same order as declared in list_auxiliary_states.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="n">in_type</span><span class="p">,</span> <span class="p">[</span><span class="n">in_type</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">*</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">()),</span> \ |
| <span class="p">[</span><span class="n">in_type</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">*</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">list_auxiliary_states</span><span class="p">())</span></div> |
| |
| <div class="viewcode-block" id="CustomOpProp.infer_storage_type"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.CustomOpProp.infer_storage_type">[docs]</a> <span class="k">def</span> <span class="nf">infer_storage_type</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">in_stype</span><span class="p">):</span> |
| <span class="sd">"""infer_storage_type interface. Used to infer storage type of</span> |
| <span class="sd"> inputs and outputs in the forward pass. When this interface is not implemented,</span> |
| <span class="sd"> all stypes will be inferred as default.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> in_stype : list of stypes, valid stypes are default, row_sparse and</span> |
| <span class="sd"> csr</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> in_stype : list</span> |
| <span class="sd"> list of argument stypes.</span> |
| <span class="sd"> out_stype : list</span> |
| <span class="sd"> list of output types calculated from in_stype,</span> |
| <span class="sd"> in the same order as declared in list_outputs.</span> |
| <span class="sd"> aux_type : Optional, list</span> |
| <span class="sd"> list of aux types calculated from in_stype,</span> |
| <span class="sd"> in the same order as declared in list_auxiliary_states.</span> |
| <span class="sd"> """</span> |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">stype</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">in_stype</span><span class="p">):</span> |
| <span class="k">assert</span> <span class="n">stype</span> <span class="o">==</span> <span class="n">_STORAGE_TYPE_ID_TO_STR</span><span class="p">[</span><span class="n">_STORAGE_TYPE_DEFAULT</span><span class="p">],</span> \ |
| <span class="s2">"Default infer_storage_type implementation doesnt allow non default stypes: "</span> \ |
| <span class="s2">"found non default stype '</span><span class="si">%s</span><span class="s2">' for in_stype[</span><span class="si">%d</span><span class="s2">]. Please implement "</span> \ |
| <span class="s2">"infer_storage_type and infer_storage_type_backward interface "</span> \ |
| <span class="s2">"in your custom operator if you have non-default input/output stypes"</span> <span class="o">%</span> <span class="p">(</span><span class="n">stype</span><span class="p">,</span> <span class="n">i</span><span class="p">)</span> |
| <span class="k">return</span> <span class="n">in_stype</span><span class="p">,</span> \ |
| <span class="p">[</span><span class="n">_STORAGE_TYPE_ID_TO_STR</span><span class="p">[</span><span class="n">_STORAGE_TYPE_DEFAULT</span><span class="p">]]</span><span class="o">*</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">()),</span> \ |
| <span class="p">[</span><span class="n">_STORAGE_TYPE_ID_TO_STR</span><span class="p">[</span><span class="n">_STORAGE_TYPE_DEFAULT</span><span class="p">]]</span><span class="o">*</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">list_auxiliary_states</span><span class="p">())</span></div> |
| |
| <div class="viewcode-block" id="CustomOpProp.infer_storage_type_backward"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.CustomOpProp.infer_storage_type_backward">[docs]</a> <span class="k">def</span> <span class="nf">infer_storage_type_backward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ograd_stype</span><span class="p">,</span> <span class="n">in_stype</span><span class="p">,</span> <span class="n">out_stype</span><span class="p">,</span> <span class="n">igrad_stype</span><span class="p">,</span> <span class="n">aux_stype</span><span class="p">):</span> |
| <span class="sd">"""infer_storage_type_backward interface. Used to infer storage</span> |
| <span class="sd"> type of inputs and outputs in the backward pass.</span> |
| |
| <span class="sd"> Will raise an error if undefined storage type is returned.</span> |
| <span class="sd"> Returned lists have to be the same size as the input lists to infer_storage_type_backward,</span> |
| <span class="sd"> otherwise an exception will be thrown. When this interface is not implemented,</span> |
| <span class="sd"> all stypes will be inferred as default.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> ograd_stype : list</span> |
| <span class="sd"> list of output gradient storage types</span> |
| <span class="sd"> in_stype : list</span> |
| <span class="sd"> list of input storage types</span> |
| <span class="sd"> out_stype : list</span> |
| <span class="sd"> list of output storage types</span> |
| <span class="sd"> igrad_stype : list</span> |
| <span class="sd"> list of input gradient storage types</span> |
| <span class="sd"> aux_stype : list</span> |
| <span class="sd"> list of auxiliary storage types</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> ograd_stype : list</span> |
| <span class="sd"> list of inferred output gradient storage types</span> |
| <span class="sd"> in_stype : list</span> |
| <span class="sd"> list of inferred input storage types</span> |
| <span class="sd"> out_stype : list</span> |
| <span class="sd"> list of inferred output storage types</span> |
| <span class="sd"> igrad_stype : list</span> |
| <span class="sd"> list of inferred input gradient storage types</span> |
| <span class="sd"> aux_stype : list</span> |
| <span class="sd"> list of inferred storage types for auxiliary states</span> |
| <span class="sd"> """</span> |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">stype</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">ograd_stype</span><span class="p">):</span> |
| <span class="k">assert</span> <span class="n">stype</span> <span class="o">==</span> <span class="n">_STORAGE_TYPE_ID_TO_STR</span><span class="p">[</span><span class="n">_STORAGE_TYPE_DEFAULT</span><span class="p">],</span> \ |
| <span class="s2">"Default infer_storage_type_backward implementation doesnt allow non default stypes: "</span> \ |
| <span class="s2">"found non default stype '</span><span class="si">%s</span><span class="s2">' for ograd_stype[</span><span class="si">%d</span><span class="s2">]. Please implement "</span> \ |
| <span class="s2">"infer_storage_type and infer_storage_type_backward interface "</span> \ |
| <span class="s2">"in your custom operator if you have non-default output gradient stypes"</span> <span class="o">%</span> <span class="p">(</span><span class="n">stype</span><span class="p">,</span> <span class="n">i</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">stype</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">igrad_stype</span><span class="p">):</span> |
| <span class="k">if</span> <span class="n">stype</span> <span class="o">==</span> <span class="n">_STORAGE_TYPE_ID_TO_STR</span><span class="p">[</span><span class="n">_STORAGE_TYPE_UNDEFINED</span><span class="p">]:</span> |
| <span class="n">stype</span> <span class="o">=</span> <span class="n">_STORAGE_TYPE_ID_TO_STR</span><span class="p">[</span><span class="n">_STORAGE_TYPE_DEFAULT</span><span class="p">]</span> |
| <span class="k">assert</span> <span class="n">stype</span> <span class="o">==</span> <span class="n">_STORAGE_TYPE_ID_TO_STR</span><span class="p">[</span><span class="n">_STORAGE_TYPE_DEFAULT</span><span class="p">],</span> \ |
| <span class="s2">"Default infer_storage_type_backward implementation doesnt allow non default stypes: "</span> \ |
| <span class="s2">"found non default stype '</span><span class="si">%s</span><span class="s2">' for igrad_stype[</span><span class="si">%d</span><span class="s2">]. Please implement "</span> \ |
| <span class="s2">"infer_storage_type and infer_storage_type_backward interface "</span> \ |
| <span class="s2">"in your custom operator if you have non-default input gradient stypes"</span> <span class="o">%</span> <span class="p">(</span><span class="n">stype</span><span class="p">,</span> <span class="n">i</span><span class="p">)</span> |
| <span class="n">stype_lists</span> <span class="o">=</span> <span class="p">[</span><span class="n">ograd_stype</span><span class="p">,</span> <span class="n">in_stype</span><span class="p">,</span> <span class="n">out_stype</span><span class="p">,</span> <span class="n">igrad_stype</span><span class="p">,</span> <span class="n">aux_stype</span><span class="p">]</span> |
| <span class="k">for</span> <span class="n">stype_list</span> <span class="ow">in</span> <span class="n">stype_lists</span><span class="p">:</span> |
| <span class="n">stype_list</span><span class="p">[:]</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">stype_list</span><span class="p">)</span> <span class="o">*</span> <span class="p">[</span><span class="n">_STORAGE_TYPE_ID_TO_STR</span><span class="p">[</span><span class="n">_STORAGE_TYPE_DEFAULT</span><span class="p">]]</span> |
| <span class="k">return</span> <span class="n">stype_lists</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">stype_lists</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">stype_lists</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">stype_lists</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">stype_lists</span><span class="p">[</span><span class="mi">4</span><span class="p">]</span></div> |
| |
| <div class="viewcode-block" id="CustomOpProp.list_outputs"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.CustomOpProp.list_outputs">[docs]</a> <span class="k">def</span> <span class="nf">list_outputs</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="sd">"""list_outputs interface. Can override when creating new operators.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> outputs : list</span> |
| <span class="sd"> List of output blob names.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="p">[</span><span class="s1">'output'</span><span class="p">]</span></div> |
| |
| <div class="viewcode-block" id="CustomOpProp.list_arguments"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.CustomOpProp.list_arguments">[docs]</a> <span class="k">def</span> <span class="nf">list_arguments</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="sd">"""list_arguments interface. Can override when creating new operators.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> arguments : list</span> |
| <span class="sd"> List of argument blob names.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="p">[</span><span class="s1">'data'</span><span class="p">]</span></div> |
| |
| <div class="viewcode-block" id="CustomOpProp.list_auxiliary_states"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.CustomOpProp.list_auxiliary_states">[docs]</a> <span class="k">def</span> <span class="nf">list_auxiliary_states</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="sd">"""list_auxiliary_states interface. Can override when creating new operators.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> auxs : list</span> |
| <span class="sd"> list of auxiliary state blob names.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="p">[]</span></div> |
| |
| <div class="viewcode-block" id="CustomOpProp.declare_backward_dependency"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.CustomOpProp.declare_backward_dependency">[docs]</a> <span class="k">def</span> <span class="nf">declare_backward_dependency</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">out_grad</span><span class="p">,</span> <span class="n">in_data</span><span class="p">,</span> <span class="n">out_data</span><span class="p">):</span> |
| <span class="sd">"""Declare dependencies of this operator for backward pass.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> out_grad : list of int</span> |
| <span class="sd"> ids of out_grad blobs.</span> |
| <span class="sd"> in_data : list of int</span> |
| <span class="sd"> ids of in_data blobs.</span> |
| <span class="sd"> out_data: list of int</span> |
| <span class="sd"> ids of out_data blobs.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> deps : list of int</span> |
| <span class="sd"> ids of the needed blobs.</span> |
| <span class="sd"> """</span> |
| <span class="n">deps</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">need_top_grad_</span><span class="p">:</span> |
| <span class="n">deps</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">out_grad</span><span class="p">)</span> |
| <span class="n">deps</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">in_data</span><span class="p">)</span> |
| <span class="n">deps</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">out_data</span><span class="p">)</span> |
| <span class="k">return</span> <span class="n">deps</span></div> |
| |
| <div class="viewcode-block" id="CustomOpProp.create_operator"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.CustomOpProp.create_operator">[docs]</a> <span class="k">def</span> <span class="nf">create_operator</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ctx</span><span class="p">,</span> <span class="n">in_shapes</span><span class="p">,</span> <span class="n">in_dtypes</span><span class="p">):</span> |
| <span class="sd">"""Create an operator that carries out the real computation</span> |
| <span class="sd"> given the context, input shapes, and input data types."""</span> |
| <span class="c1"># pylint: disable=W0613</span> |
| <span class="k">return</span> <span class="n">CustomOp</span><span class="p">()</span></div></div> |
| |
| |
| <span class="k">class</span> <span class="nc">_Registry</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span> |
| <span class="sd">"""CustomOp registry."""</span> |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">ref_holder</span> <span class="o">=</span> <span class="p">{}</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">counter</span> <span class="o">=</span> <span class="mi">0</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">result_deps</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">lock</span> <span class="o">=</span> <span class="n">Lock</span><span class="p">()</span> |
| |
| <span class="k">def</span> <span class="nf">inc</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="sd">"""Get index for new entry."""</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">lock</span><span class="o">.</span><span class="n">acquire</span><span class="p">()</span> |
| <span class="n">cur</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">counter</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">counter</span> <span class="o">+=</span> <span class="mi">1</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">lock</span><span class="o">.</span><span class="n">release</span><span class="p">()</span> |
| <span class="k">return</span> <span class="n">cur</span> |
| |
| |
| <span class="n">_registry</span> <span class="o">=</span> <span class="n">_Registry</span><span class="p">()</span> |
| |
| |
| <div class="viewcode-block" id="register"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.register">[docs]</a><span class="k">def</span> <span class="nf">register</span><span class="p">(</span><span class="n">reg_name</span><span class="p">):</span> |
| <span class="sd">"""Register a subclass of CustomOpProp to the registry with name reg_name."""</span> |
| <span class="k">def</span> <span class="nf">do_register</span><span class="p">(</span><span class="n">prop_cls</span><span class="p">):</span> |
| <span class="sd">"""Register a subclass of CustomOpProp to the registry."""</span> |
| <span class="n">fb_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">,</span> <span class="n">c_int</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_void_p</span><span class="p">),</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> <span class="n">c_int</span><span class="p">,</span> <span class="n">c_void_p</span><span class="p">)</span> |
| <span class="n">del_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">,</span> <span class="n">c_void_p</span><span class="p">)</span> |
| |
| <span class="n">infershape_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">,</span> <span class="n">c_int</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int</span><span class="p">)),</span> <span class="n">c_void_p</span><span class="p">)</span> |
| <span class="n">infertype_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">,</span> <span class="n">c_int</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> <span class="n">c_void_p</span><span class="p">)</span> |
| <span class="n">inferstorage_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">,</span> <span class="n">c_int</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> <span class="n">c_void_p</span><span class="p">)</span> |
| <span class="n">inferstorage_backward_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">,</span> <span class="n">c_int</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> \ |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> <span class="n">c_void_p</span><span class="p">)</span> |
| <span class="n">list_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">c_char</span><span class="p">))),</span> <span class="n">c_void_p</span><span class="p">)</span> |
| <span class="n">deps_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">,</span> <span class="n">c_int_p</span><span class="p">,</span> <span class="n">c_int_p</span><span class="p">,</span> <span class="n">c_int_p</span><span class="p">,</span> |
| <span class="n">c_int_p</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int_p</span><span class="p">),</span> <span class="n">c_void_p</span><span class="p">)</span> |
| <span class="n">createop_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">,</span> <span class="n">c_char_p</span><span class="p">,</span> <span class="n">c_int</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">mx_uint</span><span class="p">)),</span> |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">MXCallbackList</span><span class="p">),</span> <span class="n">c_void_p</span><span class="p">)</span> |
| <span class="n">req_enum</span> <span class="o">=</span> <span class="p">(</span><span class="s1">'null'</span><span class="p">,</span> <span class="s1">'write'</span><span class="p">,</span> <span class="s1">'inplace'</span><span class="p">,</span> <span class="s1">'add'</span><span class="p">)</span> |
| <span class="n">create_ndarray_fn</span> <span class="o">=</span> <span class="n">_np_ndarray_cls</span> <span class="k">if</span> <span class="n">is_np_array</span><span class="p">()</span> <span class="k">else</span> <span class="n">_ndarray_cls</span> |
| |
| <span class="k">def</span> <span class="nf">creator</span><span class="p">(</span><span class="n">op_type</span><span class="p">,</span> <span class="n">argc</span><span class="p">,</span> <span class="n">keys</span><span class="p">,</span> <span class="n">vals</span><span class="p">,</span> <span class="n">ret</span><span class="p">):</span> |
| <span class="sd">"""internal function"""</span> |
| <span class="k">assert</span> <span class="n">py_str</span><span class="p">(</span><span class="n">op_type</span><span class="p">)</span> <span class="o">==</span> <span class="n">reg_name</span> |
| <span class="n">kwargs</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">([(</span><span class="n">py_str</span><span class="p">(</span><span class="n">keys</span><span class="p">[</span><span class="n">i</span><span class="p">]),</span> <span class="n">py_str</span><span class="p">(</span><span class="n">vals</span><span class="p">[</span><span class="n">i</span><span class="p">]))</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">argc</span><span class="p">)])</span> |
| <span class="n">op_prop</span> <span class="o">=</span> <span class="n">prop_cls</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">infer_shape_entry</span><span class="p">(</span><span class="n">num_tensor</span><span class="p">,</span> <span class="n">tensor_dims</span><span class="p">,</span> |
| <span class="n">tensor_shapes</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for ``CustomOpProp::InferShape``."""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">n_in</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">op_prop</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">())</span> |
| <span class="n">n_out</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">op_prop</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">())</span> |
| <span class="n">n_aux</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">op_prop</span><span class="o">.</span><span class="n">list_auxiliary_states</span><span class="p">())</span> |
| <span class="k">assert</span> <span class="n">num_tensor</span> <span class="o">==</span> <span class="n">n_in</span> <span class="o">+</span> <span class="n">n_out</span> <span class="o">+</span> <span class="n">n_aux</span> |
| |
| <span class="n">shapes</span> <span class="o">=</span> <span class="p">[[</span><span class="n">tensor_shapes</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="n">j</span><span class="p">]</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">tensor_dims</span><span class="p">[</span><span class="n">i</span><span class="p">])]</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_in</span><span class="p">)]</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">op_prop</span><span class="o">.</span><span class="n">infer_shape</span><span class="p">(</span><span class="n">shapes</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span> |
| <span class="n">ishape</span><span class="p">,</span> <span class="n">oshape</span> <span class="o">=</span> <span class="n">ret</span> |
| <span class="n">ashape</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">elif</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span> <span class="o">==</span> <span class="mi">3</span><span class="p">:</span> |
| <span class="n">ishape</span><span class="p">,</span> <span class="n">oshape</span><span class="p">,</span> <span class="n">ashape</span> <span class="o">=</span> <span class="n">ret</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">AssertionError</span><span class="p">(</span><span class="s2">"infer_shape must return 2 or 3 lists"</span><span class="p">)</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">oshape</span><span class="p">)</span> <span class="o">==</span> <span class="n">n_out</span><span class="p">,</span> \ |
| <span class="s2">"InferShape Error: expecting </span><span class="si">%d</span><span class="s2"> entries in returned output "</span> \ |
| <span class="s2">"shapes, got </span><span class="si">%d</span><span class="s2">."</span><span class="o">%</span><span class="p">(</span><span class="n">n_out</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">oshape</span><span class="p">))</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">ishape</span><span class="p">)</span> <span class="o">==</span> <span class="n">n_in</span><span class="p">,</span> \ |
| <span class="s2">"InferShape Error: expecting </span><span class="si">%d</span><span class="s2"> entries in returned input "</span> \ |
| <span class="s2">"shapes, got </span><span class="si">%d</span><span class="s2">."</span><span class="o">%</span><span class="p">(</span><span class="n">n_in</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">ishape</span><span class="p">))</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">ashape</span><span class="p">)</span> <span class="o">==</span> <span class="n">n_aux</span><span class="p">,</span> \ |
| <span class="s2">"InferShape Error: expecting </span><span class="si">%d</span><span class="s2"> entries in returned aux state "</span> \ |
| <span class="s2">"shapes, got </span><span class="si">%d</span><span class="s2">."</span><span class="o">%</span><span class="p">(</span><span class="n">n_aux</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">ashape</span><span class="p">))</span> |
| <span class="n">rshape</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">ishape</span><span class="p">)</span> <span class="o">+</span> <span class="nb">list</span><span class="p">(</span><span class="n">oshape</span><span class="p">)</span> <span class="o">+</span> <span class="nb">list</span><span class="p">(</span><span class="n">ashape</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_in</span><span class="o">+</span><span class="n">n_out</span><span class="o">+</span><span class="n">n_aux</span><span class="p">):</span> |
| <span class="n">tensor_shapes</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">c_array_buf</span><span class="p">(</span><span class="n">mx_int</span><span class="p">,</span> |
| <span class="n">array</span><span class="p">(</span><span class="s1">'i'</span><span class="p">,</span> <span class="n">rshape</span><span class="p">[</span><span class="n">i</span><span class="p">])),</span> |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">mx_int</span><span class="p">))</span> |
| <span class="n">tensor_dims</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">rshape</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> |
| |
| <span class="n">infer_shape_entry</span><span class="o">.</span><span class="n">_ref_holder</span> <span class="o">=</span> <span class="p">[</span><span class="n">tensor_shapes</span><span class="p">]</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in </span><span class="si">%s</span><span class="s1">.infer_shape: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">reg_name</span><span class="p">,</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">()))</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="k">def</span> <span class="nf">infer_storage_type_backward_entry</span><span class="p">(</span><span class="n">num_tensor</span><span class="p">,</span> <span class="n">tensor_stypes</span><span class="p">,</span> <span class="n">tags</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="c1"># pylint: disable=C0301</span> |
| <span class="sd">"""C Callback for CustomOpProp::InferStorageTypeBackward"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">tensors</span> <span class="o">=</span> <span class="p">[[]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">)]</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_tensor</span><span class="p">):</span> |
| <span class="n">tensors</span><span class="p">[</span><span class="n">tags</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_STORAGE_TYPE_ID_TO_STR</span><span class="p">[</span><span class="n">tensor_stypes</span><span class="p">[</span><span class="n">i</span><span class="p">]])</span> |
| <span class="c1"># Ordering of stypes: ograd, input, output, igrad, aux</span> |
| <span class="n">tensors</span> <span class="o">=</span> <span class="p">[</span><span class="n">tensors</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">tensors</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">tensors</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">tensors</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">tensors</span><span class="p">[</span><span class="mi">4</span><span class="p">]]</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">op_prop</span><span class="o">.</span><span class="n">infer_storage_type_backward</span><span class="p">(</span><span class="n">tensors</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> |
| <span class="n">tensors</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> |
| <span class="n">tensors</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> |
| <span class="n">tensors</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> |
| <span class="n">tensors</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span> <span class="o">==</span> <span class="mi">4</span><span class="p">:</span> |
| <span class="n">ret</span> <span class="o">+=</span> <span class="p">[]</span> |
| <span class="k">elif</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span> <span class="o">==</span> <span class="mi">5</span><span class="p">:</span> |
| <span class="k">pass</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">AssertionError</span><span class="p">(</span><span class="s2">"infer_storage_type_backward must return 4 or 5 lists"</span><span class="p">)</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">tensors</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> \ |
| <span class="s2">"InferStorageTypeBackward Error: expecting == </span><span class="si">%d</span><span class="s2"> "</span> \ |
| <span class="s2">"entries in returned output gradient "</span> \ |
| <span class="s2">"stypes, got </span><span class="si">%d</span><span class="s2">."</span><span class="o">%</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">tensors</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">[</span><span class="mi">0</span><span class="p">]))</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">tensors</span><span class="p">[</span><span class="mi">1</span><span class="p">]),</span> \ |
| <span class="s2">"InferStorageTypeBackward Error: expecting == </span><span class="si">%d</span><span class="s2"> "</span> \ |
| <span class="s2">"entries in returned input stypes, "</span> \ |
| <span class="s2">"got </span><span class="si">%d</span><span class="s2">."</span><span class="o">%</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">tensors</span><span class="p">[</span><span class="mi">1</span><span class="p">]),</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">[</span><span class="mi">1</span><span class="p">]))</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">[</span><span class="mi">2</span><span class="p">])</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">tensors</span><span class="p">[</span><span class="mi">2</span><span class="p">]),</span> \ |
| <span class="s2">"InferStorageTypeBackward Error: expecting == </span><span class="si">%d</span><span class="s2"> "</span> \ |
| <span class="s2">"entries in returned output stypes, "</span> \ |
| <span class="s2">"got </span><span class="si">%d</span><span class="s2">."</span><span class="o">%</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">tensors</span><span class="p">[</span><span class="mi">2</span><span class="p">]),</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">[</span><span class="mi">2</span><span class="p">]))</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">[</span><span class="mi">3</span><span class="p">])</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">tensors</span><span class="p">[</span><span class="mi">3</span><span class="p">]),</span> \ |
| <span class="s2">"InferStorageTypeBackward Error: expecting == </span><span class="si">%d</span><span class="s2"> "</span> \ |
| <span class="s2">"entries in returned input gradient stypes, "</span> \ |
| <span class="s2">"got </span><span class="si">%d</span><span class="s2">."</span><span class="o">%</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">tensors</span><span class="p">[</span><span class="mi">3</span><span class="p">]),</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">[</span><span class="mi">3</span><span class="p">]))</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">tensors</span><span class="p">[</span><span class="mi">4</span><span class="p">]),</span> \ |
| <span class="s2">"InferStorageTypeBackward Error: expecting == </span><span class="si">%d</span><span class="s2"> "</span> \ |
| <span class="s2">"entries in returned aux stypes, "</span> \ |
| <span class="s2">"got </span><span class="si">%d</span><span class="s2">."</span><span class="o">%</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">tensors</span><span class="p">[</span><span class="mi">4</span><span class="p">]),</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">[</span><span class="mi">4</span><span class="p">]))</span> |
| <span class="n">rstype</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">ret_list</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">ret</span><span class="p">):</span> |
| <span class="n">rstype</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">ret_list</span><span class="p">)</span> |
| |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">stype</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">rstype</span><span class="p">):</span> |
| <span class="k">assert</span> <span class="n">stype</span> <span class="o">!=</span> <span class="n">_STORAGE_TYPE_ID_TO_STR</span><span class="p">[</span><span class="n">_STORAGE_TYPE_UNDEFINED</span><span class="p">],</span> \ |
| <span class="s2">"stype should not be undefined"</span> |
| <span class="k">assert</span> <span class="n">stype</span> <span class="ow">in</span> <span class="n">_STORAGE_TYPE_STR_TO_ID</span><span class="p">,</span> \ |
| <span class="s2">"Provided stype: </span><span class="si">%s</span><span class="s2"> is not valid "</span> \ |
| <span class="s2">"valid stypes are </span><span class="si">%s</span><span class="s2">, </span><span class="si">%s</span><span class="s2">, </span><span class="si">%s</span><span class="s2">"</span><span class="o">%</span><span class="p">(</span><span class="n">stype</span><span class="p">,</span> |
| <span class="n">_STORAGE_TYPE_ID_TO_STR</span><span class="p">[</span><span class="n">_STORAGE_TYPE_DEFAULT</span><span class="p">],</span> |
| <span class="n">_STORAGE_TYPE_ID_TO_STR</span><span class="p">[</span><span class="n">_STORAGE_TYPE_ROW_SPARSE</span><span class="p">],</span> |
| <span class="n">_STORAGE_TYPE_ID_TO_STR</span><span class="p">[</span><span class="n">_STORAGE_TYPE_CSR</span><span class="p">])</span> |
| <span class="n">tensor_stypes</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">_STORAGE_TYPE_STR_TO_ID</span><span class="p">[</span><span class="n">stype</span><span class="p">]</span> |
| |
| <span class="n">infer_storage_type_backward_entry</span><span class="o">.</span><span class="n">_ref_holder</span> <span class="o">=</span> <span class="p">[</span><span class="n">tensor_stypes</span><span class="p">]</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in </span><span class="si">%s</span><span class="s1">.infer_type: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">reg_name</span><span class="p">,</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">()))</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="k">def</span> <span class="nf">infer_storage_type_entry</span><span class="p">(</span><span class="n">num_tensor</span><span class="p">,</span> <span class="n">tensor_stypes</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for CustomOpProp::InferStorageType"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">n_in</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">op_prop</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">())</span> |
| <span class="n">n_out</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">op_prop</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">())</span> |
| <span class="n">n_aux</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">op_prop</span><span class="o">.</span><span class="n">list_auxiliary_states</span><span class="p">())</span> |
| <span class="k">assert</span> <span class="n">num_tensor</span> <span class="o">==</span> <span class="n">n_in</span> <span class="o">+</span> <span class="n">n_out</span> <span class="o">+</span> <span class="n">n_aux</span> |
| |
| <span class="n">stypes</span> <span class="o">=</span> <span class="p">[</span><span class="n">_STORAGE_TYPE_ID_TO_STR</span><span class="p">[</span><span class="n">tensor_stypes</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_in</span><span class="p">)]</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">op_prop</span><span class="o">.</span><span class="n">infer_storage_type</span><span class="p">(</span><span class="n">stypes</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span> |
| <span class="n">istype</span><span class="p">,</span> <span class="n">ostype</span> <span class="o">=</span> <span class="n">ret</span> |
| <span class="n">astype</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">elif</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span> <span class="o">==</span> <span class="mi">3</span><span class="p">:</span> |
| <span class="n">istype</span><span class="p">,</span> <span class="n">ostype</span><span class="p">,</span> <span class="n">astype</span> <span class="o">=</span> <span class="n">ret</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">AssertionError</span><span class="p">(</span><span class="s2">"infer_storage_type must return 2 or 3 lists"</span><span class="p">)</span> |
| |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">ostype</span><span class="p">)</span> <span class="o">==</span> <span class="n">n_out</span><span class="p">,</span> \ |
| <span class="s2">"InferStorageType Error: expecting </span><span class="si">%d</span><span class="s2"> entries in returned output "</span> \ |
| <span class="s2">"stypes, got </span><span class="si">%d</span><span class="s2">."</span><span class="o">%</span><span class="p">(</span><span class="n">n_out</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">ostype</span><span class="p">))</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">istype</span><span class="p">)</span> <span class="o">==</span> <span class="n">n_in</span><span class="p">,</span> \ |
| <span class="s2">"InferStorageType Error: expecting </span><span class="si">%d</span><span class="s2"> entries in returned input "</span> \ |
| <span class="s2">"stypes, got </span><span class="si">%d</span><span class="s2">."</span><span class="o">%</span><span class="p">(</span><span class="n">n_in</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">istype</span><span class="p">))</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">astype</span><span class="p">)</span> <span class="o">==</span> <span class="n">n_aux</span><span class="p">,</span> \ |
| <span class="s2">"InferStorageType Error: expecting </span><span class="si">%d</span><span class="s2"> entries in returned aux state "</span> \ |
| <span class="s2">"stypes, got </span><span class="si">%d</span><span class="s2">."</span><span class="o">%</span><span class="p">(</span><span class="n">n_aux</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">astype</span><span class="p">))</span> |
| <span class="n">rtype</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">istype</span><span class="p">)</span> <span class="o">+</span> <span class="nb">list</span><span class="p">(</span><span class="n">ostype</span><span class="p">)</span> <span class="o">+</span> <span class="nb">list</span><span class="p">(</span><span class="n">astype</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">dtype</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">rtype</span><span class="p">):</span> |
| <span class="n">tensor_stypes</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">_STORAGE_TYPE_STR_TO_ID</span><span class="p">[</span><span class="n">dtype</span><span class="p">]</span> |
| <span class="n">infer_storage_type_entry</span><span class="o">.</span><span class="n">_ref_holder</span> <span class="o">=</span> <span class="p">[</span><span class="n">tensor_stypes</span><span class="p">]</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in </span><span class="si">%s</span><span class="s1">.infer_type: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">reg_name</span><span class="p">,</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">()))</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="k">def</span> <span class="nf">infer_type_entry</span><span class="p">(</span><span class="n">num_tensor</span><span class="p">,</span> <span class="n">tensor_types</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for CustomOpProp::InferType"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">n_in</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">op_prop</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">())</span> |
| <span class="n">n_out</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">op_prop</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">())</span> |
| <span class="n">n_aux</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">op_prop</span><span class="o">.</span><span class="n">list_auxiliary_states</span><span class="p">())</span> |
| <span class="k">assert</span> <span class="n">num_tensor</span> <span class="o">==</span> <span class="n">n_in</span> <span class="o">+</span> <span class="n">n_out</span> <span class="o">+</span> <span class="n">n_aux</span> |
| |
| <span class="n">types</span> <span class="o">=</span> <span class="p">[</span><span class="n">_DTYPE_MX_TO_NP</span><span class="p">[</span><span class="n">tensor_types</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_in</span><span class="p">)]</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">op_prop</span><span class="o">.</span><span class="n">infer_type</span><span class="p">(</span><span class="n">types</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span> |
| <span class="n">itype</span><span class="p">,</span> <span class="n">otype</span> <span class="o">=</span> <span class="n">ret</span> |
| <span class="n">atype</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">elif</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span> <span class="o">==</span> <span class="mi">3</span><span class="p">:</span> |
| <span class="n">itype</span><span class="p">,</span> <span class="n">otype</span><span class="p">,</span> <span class="n">atype</span> <span class="o">=</span> <span class="n">ret</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">AssertionError</span><span class="p">(</span><span class="s2">"infer_type must return 2 or 3 lists"</span><span class="p">)</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">otype</span><span class="p">)</span> <span class="o">==</span> <span class="n">n_out</span><span class="p">,</span> \ |
| <span class="s2">"InferType Error: expecting </span><span class="si">%d</span><span class="s2"> entries in returned output "</span> \ |
| <span class="s2">"types, got </span><span class="si">%d</span><span class="s2">."</span><span class="o">%</span><span class="p">(</span><span class="n">n_out</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">otype</span><span class="p">))</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">itype</span><span class="p">)</span> <span class="o">==</span> <span class="n">n_in</span><span class="p">,</span> \ |
| <span class="s2">"InferType Error: expecting </span><span class="si">%d</span><span class="s2"> entries in returned input "</span> \ |
| <span class="s2">"types, got </span><span class="si">%d</span><span class="s2">."</span><span class="o">%</span><span class="p">(</span><span class="n">n_in</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">itype</span><span class="p">))</span> |
| <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">atype</span><span class="p">)</span> <span class="o">==</span> <span class="n">n_aux</span><span class="p">,</span> \ |
| <span class="s2">"InferType Error: expecting </span><span class="si">%d</span><span class="s2"> entries in returned aux state "</span> \ |
| <span class="s2">"types, got </span><span class="si">%d</span><span class="s2">."</span><span class="o">%</span><span class="p">(</span><span class="n">n_aux</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">atype</span><span class="p">))</span> |
| <span class="n">rtype</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">itype</span><span class="p">)</span> <span class="o">+</span> <span class="nb">list</span><span class="p">(</span><span class="n">otype</span><span class="p">)</span> <span class="o">+</span> <span class="nb">list</span><span class="p">(</span><span class="n">atype</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">dtype</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">rtype</span><span class="p">):</span> |
| <span class="n">tensor_types</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">_DTYPE_NP_TO_MX</span><span class="p">[</span><span class="n">dtype</span><span class="p">]</span> |
| |
| <span class="n">infer_type_entry</span><span class="o">.</span><span class="n">_ref_holder</span> <span class="o">=</span> <span class="p">[</span><span class="n">tensor_types</span><span class="p">]</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in </span><span class="si">%s</span><span class="s1">.infer_type: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">reg_name</span><span class="p">,</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">()))</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="k">def</span> <span class="nf">list_outputs_entry</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for CustomOpProp::ListOutputs"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">op_prop</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">()</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="p">[</span><span class="n">c_str</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">ret</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="n">c_char_p</span><span class="p">(</span><span class="mi">0</span><span class="p">)]</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">c_array</span><span class="p">(</span><span class="n">c_char_p</span><span class="p">,</span> <span class="n">ret</span><span class="p">)</span> |
| <span class="n">out</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">ret</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">c_char</span><span class="p">)))</span> |
| |
| <span class="n">list_outputs_entry</span><span class="o">.</span><span class="n">_ref_holder</span> <span class="o">=</span> <span class="p">[</span><span class="n">out</span><span class="p">]</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in </span><span class="si">%s</span><span class="s1">.list_outputs: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">reg_name</span><span class="p">,</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">()))</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="k">def</span> <span class="nf">list_arguments_entry</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for CustomOpProp::ListArguments"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">op_prop</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">()</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="p">[</span><span class="n">c_str</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">ret</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="n">c_char_p</span><span class="p">(</span><span class="mi">0</span><span class="p">)]</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">c_array</span><span class="p">(</span><span class="n">c_char_p</span><span class="p">,</span> <span class="n">ret</span><span class="p">)</span> |
| <span class="n">out</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">ret</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">c_char</span><span class="p">)))</span> |
| |
| <span class="n">list_arguments_entry</span><span class="o">.</span><span class="n">_ref_holder</span> <span class="o">=</span> <span class="p">[</span><span class="n">out</span><span class="p">]</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in </span><span class="si">%s</span><span class="s1">.list_arguments: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">reg_name</span><span class="p">,</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">()))</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="k">def</span> <span class="nf">list_auxiliary_states_entry</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for CustomOpProp::ListAuxiliaryStates"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">op_prop</span><span class="o">.</span><span class="n">list_auxiliary_states</span><span class="p">()</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="p">[</span><span class="n">c_str</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">ret</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="n">c_char_p</span><span class="p">(</span><span class="mi">0</span><span class="p">)]</span> |
| <span class="n">ret</span> <span class="o">=</span> <span class="n">c_array</span><span class="p">(</span><span class="n">c_char_p</span><span class="p">,</span> <span class="n">ret</span><span class="p">)</span> |
| <span class="n">out</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">ret</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">POINTER</span><span class="p">(</span><span class="n">c_char</span><span class="p">)))</span> |
| |
| <span class="n">list_auxiliary_states_entry</span><span class="o">.</span><span class="n">_ref_holder</span> <span class="o">=</span> <span class="p">[</span><span class="n">out</span><span class="p">]</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="n">tb</span> <span class="o">=</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">()</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in </span><span class="si">%s</span><span class="s1">.list_auxiliary_states: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">reg_name</span><span class="p">,</span> <span class="n">tb</span><span class="p">))</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="k">def</span> <span class="nf">declare_backward_dependency_entry</span><span class="p">(</span><span class="n">out_grad</span><span class="p">,</span> <span class="n">in_data</span><span class="p">,</span> <span class="n">out_data</span><span class="p">,</span> <span class="n">num_dep</span><span class="p">,</span> <span class="n">deps</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for CustomOpProp::DeclareBacwardDependency"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">out_grad</span> <span class="o">=</span> <span class="p">[</span><span class="n">out_grad</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">op_prop</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">()))]</span> |
| <span class="n">in_data</span> <span class="o">=</span> <span class="p">[</span><span class="n">in_data</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">op_prop</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">()))]</span> |
| <span class="n">out_data</span> <span class="o">=</span> <span class="p">[</span><span class="n">out_data</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">op_prop</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">()))]</span> |
| <span class="n">rdeps</span> <span class="o">=</span> <span class="n">op_prop</span><span class="o">.</span><span class="n">declare_backward_dependency</span><span class="p">(</span><span class="n">out_grad</span><span class="p">,</span> <span class="n">in_data</span><span class="p">,</span> <span class="n">out_data</span><span class="p">)</span> |
| <span class="n">num_dep</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">rdeps</span><span class="p">)</span> |
| <span class="n">_registry</span><span class="o">.</span><span class="n">result_deps</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span> |
| <span class="k">for</span> <span class="n">dep</span> <span class="ow">in</span> <span class="n">rdeps</span><span class="p">:</span> |
| <span class="n">_registry</span><span class="o">.</span><span class="n">result_deps</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">dep</span><span class="p">)</span> |
| <span class="n">rdeps</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">c_array_buf</span><span class="p">(</span><span class="n">c_int</span><span class="p">,</span> <span class="n">array</span><span class="p">(</span><span class="s1">'i'</span><span class="p">,</span> <span class="n">rdeps</span><span class="p">)),</span> <span class="n">c_int_p</span><span class="p">)</span> |
| <span class="n">deps</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">rdeps</span> |
| |
| <span class="n">declare_backward_dependency_entry</span><span class="o">.</span><span class="n">_ref_holder</span> <span class="o">=</span> <span class="p">[</span><span class="n">deps</span><span class="p">]</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="n">tb</span> <span class="o">=</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">()</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in </span><span class="si">%s</span><span class="s1">.declare_backward_dependency: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">reg_name</span><span class="p">,</span> <span class="n">tb</span><span class="p">))</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="k">def</span> <span class="nf">create_operator_entry</span><span class="p">(</span><span class="n">ctx</span><span class="p">,</span> <span class="n">num_inputs</span><span class="p">,</span> <span class="n">shapes</span><span class="p">,</span> <span class="n">ndims</span><span class="p">,</span> <span class="n">dtypes</span><span class="p">,</span> <span class="n">ret</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for CustomOpProp::CreateOperator"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">ctx</span> <span class="o">=</span> <span class="n">py_str</span><span class="p">(</span><span class="n">ctx</span><span class="p">)</span> |
| <span class="n">sep</span> <span class="o">=</span> <span class="n">ctx</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">'('</span><span class="p">)</span> |
| <span class="n">ctx</span> <span class="o">=</span> <span class="n">context</span><span class="o">.</span><span class="n">Context</span><span class="p">(</span><span class="n">ctx</span><span class="p">[:</span><span class="n">sep</span><span class="p">],</span> <span class="nb">int</span><span class="p">(</span><span class="n">ctx</span><span class="p">[</span><span class="n">sep</span><span class="o">+</span><span class="mi">1</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">]))</span> |
| <span class="n">ndims</span> <span class="o">=</span> <span class="p">[</span><span class="n">ndims</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_inputs</span><span class="p">)]</span> |
| <span class="n">shapes</span> <span class="o">=</span> <span class="p">[[</span><span class="n">shapes</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="n">j</span><span class="p">]</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">ndims</span><span class="p">[</span><span class="n">i</span><span class="p">])]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_inputs</span><span class="p">)]</span> |
| <span class="n">dtypes</span> <span class="o">=</span> <span class="p">[</span><span class="n">dtypes</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_inputs</span><span class="p">)]</span> |
| <span class="n">op</span> <span class="o">=</span> <span class="n">op_prop</span><span class="o">.</span><span class="n">create_operator</span><span class="p">(</span><span class="n">ctx</span><span class="p">,</span> <span class="n">shapes</span><span class="p">,</span> <span class="n">dtypes</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">forward_entry</span><span class="p">(</span><span class="n">num_ndarray</span><span class="p">,</span> <span class="n">ndarraies</span><span class="p">,</span> <span class="n">tags</span><span class="p">,</span> <span class="n">reqs</span><span class="p">,</span> <span class="n">is_train</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for CustomOp::Forward"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">tensors</span> <span class="o">=</span> <span class="p">[[]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">)]</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_ndarray</span><span class="p">):</span> |
| <span class="k">if</span> <span class="n">tags</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span> <span class="ow">or</span> <span class="n">tags</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">4</span><span class="p">:</span> |
| <span class="n">tensors</span><span class="p">[</span><span class="n">tags</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span> |
| <span class="n">create_ndarray_fn</span><span class="p">(</span><span class="n">cast</span><span class="p">(</span><span class="n">ndarraies</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">NDArrayHandle</span><span class="p">),</span> <span class="n">writable</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> |
| <span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">tensors</span><span class="p">[</span><span class="n">tags</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span> |
| <span class="n">create_ndarray_fn</span><span class="p">(</span><span class="n">cast</span><span class="p">(</span><span class="n">ndarraies</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">NDArrayHandle</span><span class="p">),</span> <span class="n">writable</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> |
| <span class="p">)</span> |
| <span class="n">reqs</span> <span class="o">=</span> <span class="p">[</span><span class="n">req_enum</span><span class="p">[</span><span class="n">reqs</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">tensors</span><span class="p">[</span><span class="mi">1</span><span class="p">]))]</span> |
| <span class="k">with</span> <span class="n">ctx</span><span class="p">:</span> |
| <span class="n">op</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="n">is_train</span><span class="o">=</span><span class="n">is_train</span><span class="p">,</span> <span class="n">req</span><span class="o">=</span><span class="n">reqs</span><span class="p">,</span> |
| <span class="n">in_data</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">out_data</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> |
| <span class="n">aux</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in CustomOp.forward: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">())</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="k">def</span> <span class="nf">backward_entry</span><span class="p">(</span><span class="n">num_ndarray</span><span class="p">,</span> <span class="n">ndarraies</span><span class="p">,</span> <span class="n">tags</span><span class="p">,</span> <span class="n">reqs</span><span class="p">,</span> <span class="n">is_train</span><span class="p">,</span> <span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for CustomOp::Backward"""</span> |
| <span class="c1"># pylint: disable=W0613</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">tensors</span> <span class="o">=</span> <span class="p">[[]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">)]</span> |
| <span class="n">num_outputs</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">op_prop</span><span class="o">.</span><span class="n">list_outputs</span><span class="p">())</span> |
| <span class="n">num_args</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">op_prop</span><span class="o">.</span><span class="n">list_arguments</span><span class="p">())</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_ndarray</span><span class="p">):</span> |
| <span class="k">if</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">_registry</span><span class="o">.</span><span class="n">result_deps</span> <span class="ow">or</span> <span class="n">i</span> <span class="o">>=</span> <span class="p">(</span><span class="n">num_outputs</span> <span class="o">*</span> <span class="mi">2</span> <span class="o">+</span> <span class="n">num_args</span><span class="p">):</span> |
| <span class="c1"># If it is a backward dependency or output or aux:</span> |
| <span class="c1"># Set stype as undefined so that it returns</span> |
| <span class="c1"># ndarray based on existing stype</span> |
| <span class="n">stype</span> <span class="o">=</span> <span class="n">_STORAGE_TYPE_UNDEFINED</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="c1"># If it is some input, output or out grad ndarray not part of</span> |
| <span class="c1"># backward dependency it is empty and thus the ndarray should</span> |
| <span class="c1"># be set to default</span> |
| <span class="n">stype</span> <span class="o">=</span> <span class="n">_STORAGE_TYPE_DEFAULT</span> |
| <span class="k">if</span> <span class="n">tags</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">2</span> <span class="ow">or</span> <span class="n">tags</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">4</span><span class="p">:</span> |
| <span class="n">tensors</span><span class="p">[</span><span class="n">tags</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span> |
| <span class="n">create_ndarray_fn</span><span class="p">(</span><span class="n">cast</span><span class="p">(</span><span class="n">ndarraies</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">NDArrayHandle</span><span class="p">),</span> |
| <span class="n">writable</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">stype</span><span class="o">=</span><span class="n">stype</span><span class="p">)</span> |
| <span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">tensors</span><span class="p">[</span><span class="n">tags</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span> |
| <span class="n">create_ndarray_fn</span><span class="p">(</span><span class="n">cast</span><span class="p">(</span><span class="n">ndarraies</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">NDArrayHandle</span><span class="p">),</span> |
| <span class="n">writable</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">stype</span><span class="o">=</span><span class="n">stype</span><span class="p">)</span> |
| <span class="p">)</span> |
| <span class="n">reqs</span> <span class="o">=</span> <span class="p">[</span><span class="n">req_enum</span><span class="p">[</span><span class="n">reqs</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">tensors</span><span class="p">[</span><span class="mi">2</span><span class="p">]))]</span> |
| <span class="k">with</span> <span class="n">ctx</span><span class="p">:</span> |
| <span class="n">op</span><span class="o">.</span><span class="n">backward</span><span class="p">(</span><span class="n">req</span><span class="o">=</span><span class="n">reqs</span><span class="p">,</span> |
| <span class="n">in_data</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">out_data</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> |
| <span class="n">in_grad</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">out_grad</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> |
| <span class="n">aux</span><span class="o">=</span><span class="n">tensors</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in CustomOp.backward: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">())</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="n">cur</span> <span class="o">=</span> <span class="n">_registry</span><span class="o">.</span><span class="n">inc</span><span class="p">()</span> |
| |
| <span class="k">def</span> <span class="nf">delete_entry</span><span class="p">(</span><span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for CustomOp::del"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="k">del</span> <span class="n">_registry</span><span class="o">.</span><span class="n">ref_holder</span><span class="p">[</span><span class="n">cur</span><span class="p">]</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in CustomOp.delete: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">())</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="n">callbacks</span> <span class="o">=</span> <span class="p">[</span><span class="n">del_functype</span><span class="p">(</span><span class="n">delete_entry</span><span class="p">),</span> |
| <span class="n">fb_functype</span><span class="p">(</span><span class="n">forward_entry</span><span class="p">),</span> |
| <span class="n">fb_functype</span><span class="p">(</span><span class="n">backward_entry</span><span class="p">)]</span> |
| <span class="n">callbacks</span> <span class="o">=</span> <span class="p">[</span><span class="n">cast</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">))</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">callbacks</span><span class="p">]</span> |
| <span class="n">contexts</span> <span class="o">=</span> <span class="p">[</span><span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">]</span> |
| <span class="n">ret</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">MXCallbackList</span><span class="p">(</span><span class="n">c_int</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">callbacks</span><span class="p">)),</span> |
| <span class="n">cast</span><span class="p">(</span><span class="n">c_array</span><span class="p">(</span><span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> <span class="n">callbacks</span><span class="p">),</span> |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">))),</span> |
| <span class="n">cast</span><span class="p">(</span><span class="n">c_array</span><span class="p">(</span><span class="n">c_void_p</span><span class="p">,</span> <span class="n">contexts</span><span class="p">),</span> |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">c_void_p</span><span class="p">)))</span> |
| <span class="n">op</span><span class="o">.</span><span class="n">_ref_holder</span> <span class="o">=</span> <span class="p">[</span><span class="n">ret</span><span class="p">]</span> |
| <span class="n">_registry</span><span class="o">.</span><span class="n">ref_holder</span><span class="p">[</span><span class="n">cur</span><span class="p">]</span> <span class="o">=</span> <span class="n">op</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in </span><span class="si">%s</span><span class="s1">.create_operator: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">reg_name</span><span class="p">,</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">()))</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="n">cur</span> <span class="o">=</span> <span class="n">_registry</span><span class="o">.</span><span class="n">inc</span><span class="p">()</span> |
| |
| <span class="k">def</span> <span class="nf">delete_entry</span><span class="p">(</span><span class="n">_</span><span class="p">):</span> |
| <span class="sd">"""C Callback for CustomOpProp::del"""</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="k">del</span> <span class="n">_registry</span><span class="o">.</span><span class="n">ref_holder</span><span class="p">[</span><span class="n">cur</span><span class="p">]</span> |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="s1">'Error in CustomOpProp.delete: </span><span class="si">%s</span><span class="s1">'</span> <span class="o">%</span> <span class="n">traceback</span><span class="o">.</span><span class="n">format_exc</span><span class="p">())</span> |
| <span class="k">return</span> <span class="kc">False</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="n">callbacks</span> <span class="o">=</span> <span class="p">[</span><span class="n">del_functype</span><span class="p">(</span><span class="n">delete_entry</span><span class="p">),</span> |
| <span class="n">list_functype</span><span class="p">(</span><span class="n">list_arguments_entry</span><span class="p">),</span> |
| <span class="n">list_functype</span><span class="p">(</span><span class="n">list_outputs_entry</span><span class="p">),</span> |
| <span class="n">list_functype</span><span class="p">(</span><span class="n">list_auxiliary_states_entry</span><span class="p">),</span> |
| <span class="n">infershape_functype</span><span class="p">(</span><span class="n">infer_shape_entry</span><span class="p">),</span> |
| <span class="n">deps_functype</span><span class="p">(</span><span class="n">declare_backward_dependency_entry</span><span class="p">),</span> |
| <span class="n">createop_functype</span><span class="p">(</span><span class="n">create_operator_entry</span><span class="p">),</span> |
| <span class="n">infertype_functype</span><span class="p">(</span><span class="n">infer_type_entry</span><span class="p">),</span> |
| <span class="n">inferstorage_functype</span><span class="p">(</span><span class="n">infer_storage_type_entry</span><span class="p">),</span> |
| <span class="n">inferstorage_backward_functype</span><span class="p">(</span><span class="n">infer_storage_type_backward_entry</span><span class="p">)]</span> |
| <span class="n">callbacks</span> <span class="o">=</span> <span class="p">[</span><span class="n">cast</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">))</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">callbacks</span><span class="p">]</span> |
| <span class="n">contexts</span> <span class="o">=</span> <span class="p">[</span><span class="kc">None</span><span class="p">]</span><span class="o">*</span><span class="nb">len</span><span class="p">(</span><span class="n">callbacks</span><span class="p">)</span> |
| <span class="n">ret</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">MXCallbackList</span><span class="p">(</span><span class="n">c_int</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">callbacks</span><span class="p">)),</span> |
| <span class="n">cast</span><span class="p">(</span><span class="n">c_array</span><span class="p">(</span><span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">),</span> <span class="n">callbacks</span><span class="p">),</span> |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">))),</span> |
| <span class="n">cast</span><span class="p">(</span><span class="n">c_array</span><span class="p">(</span><span class="n">c_void_p</span><span class="p">,</span> <span class="n">contexts</span><span class="p">),</span> |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">c_void_p</span><span class="p">)))</span> |
| <span class="n">op_prop</span><span class="o">.</span><span class="n">_ref_holder</span> <span class="o">=</span> <span class="p">[</span><span class="n">ret</span><span class="p">]</span> |
| <span class="n">_registry</span><span class="o">.</span><span class="n">ref_holder</span><span class="p">[</span><span class="n">cur</span><span class="p">]</span> <span class="o">=</span> <span class="n">op_prop</span> |
| <span class="k">return</span> <span class="kc">True</span> |
| |
| <span class="n">creator_functype</span> <span class="o">=</span> <span class="n">CFUNCTYPE</span><span class="p">(</span><span class="n">c_int</span><span class="p">,</span> <span class="n">c_char_p</span><span class="p">,</span> <span class="n">c_int</span><span class="p">,</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">c_char_p</span><span class="p">),</span> |
| <span class="n">POINTER</span><span class="p">(</span><span class="n">c_char_p</span><span class="p">),</span> <span class="n">POINTER</span><span class="p">(</span><span class="n">MXCallbackList</span><span class="p">))</span> |
| <span class="n">creator_func</span> <span class="o">=</span> <span class="n">creator_functype</span><span class="p">(</span><span class="n">creator</span><span class="p">)</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXCustomOpRegister</span><span class="p">(</span><span class="n">c_str</span><span class="p">(</span><span class="n">reg_name</span><span class="p">),</span> <span class="n">creator_func</span><span class="p">))</span> |
| <span class="n">cur</span> <span class="o">=</span> <span class="n">_registry</span><span class="o">.</span><span class="n">inc</span><span class="p">()</span> |
| <span class="n">_registry</span><span class="o">.</span><span class="n">ref_holder</span><span class="p">[</span><span class="n">cur</span><span class="p">]</span> <span class="o">=</span> <span class="n">creator_func</span> |
| <span class="k">return</span> <span class="n">prop_cls</span> |
| <span class="k">return</span> <span class="n">do_register</span></div> |
| |
| |
| <span class="n">register</span><span class="p">(</span><span class="s2">"custom_op"</span><span class="p">)(</span><span class="n">CustomOpProp</span><span class="p">)</span> |
| |
| |
| <div class="viewcode-block" id="get_all_registered_operators"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.get_all_registered_operators">[docs]</a><span class="k">def</span> <span class="nf">get_all_registered_operators</span><span class="p">():</span> |
| <span class="sd">"""Get all registered MXNet operator names.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> operator_names : list of string</span> |
| <span class="sd"> """</span> |
| <span class="n">plist</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">)()</span> |
| <span class="n">size</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_uint</span><span class="p">()</span> |
| |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXListAllOpNames</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">size</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">plist</span><span class="p">)))</span> |
| |
| <span class="n">mx_registered_operator_names</span> <span class="o">=</span> <span class="p">[</span><span class="n">py_str</span><span class="p">(</span><span class="n">plist</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">size</span><span class="o">.</span><span class="n">value</span><span class="p">)]</span> |
| <span class="k">return</span> <span class="n">mx_registered_operator_names</span></div> |
| |
| |
| <span class="n">OperatorArguments</span> <span class="o">=</span> <span class="n">collections</span><span class="o">.</span><span class="n">namedtuple</span><span class="p">(</span><span class="s1">'OperatorArguments'</span><span class="p">,</span> <span class="p">[</span><span class="s1">'narg'</span><span class="p">,</span> <span class="s1">'names'</span><span class="p">,</span> <span class="s1">'types'</span><span class="p">])</span> |
| |
| |
| <div class="viewcode-block" id="get_operator_arguments"><a class="viewcode-back" href="../../api/mxnet/operator/index.html#mxnet.operator.get_operator_arguments">[docs]</a><span class="k">def</span> <span class="nf">get_operator_arguments</span><span class="p">(</span><span class="n">op_name</span><span class="p">):</span> |
| <span class="sd">"""Given operator name, fetch operator arguments - number of arguments,</span> |
| <span class="sd"> argument names, argument types.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> op_name: str</span> |
| <span class="sd"> Handle for the operator</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> operator_arguments : OperatorArguments, namedtuple with number of arguments, names and types</span> |
| <span class="sd"> """</span> |
| <span class="n">op_handle</span> <span class="o">=</span> <span class="n">OpHandle</span><span class="p">()</span> |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">NNGetOpHandle</span><span class="p">(</span><span class="n">c_str</span><span class="p">(</span><span class="n">op_name</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">op_handle</span><span class="p">)))</span> |
| <span class="n">real_name</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">()</span> |
| <span class="n">desc</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">()</span> |
| <span class="n">num_args</span> <span class="o">=</span> <span class="n">mx_uint</span><span class="p">()</span> |
| <span class="n">arg_names</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">)()</span> |
| <span class="n">arg_types</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">)()</span> |
| <span class="n">arg_descs</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">POINTER</span><span class="p">(</span><span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">)()</span> |
| <span class="n">key_var_num_args</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">()</span> |
| <span class="n">ret_type</span> <span class="o">=</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">c_char_p</span><span class="p">()</span> |
| |
| <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXSymbolGetAtomicSymbolInfo</span><span class="p">(</span> |
| <span class="n">op_handle</span><span class="p">,</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">real_name</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">desc</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">num_args</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">arg_names</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">arg_types</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">arg_descs</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">key_var_num_args</span><span class="p">),</span> |
| <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">ret_type</span><span class="p">)))</span> |
| |
| <span class="n">narg</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">num_args</span><span class="o">.</span><span class="n">value</span><span class="p">)</span> |
| <span class="n">arg_names</span> <span class="o">=</span> <span class="p">[</span><span class="n">py_str</span><span class="p">(</span><span class="n">arg_names</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">narg</span><span class="p">)]</span> |
| <span class="n">arg_types</span> <span class="o">=</span> <span class="p">[</span><span class="n">py_str</span><span class="p">(</span><span class="n">arg_types</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">narg</span><span class="p">)]</span> |
| <span class="k">return</span> <span class="n">OperatorArguments</span><span class="p">(</span><span class="n">narg</span><span class="p">,</span> <span class="n">arg_names</span><span class="p">,</span> <span class="n">arg_types</span><span class="p">)</span></div> |
| </pre></div> |
| |
| <hr class="feedback-hr-top" /> |
| <div class="feedback-container"> |
| <div class="feedback-question">Did this page help you?</div> |
| <div class="feedback-answer-container"> |
| <div class="feedback-answer yes-link" data-response="yes">Yes</div> |
| <div class="feedback-answer no-link" data-response="no">No</div> |
| </div> |
| <div class="feedback-thank-you">Thanks for your feedback!</div> |
| </div> |
| <hr class="feedback-hr-bottom" /> |
| </div> |
| <div class="side-doc-outline"> |
| <div class="side-doc-outline--content"> |
| </div> |
| </div> |
| |
| <div class="clearer"></div> |
| </div><div class="pagenation"> |
| </div> |
| <footer class="site-footer h-card"> |
| <div class="wrapper"> |
| <div class="row"> |
| <div class="col-4"> |
| <h4 class="footer-category-title">Resources</h4> |
| <ul class="contact-list"> |
| <li><a class="u-email" href="mailto:dev@mxnet.apache.org">Dev list</a></li> |
| <li><a class="u-email" href="mailto:user@mxnet.apache.org">User mailing list</a></li> |
| <li><a href="https://cwiki.apache.org/confluence/display/MXNET/Apache+MXNet+Home">Developer Wiki</a></li> |
| <li><a href="https://issues.apache.org/jira/projects/MXNET/issues">Jira Tracker</a></li> |
| <li><a href="https://github.com/apache/incubator-mxnet/labels/Roadmap">Github Roadmap</a></li> |
| <li><a href="https://medium.com/apache-mxnet">Blog</a></li> |
| <li><a href="https://discuss.mxnet.io">Forum</a></li> |
| <li><a href="/community/contribute">Contribute</a></li> |
| |
| </ul> |
| </div> |
| |
| <div class="col-4"><ul class="social-media-list"><li><a href="https://github.com/apache/incubator-mxnet"><svg class="svg-icon"><use xlink:href="../../_static/minima-social-icons.svg#github"></use></svg> <span class="username">apache/incubator-mxnet</span></a></li><li><a href="https://www.twitter.com/apachemxnet"><svg class="svg-icon"><use xlink:href="../../_static/minima-social-icons.svg#twitter"></use></svg> <span class="username">apachemxnet</span></a></li><li><a href="https://youtube.com/apachemxnet"><svg class="svg-icon"><use xlink:href="../../_static/minima-social-icons.svg#youtube"></use></svg> <span class="username">apachemxnet</span></a></li></ul> |
| </div> |
| |
| <div class="col-4 footer-text"> |
| <p>A flexible and efficient library for deep learning.</p> |
| </div> |
| </div> |
| </div> |
| </footer> |
| |
| <footer class="site-footer2"> |
| <div class="wrapper"> |
| <div class="row"> |
| <div class="col-3"> |
| <img src="../../_static/apache_incubator_logo.png" class="footer-logo col-2"> |
| </div> |
| <div class="footer-bottom-warning col-9"> |
| <p>Apache MXNet is an effort undergoing incubation at <a href="http://www.apache.org/">The Apache Software Foundation</a> (ASF), <span style="font-weight:bold">sponsored by the <i>Apache Incubator</i></span>. Incubation is required |
| of all newly accepted projects until a further review indicates that the infrastructure, |
| communications, and decision making process have stabilized in a manner consistent with other |
| successful ASF projects. While incubation status is not necessarily a reflection of the completeness |
| or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF. |
| </p><p>"Copyright © 2017-2018, The Apache Software Foundation Apache MXNet, MXNet, Apache, the Apache |
| feather, and the Apache MXNet project logo are either registered trademarks or trademarks of the |
| Apache Software Foundation."</p> |
| </div> |
| </div> |
| </div> |
| </footer> |
| |
| </body> |
| </html> |
