├── .ci └── docker │ ├── Dockerfile │ ├── build.sh │ ├── common │ ├── install_base.sh │ ├── install_docs_reqs.sh │ ├── install_pip_requirements.sh │ └── install_user.sh │ └── requirements.txt ├── .devcontainer ├── Dockerfile ├── devcontainer.json └── requirements.txt ├── .github ├── ISSUE_TEMPLATE │ ├── bug-report.yml │ └── feature-request.yml ├── PULL_REQUEST_TEMPLATE.md ├── pytorch-probot.yml ├── scripts │ ├── check_redirects.sh │ └── docathon-label-sync.py └── workflows │ ├── MonthlyLinkCheck.yml │ ├── StalePRs.yml │ ├── build-tutorials.yml │ ├── check-redirects.yml │ ├── docathon-assign.yml │ ├── docathon-label-sync.yml │ ├── docker-build.yml │ ├── link_checkPR.yml │ └── spelling.yml ├── .gitignore ├── .gitmodules ├── .jenkins ├── build.sh ├── custom_pandoc_filter.py ├── delete_html_file_with_runnable_code_removed.py ├── download_data.py ├── get_docker_tag.py ├── get_files_to_run.py ├── get_sphinx_filenames.py ├── insert_last_verified.py ├── metadata.json ├── post_process_notebooks.py ├── remove_invisible_code_block_batch.sh ├── remove_invisible_code_block_from_html.py ├── remove_invisible_code_block_from_ipynb.py ├── remove_invisible_code_block_from_py.py ├── remove_invisible_code_block_from_rst_txt.py ├── remove_runnable_code.py ├── replace_tutorial_html_content.py ├── test_files_to_run.py └── validate_tutorials_built.py ├── .lycheeignore ├── .pyspelling.yml ├── CODE_OF_CONDUCT.md ├── CONTRIBUTING.md ├── LICENSE ├── Makefile ├── README.md ├── _static ├── ajax-loader.gif ├── basic.css ├── broken_example.png ├── comment-bright.png ├── comment-close.png ├── comment.png ├── css │ ├── custom.css │ ├── custom2.css │ └── pytorch_theme.css ├── doctools.js ├── documentation_options.js ├── down-pressed.png ├── down.png ├── file.png ├── fonts │ ├── FreightSans │ │ ├── freight-sans-light.woff │ │ ├── freight-sans-light.woff2 │ │ ├── freight-sans-regular.woff │ │ └── freight-sans-regular.woff2 │ └── IBMPlexMono │ │ ├── IBMPlexMono-Light.woff │ │ ├── IBMPlexMono-Light.woff2 │ │ ├── IBMPlexMono-Medium.woff │ │ ├── IBMPlexMono-Medium.woff2 │ │ ├── IBMPlexMono-Regular.woff │ │ ├── IBMPlexMono-Regular.woff2 │ │ ├── IBMPlexMono-SemiBold.woff │ │ └── IBMPlexMono-SemiBold.woff2 ├── gallery.css ├── imagenet_class_index.json ├── images │ ├── arrow-down-orange.svg │ ├── arrow-right-with-tail.svg │ ├── chevron-down-grey.svg │ ├── chevron-right-orange.svg │ ├── chevron-right-white.svg │ ├── home-footer-background.jpg │ ├── icon-close.svg │ ├── icon-menu-dots-dark.svg │ ├── logo-dark.svg │ ├── logo-facebook-dark.svg │ ├── logo-icon.svg │ ├── logo-twitter-dark.svg │ ├── logo.svg │ ├── microsoft-logo.svg │ └── view-page-source-icon.svg ├── img │ ├── 8_workers.png │ ├── ExecuTorch-Logo-cropped.svg │ ├── ONNXLive.png │ ├── SRResNet.png │ ├── Variable.png │ ├── audio_preprocessing_tutorial_waveform.png │ ├── autodiff.png │ ├── ax_logo.png │ ├── ax_scheduler_illustration.png │ ├── basics │ │ ├── comp-graph.png │ │ ├── fashion_mnist.png │ │ ├── optimizationloops.png │ │ └── typesdata.png │ ├── bert_mrpc.png │ ├── cartpole.gif │ ├── cat.jpg │ ├── cat_224x224.jpg │ ├── cat_resized.jpg │ ├── cat_superres_with_ort.jpg │ ├── channels_last_memory_format.png │ ├── char_rnn_generation.png │ ├── chat.png │ ├── chatbot │ │ ├── RNN-bidirectional.png │ │ ├── attn1.png │ │ ├── attn2.png │ │ ├── bot.png │ │ ├── diff.png │ │ ├── global_attn.png │ │ ├── grad_clip.png │ │ ├── pytorch_workflow.png │ │ ├── scores.png │ │ ├── seq2seq_batches.png │ │ └── seq2seq_ts.png │ ├── cifar10.png │ ├── classic_memory_format.png │ ├── compiled_autograd │ │ ├── call_hook_node.png │ │ ├── entire_verbose_log.png │ │ ├── recompile_due_to_dynamic.png │ │ └── recompile_due_to_node.png │ ├── cpp-frontend │ │ └── digits.png │ ├── cpp-pytorch.png │ ├── cpp_logo.png │ ├── dag_autograd.png │ ├── data_parallel.png │ ├── dcgan_generator.png │ ├── deeplabv3_android.png │ ├── deeplabv3_android2.png │ ├── deeplabv3_ios.png │ ├── deeplabv3_ios2.png │ ├── distributed │ │ ├── DDP_memory.gif │ │ ├── DistPyTorch.jpg │ │ ├── FSDP_autowrap.gif │ │ ├── FSDP_memory.gif │ │ ├── all_gather.pdf │ │ ├── all_gather.png │ │ ├── all_reduce.pdf │ │ ├── all_reduce.png │ │ ├── broadcast.png │ │ ├── device_mesh.png │ │ ├── distributed_checkpoint_generated_files.png │ │ ├── fsdp_implicit.png │ │ ├── fsdp_sharding.png │ │ ├── fsdp_tp.png │ │ ├── fsdp_workflow.png │ │ ├── gather.png │ │ ├── loss_parallel.png │ │ ├── megatron_lm.png │ │ ├── reduce.png │ │ ├── scatter.png │ │ ├── send_recv.png │ │ ├── send_recv_big.png │ │ ├── tcpstore_barrier_time.png │ │ └── tcpstore_init_time.png │ ├── dynamic_graph.gif │ ├── fgsm_panda_image.png │ ├── flask.png │ ├── half_cheetah.gif │ ├── hta │ │ ├── comm_across_ranks.png │ │ ├── counts_diff.png │ │ ├── cuda_kernel_launch.png │ │ ├── cuda_kernel_launch_stats.png │ │ ├── duration_diff.png │ │ ├── idle_time.png │ │ ├── idle_time_breakdown_percentage.png │ │ ├── idle_time_summary.png │ │ ├── kernel_metrics_df.png │ │ ├── kernel_type_breakdown.png │ │ ├── launch_delay_outliers.png │ │ ├── mem_bandwidth_queue_length.png │ │ ├── overlap_df.png │ │ ├── overlap_plot.png │ │ ├── pie_charts.png │ │ ├── queue_length_summary.png │ │ ├── runtime_outliers.png │ │ ├── short_gpu_kernels.png │ │ ├── temporal_breakdown_df.png │ │ └── temporal_breakdown_plot.png │ ├── hybrid_frontend │ │ ├── 220px-KnnClassification.png │ │ ├── iris_pic.jpg │ │ └── pytorch_workflow_small.jpg │ ├── install_msvc.png │ ├── invpendulum.gif │ ├── itt_tutorial │ │ ├── vtune_config.png │ │ ├── vtune_start.png │ │ ├── vtune_timeline.png │ │ ├── vtune_xpu_config.png │ │ └── vtune_xpu_timeline.png │ ├── knowledge_distillation │ │ ├── ce_only.png │ │ ├── cosine_embedding_loss.png │ │ ├── cosine_loss_distillation.png │ │ ├── distillation_output_loss.png │ │ └── fitnets_knowledge_distill.png │ ├── landmarked_face2.png │ ├── mario.gif │ ├── mario_env.png │ ├── memory_format_logo.png │ ├── mnist.png │ ├── model-parallel-images │ │ ├── mp_vs_rn.png │ │ ├── mp_vs_rn_vs_pp.png │ │ └── split_size_tradeoff.png │ ├── named_tensor.png │ ├── neural-style │ │ ├── dancing.jpg │ │ ├── neuralstyle.png │ │ ├── picasso.jpg │ │ ├── sphx_glr_neural_style_tutorial_001.png │ │ ├── sphx_glr_neural_style_tutorial_002.png │ │ ├── sphx_glr_neural_style_tutorial_003.png │ │ └── sphx_glr_neural_style_tutorial_004.png │ ├── nvfuser_intro │ │ ├── nvfuser_transformer_block.png │ │ ├── nvfuser_tutorial_0.png │ │ ├── nvfuser_tutorial_1.png │ │ ├── nvfuser_tutorial_2.png │ │ ├── nvfuser_tutorial_3.png │ │ ├── nvfuser_tutorial_4.png │ │ ├── nvfuser_tutorial_5.png │ │ └── nvfuser_tutorial_6.png │ ├── oneworker.png │ ├── onnx │ │ ├── image_classifier_onnx_model_on_netron_web_ui.png │ │ └── netron_web_ui.png │ ├── optim_step_in_bwd │ │ ├── snapshot.jpg │ │ └── snapshot_opt_in_bwd.jpg │ ├── panda.png │ ├── pendulum.gif │ ├── per_channel_quant.png │ ├── per_tensor_quant.png │ ├── perf_viz.png │ ├── pinmem │ │ ├── pinmem.png │ │ ├── trace_streamed0_pinned0.png │ │ ├── trace_streamed0_pinned1.png │ │ ├── trace_streamed1_pinned0.png │ │ └── trace_streamed1_pinned1.png │ ├── profiler_callstack.png │ ├── profiler_distributed_view.png │ ├── profiler_kernel_view.png │ ├── profiler_memory_curve_selecting.png │ ├── profiler_memory_curve_single.png │ ├── profiler_memory_view.png │ ├── profiler_operator_view.png │ ├── profiler_overview1.png │ ├── profiler_overview2.png │ ├── profiler_rocm_chrome_trace_view.png │ ├── profiler_rocm_tensorboard_operartor_view.png │ ├── profiler_trace_view1.png │ ├── profiler_trace_view2.png │ ├── profiler_trace_view_fwd_bwd.png │ ├── profiler_views_list.png │ ├── profiler_vscode.png │ ├── pruning.png │ ├── pruning_flow.jpg │ ├── python_extension_autoload_impl.png │ ├── pytorch-logo-dark.png │ ├── pytorch-logo-dark.svg │ ├── qat.png │ ├── quant_embeddings.png │ ├── ray-tune.png │ ├── reinforcement_learning_diagram.drawio │ ├── reinforcement_learning_diagram.jpg │ ├── replaybuffer_traj.png │ ├── rnnclass.png │ ├── rollout_recurrent.png │ ├── rpc-images │ │ └── batch.png │ ├── rpc_trace_img.png │ ├── sample_file.jpeg │ ├── scipynumpy.png │ ├── seq-seq-images │ │ ├── attention-decoder-network.dot │ │ ├── attention-decoder-network.png │ │ ├── decoder-network.dot │ │ ├── decoder-network.png │ │ ├── decoder.png │ │ ├── decoder@2x.png │ │ ├── encoder-network.dot │ │ ├── encoder-network.png │ │ ├── seq2seq.png │ │ ├── seq2seq@2x.png │ │ ├── word-encoding.png │ │ └── word-encoding@2x.png │ ├── seq2seq_flat.png │ ├── steam-train-whistle-daniel_simon-converted-from-mp3.wav │ ├── stn │ │ ├── FSeq.png │ │ ├── Five.gif │ │ ├── stn-arch.png │ │ └── tr.png │ ├── tensor_illustration.png │ ├── tensor_illustration_flat.png │ ├── tensorboard_figure.png │ ├── tensorboard_first_view.png │ ├── tensorboard_images.png │ ├── tensorboard_model_viz.png │ ├── tensorboard_pr_curves.png │ ├── tensorboard_projector.png │ ├── tensorboard_scalar_runs.png │ ├── text_sentiment_ngrams_model.png │ ├── thumbnails │ │ ├── 220px-KnnClassification.png │ │ ├── babel.jpg │ │ ├── captum_teaser.png │ │ ├── cropped │ │ │ ├── 60-min-blitz.png │ │ │ ├── Adversarial-Example-Generation.png │ │ │ ├── Autograd-in-Cpp-Frontend.png │ │ │ ├── Combining-Distributed-DataParallel-with-Distributed-RPC-Framework.png │ │ │ ├── Custom-Cpp-and-CUDA-Extensions.png │ │ │ ├── Customize-Process-Group-Backends-Using-Cpp-Extensions.png │ │ │ ├── DCGAN-Tutorial.png │ │ │ ├── Deploying-PyTorch-in-Python-via-a-REST-API-with-Flask.png │ │ │ ├── Distributed-Pipeline-Parallelism-Using-RPC.png │ │ │ ├── Exporting-PyTorch-Models-to-ONNX-Graphs.png │ │ │ ├── Extending-TorchScript-with-Custom-Cpp-Classes.png │ │ │ ├── Extending-TorchScript-with-Custom-Cpp-Operators.png │ │ │ ├── Getting Started with Distributed-RPC-Framework.png │ │ │ ├── Getting-Started-with Distributed RPC Framework.png │ │ │ ├── Getting-Started-with-DCP.png │ │ │ ├── Getting-Started-with-Distributed-Data-Parallel.png │ │ │ ├── Getting-Started-with-Distributed-RPC-Framework.png │ │ │ ├── Getting-Started-with-FSDP.png │ │ │ ├── Implementing-Batch-RPC-Processing-Using-Asynchronous-Executions.png │ │ │ ├── Implementing-a-Parameter-Server-Using-Distributed-RPC-Framework.png │ │ │ ├── Introduction-to-TorchScript.png │ │ │ ├── Language-Translation-with-TorchText.png │ │ │ ├── Large-Scale-Transformer-model-training-with-Tensor-Parallel.png │ │ │ ├── Loading-a-TorchScript-Model-in-Cpp.png │ │ │ ├── Model-Parallel-Best-Practices.png │ │ │ ├── NLP-From-Scratch-Classifying-Names-with-a-Character-Level-RNN.png │ │ │ ├── NLP-From-Scratch-Generating-Names-with-a-Character-Level-RNN.png │ │ │ ├── NLP-From-Scratch-Translation-with-a-Sequence-to-Sequence-Network-and-Attention.png │ │ │ ├── Pruning-Tutorial.png │ │ │ ├── PyTorch-Distributed-Overview.png │ │ │ ├── Sequence-to-Sequence-Modeling-with-nnTransformer-andTorchText.png │ │ │ ├── TIAToolbox-Tutorial.png │ │ │ ├── Text-Classification-with-TorchText.png │ │ │ ├── TorchScript-Parallelism.jpg │ │ │ ├── TorchVision-Object-Detection-Finetuning-Tutorial.png │ │ │ ├── Training-Transformer-Models-using-Distributed-Data-Parallel-and-Pipeline-Parallelism.png │ │ │ ├── Training-Transformer-models-using-Pipeline-Parallelism.png │ │ │ ├── Transfer-Learning-for-Computer-Vision-Tutorial.png │ │ │ ├── Tutorials_Card_Template.psd │ │ │ ├── Using-the-PyTorch-Cpp-Frontend.png │ │ │ ├── Writing-Distributed-Applications-with-PyTorch.png │ │ │ ├── advanced-PyTorch-1point0-Distributed-Trainer-with-Amazon-AWS.png │ │ │ ├── amp.png │ │ │ ├── android.png │ │ │ ├── custom-datasets-transforms-and-dataloaders.png │ │ │ ├── defining-a-network.PNG │ │ │ ├── experimental-Channels-Last-Memory-Format-in-PyTorch.png │ │ │ ├── experimental-Introduction-to-Named-Tensors-in-PyTorch.png │ │ │ ├── experimental-Quantized-Transfer-Learning-for-Computer-Vision-Tutorial.png │ │ │ ├── experimental-Static-Quantization-with-Eager-Mode-in-PyTorch.png │ │ │ ├── generic-pytorch-logo.png │ │ │ ├── ios.png │ │ │ ├── knowledge_distillation_pytorch_logo.png │ │ │ ├── learning-pytorch-with-examples.png │ │ │ ├── loading-data-in-pytorch.png │ │ │ ├── loading-data.PNG │ │ │ ├── model-interpretability-using-captum.png │ │ │ ├── optional-Exporting-a-Model-from-PyTorch-to-ONNX-and-Running-it-using-ONNX-Runtime.png │ │ │ ├── parametrizations.png │ │ │ ├── profile.png │ │ │ ├── profiler.png │ │ │ ├── pytorch-logo.png │ │ │ ├── realtime_rpi.png │ │ │ ├── saving-and-loading-general-checkpoint.PNG │ │ │ ├── saving-and-loading-models-across-devices.PNG │ │ │ ├── saving-and-loading-models-for-inference.PNG │ │ │ ├── saving-multiple-models.PNG │ │ │ ├── torch-nn.png │ │ │ ├── torch_text_logo.png │ │ │ ├── torchaudio-Tutorial.png │ │ │ ├── torchaudio-alignment.png │ │ │ ├── torchaudio-asr.png │ │ │ ├── torchaudio-speech.png │ │ │ ├── torchscript_overview.png │ │ │ ├── using-flask-create-restful-api.png │ │ │ ├── visualizing-with-tensorboard.png │ │ │ ├── warmstarting-models.PNG │ │ │ ├── what-is-a-state-dict.PNG │ │ │ └── zeroing-out-gradients.PNG │ │ ├── custom_dataset.png │ │ ├── default.png │ │ ├── defining_a_network.png │ │ ├── examples.png │ │ ├── eye.png │ │ ├── floppy.png │ │ ├── german_to_english_translation.png │ │ ├── landmarked_face2.png │ │ ├── pixelated-cat.png │ │ ├── pytorch-logo-flat.png │ │ ├── pytorch_tensorboard.png │ │ ├── sphx_glr_transfer_learning_tutorial_001.png │ │ ├── tensorboard_dev.png │ │ ├── tensorboard_scalars.png │ │ ├── torch-logo.png │ │ ├── torchrec.png │ │ ├── torchtext.png │ │ └── tv-img.png │ ├── tiatoolbox_tutorial │ │ ├── read_bounds_tissue.webp │ │ ├── tiatoolbox_tutorial_001.png │ │ ├── tiatoolbox_tutorial_002.png │ │ ├── tiatoolbox_tutorial_003.png │ │ ├── tiatoolbox_tutorial_004.png │ │ └── tiatoolbox_tutorial_005.png │ ├── torch-nn-vs-pytorch-nn.png │ ├── torch.nn.png │ ├── torchscript.png │ ├── torchscript_to_cpp.png │ ├── torchserve-ipex-images-2 │ │ ├── 1.png │ │ ├── 10.png │ │ ├── 11.png │ │ ├── 12.png │ │ ├── 13.png │ │ ├── 14.png │ │ ├── 15.png │ │ ├── 16.png │ │ ├── 17.png │ │ ├── 18.png │ │ ├── 19.png │ │ ├── 2.png │ │ ├── 20.png │ │ ├── 21.png │ │ ├── 22.png │ │ ├── 23.png │ │ ├── 24.png │ │ ├── 3.png │ │ ├── 4.png │ │ ├── 5.png │ │ ├── 6.png │ │ ├── 7.png │ │ ├── 8.png │ │ └── 9.png │ ├── torchserve-ipex-images │ │ ├── 1.png │ │ ├── 10.png │ │ ├── 11.gif │ │ ├── 12.png │ │ ├── 13.png │ │ ├── 14.png │ │ ├── 15.png │ │ ├── 16.png │ │ ├── 17.png │ │ ├── 18.png │ │ ├── 19.png │ │ ├── 1_.png │ │ ├── 2.png │ │ ├── 20.gif │ │ ├── 21.png │ │ ├── 22.png │ │ ├── 23.png │ │ ├── 24.png │ │ ├── 25.png │ │ ├── 26.gif │ │ ├── 27.png │ │ ├── 28.png │ │ ├── 29.png │ │ ├── 3.png │ │ ├── 30.png │ │ ├── 31.png │ │ ├── 4.png │ │ ├── 5.png │ │ ├── 6.png │ │ ├── 7.png │ │ ├── 8.png │ │ └── 9.gif │ ├── trace_img.png │ ├── trace_xpu_img.png │ ├── transformer_architecture.jpg │ ├── transformer_input_target.png │ ├── tts_pipeline.png │ ├── tv_tutorial │ │ ├── tv_image03.png │ │ └── tv_image04.png │ └── usb_semisup_learn │ │ └── code.png ├── jquery-3.2.1.js ├── jquery.js ├── js │ ├── custom.js │ └── modernizr.min.js ├── minus.png ├── mnist.pkl.gz ├── no_image.png ├── pencil-16.png ├── plus.png ├── pygments.css ├── pytorch-logo-dark.svg ├── searchtools.js ├── tiatoolbox_tutorial.ipynb ├── underscore-1.3.1.js ├── underscore.js ├── up-pressed.png ├── up.png └── websupport.js ├── _templates └── layout.html ├── advanced_source ├── ONNXLive.rst ├── README.txt ├── coding_ddpg.py ├── cpp_autograd.rst ├── cpp_cuda_graphs.rst ├── cpp_cuda_graphs │ ├── CMakeLists.txt │ ├── README.md │ └── mnist.cpp ├── cpp_custom_ops.rst ├── cpp_export.rst ├── cpp_extension.rst ├── cpp_frontend.rst ├── custom_ops_landing_page.rst ├── ddp_pipeline.rst ├── dispatcher.rst ├── dispatcher │ ├── CMakeLists.txt │ ├── op.cpp │ └── test.py ├── extend_dispatcher.rst ├── generic_join.rst ├── neural_style_tutorial.py ├── numpy_extensions_tutorial.py ├── pendulum.py ├── privateuseone.rst ├── python_custom_ops.py ├── rpc_ddp_tutorial.rst ├── rpc_ddp_tutorial │ └── main.py ├── semi_structured_sparse.py ├── sharding.rst ├── static_quantization_tutorial.rst ├── super_resolution_with_onnxruntime.py ├── torch-script-parallelism.rst ├── torch_script_custom_classes.rst ├── torch_script_custom_classes │ ├── CMakeLists.txt │ ├── custom_class_project │ │ ├── CMakeLists.txt │ │ ├── class.cpp │ │ ├── custom_test.py │ │ ├── export_attr.py │ │ └── save.py │ ├── infer.cpp │ ├── run.sh │ └── run2.sh ├── torch_script_custom_ops.rst ├── torch_script_custom_ops │ ├── CMakeLists.txt │ ├── op.cpp │ ├── smoke_test.py │ └── test.py ├── transformer__timeseries_cpp_tutorial │ ├── CMakeLists.txt │ ├── scheduler.h │ └── transformer_timeseries.cpp └── usb_semisup_learn.py ├── beginner_source ├── Intro_to_TorchScript_tutorial.py ├── README.txt ├── audio_data_augmentation_tutorial.rst ├── audio_datasets_tutorial.rst ├── audio_feature_augmentation_tutorial.rst ├── audio_feature_extractions_tutorial.rst ├── audio_io_tutorial.rst ├── audio_resampling_tutorial.rst ├── basics │ ├── README.txt │ ├── autogradqs_tutorial.py │ ├── buildmodel_tutorial.py │ ├── data_tutorial.py │ ├── intro.py │ ├── optimization_tutorial.py │ ├── qs_toc.txt │ ├── quickstart_tutorial.py │ ├── saveloadrun_tutorial.py │ ├── tensorqs_tutorial.py │ └── transforms_tutorial.py ├── bettertransformer_tutorial.rst ├── blitz │ ├── README.txt │ ├── autograd_tutorial.py │ ├── cifar10_tutorial.py │ ├── data_parallel_tutorial.py │ ├── neural_networks_tutorial.py │ └── tensor_tutorial.py ├── chatbot_tutorial.py ├── colab.rst ├── data_loading_tutorial.py ├── dcgan_faces_tutorial.py ├── ddp_series_fault_tolerance.rst ├── ddp_series_intro.rst ├── ddp_series_multigpu.rst ├── ddp_series_theory.rst ├── deep_learning_60min_blitz.rst ├── deeplabv3_on_android.rst ├── deeplabv3_on_ios.rst ├── dist_overview.rst ├── examples_autograd │ ├── README.txt │ ├── polynomial_autograd.py │ └── polynomial_custom_function.py ├── examples_nn │ ├── README.txt │ ├── dynamic_net.py │ ├── polynomial_module.py │ ├── polynomial_nn.py │ └── polynomial_optim.py ├── examples_tensor │ ├── README.txt │ ├── polynomial_numpy.py │ └── polynomial_tensor.py ├── fgsm_tutorial.py ├── finetuning_torchvision_models_tutorial.rst ├── former_torchies │ ├── autograd_tutorial_old.rst │ ├── nnft_tutorial.rst │ ├── parallelism_tutorial.rst │ └── tensor_tutorial_old.rst ├── former_torchies_tutorial.rst ├── hta_intro_tutorial.rst ├── hta_trace_diff_tutorial.rst ├── hybrid_frontend │ ├── README.txt │ └── learning_hybrid_frontend_through_example_tutorial.py ├── hybrid_frontend_tutorial.rst ├── hyperparameter_tuning_tutorial.py ├── introyt.rst ├── introyt │ ├── README.txt │ ├── autogradyt_tutorial.py │ ├── captumyt.py │ ├── introyt1_tutorial.py │ ├── introyt_index.py │ ├── modelsyt_tutorial.py │ ├── tensorboardyt_tutorial.py │ ├── tensors_deeper_tutorial.py │ ├── tocyt.txt │ └── trainingyt.py ├── knowledge_distillation_tutorial.py ├── nlp │ ├── README.txt │ ├── advanced_tutorial.py │ ├── deep_learning_tutorial.py │ ├── pytorch_tutorial.py │ ├── sequence_models_tutorial.py │ └── word_embeddings_tutorial.py ├── nn_tutorial.py ├── onnx │ ├── README.txt │ ├── export_control_flow_model_to_onnx_tutorial.py │ ├── export_simple_model_to_onnx_tutorial.py │ ├── intro_onnx.py │ ├── onnx_registry_tutorial.py │ └── onnx_toc.txt ├── profiler.py ├── pytorch_with_examples.rst ├── saving_loading_models.py ├── t5_tutoria.rst ├── template_tutorial.py ├── text_sentiment_ngrams_tutorial.rst ├── torchtext_custom_dataset_tutorial.rst ├── transfer_learning_tutorial.py ├── transformer_tutorial.rst └── translation_transformer.rst ├── build.sh ├── cleanup.sh ├── conf.py ├── custom_directives.py ├── distributed └── home.rst ├── docathon-leaderboard.md ├── en-wordlist.txt ├── index.rst ├── intermediate_source ├── FSDP1_tutorial.rst ├── FSDP_advanced_tutorial.rst ├── FSDP_tutorial.rst ├── README.txt ├── TCPStore_libuv_backend.rst ├── TP_tutorial.rst ├── _torch_export_nightly_tutorial.py ├── autograd_saved_tensors_hooks_tutorial.py ├── ax_multiobjective_nas_tutorial.py ├── char_rnn_classification_tutorial.py ├── char_rnn_generation_tutorial.py ├── compiled_autograd_tutorial.rst ├── custom_function_conv_bn_tutorial.py ├── custom_function_double_backward_tutorial.rst ├── ddp_series_minGPT.rst ├── ddp_series_multinode.rst ├── ddp_tutorial.rst ├── dist_pipeline_parallel_tutorial.rst ├── dist_tuto.rst ├── dqn_with_rnn_tutorial.py ├── ensembling.py ├── forced_alignment_with_torchaudio_tutorial.rst ├── forward_ad_usage.py ├── fx_conv_bn_fuser.py ├── fx_profiling_tutorial.py ├── inductor_debug_cpu.py ├── jacobians_hessians.py ├── mario_rl_tutorial.py ├── memory_format_tutorial.py ├── mnist_train_nas.py ├── model_parallel_tutorial.rst ├── neural_tangent_kernels.py ├── nlp_from_scratch_index.rst ├── nvfuser_intro_tutorial.rst ├── optimizer_step_in_backward_tutorial.py ├── parametrizations.py ├── per_sample_grads.py ├── pinmem_nonblock.py ├── pipeline_tutorial.rst ├── pipelining_tutorial.rst ├── process_group_cpp_extension_tutorial.rst ├── pruning_tutorial.py ├── realtime_rpi.rst ├── reinforcement_ppo.py ├── reinforcement_q_learning.py ├── rpc_async_execution.rst ├── rpc_param_server_tutorial.rst ├── rpc_tutorial.rst ├── scaled_dot_product_attention_tutorial.py ├── seq2seq_translation_tutorial.py ├── spatial_transformer_tutorial.py ├── speech_recognition_pipeline_tutorial.rst ├── tensorboard_profiler_tutorial.py ├── tensorboard_tutorial.rst ├── text_to_speech_with_torchaudio.rst ├── tiatoolbox_tutorial.rst ├── torch_compile_tutorial.py ├── torch_export_nightly_tutorial.rst ├── torch_export_tutorial.py ├── torchrec_intro_tutorial.py ├── torchrec_tutorial.rst ├── torchvision_tutorial.py └── transformer_building_blocks.py ├── lychee.toml ├── prototype_source ├── README.md ├── README.txt ├── backend_config_tutorial.rst ├── context_parallel.rst ├── distributed_rpc_profiling.rst ├── flight_recorder_tutorial.rst ├── gpu_direct_storage.py ├── gpu_quantization_torchao_tutorial.py ├── inductor_cpp_wrapper_tutorial.rst ├── inductor_windows.rst ├── inductor_windows_cpu.rst ├── ios_coreml_workflow.rst ├── ios_gpu_workflow.rst ├── lite_interpreter.rst ├── maskedtensor_adagrad.py ├── maskedtensor_advanced_semantics.py ├── maskedtensor_overview.py ├── maskedtensor_sparsity.py ├── max_autotune_on_CPU_tutorial.rst ├── nestedtensor.py ├── nnapi_mobilenetv2.rst ├── openvino_quantizer.rst ├── prototype_index.rst ├── python_extension_autoload.rst ├── semi_structured_sparse.rst ├── skip_param_init.rst ├── torchscript_freezing.py ├── tracing_based_selective_build.rst ├── vmap_recipe.py └── vulkan_workflow.rst ├── recipes_source ├── README.txt ├── amx.rst ├── android_native_app_with_custom_op.rst ├── compiling_optimizer.rst ├── compiling_optimizer_lr_scheduler.py ├── cuda_rpc.rst ├── distributed_async_checkpoint_recipe.rst ├── distributed_checkpoint_recipe.rst ├── distributed_comm_debug_mode.rst ├── distributed_device_mesh.rst ├── distributed_optim_torchscript.rst ├── distributed_rpc_profiling.rst ├── foreach_map.py ├── inference_tuning_on_aws_graviton.rst ├── intel_extension_for_pytorch.rst ├── intel_neural_compressor_for_pytorch.rst ├── loading_data_recipe.rst ├── mobile_interpreter.rst ├── mobile_perf.rst ├── model_preparation_android.rst ├── model_preparation_ios.rst ├── profile_with_itt.rst ├── ptmobile_recipes_summary.rst ├── recipes │ ├── Captum_Recipe.py │ ├── README.txt │ ├── amp_recipe.py │ ├── benchmark.py │ ├── changing_default_device.py │ ├── defining_a_neural_network.py │ ├── module_load_state_dict_tips.py │ ├── profiler_recipe.py │ ├── reasoning_about_shapes.py │ ├── save_load_across_devices.rst │ ├── saving_and_loading_a_general_checkpoint.rst │ ├── saving_and_loading_models_for_inference.rst │ ├── saving_multiple_models_in_one_file.rst │ ├── swap_tensors.py │ ├── tensorboard_with_pytorch.py │ ├── timer_quick_start.py │ ├── tuning_guide.py │ ├── warmstarting_model_using_parameters_from_a_different_model.py │ ├── what_is_state_dict.py │ └── zeroing_out_gradients.py ├── recipes_index.rst ├── regional_compilation.py ├── script_optimized.rst ├── torch_compile_backend_ipex.rst ├── torch_compile_caching_configuration_tutorial.rst ├── torch_compile_caching_tutorial.rst ├── torch_compile_torch_function_modes.py ├── torch_compile_user_defined_triton_kernel_tutorial.py ├── torch_compiler_set_stance_tutorial.py ├── torch_export_aoti_python.py ├── torch_export_challenges_solutions.rst ├── torch_logs.py ├── torchscript_inference.rst ├── xeon_run_cpu.rst └── zero_redundancy_optimizer.rst ├── redirects.py ├── requirements.txt ├── runtime.txt └── tutorial_submission_policy.md /.ci/docker/Dockerfile: -------------------------------------------------------------------------------- 1 | ARG BASE_IMAGE 2 | FROM ${BASE_IMAGE} 3 | 4 | ENV DEBIAN_FRONTEND noninteractive 5 | 6 | # Install common dependencies (so that this step can be cached separately) 7 | COPY ./common/install_base.sh install_base.sh 8 | RUN bash ./install_base.sh && rm install_base.sh 9 | 10 | # Setup user 11 | # TODO: figure out how to remove this part 12 | COPY ./common/install_user.sh install_user.sh 13 | RUN bash ./install_user.sh && rm install_user.sh 14 | 15 | COPY ./common/install_docs_reqs.sh install_docs_reqs.sh 16 | RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh 17 | 18 | COPY ./common/install_pip_requirements.sh install_pip_requirements.sh 19 | COPY ./requirements.txt requirements.txt 20 | RUN bash ./install_pip_requirements.sh && rm install_pip_requirements.sh 21 | 22 | RUN ln -s /usr/bin/python3 /usr/bin/python 23 | 24 | USER ci-user 25 | CMD ["bash"] 26 | -------------------------------------------------------------------------------- /.ci/docker/build.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | # Copyright (c) Meta Platforms, Inc. and affiliates. 3 | # All rights reserved. 4 | # 5 | # This source code is licensed under the BSD-style license found in the 6 | # LICENSE file in the root directory of this source tree. 7 | 8 | set -exu 9 | 10 | IMAGE_NAME="$1" 11 | shift 12 | 13 | export UBUNTU_VERSION="22.04" 14 | export CUDA_VERSION="12.6.3" 15 | 16 | export BASE_IMAGE="nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}" 17 | echo "Building ${IMAGE_NAME} Docker image" 18 | 19 | docker build \ 20 | --no-cache \ 21 | --progress=plain \ 22 | -f Dockerfile \ 23 | --build-arg BASE_IMAGE="${BASE_IMAGE}" \ 24 | "$@" \ 25 | . 26 | -------------------------------------------------------------------------------- /.ci/docker/common/install_base.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | # Based off of https://github.com/pytorch/pytorch/tree/b52e0bf131a4e55cd987176f9c5a8d2ad6783b4f/.ci/docker 3 | 4 | set -ex 5 | 6 | install_ubuntu() { 7 | # Install common dependencies 8 | apt-get update 9 | # TODO: Some of these may not be necessary 10 | apt-get install -y --no-install-recommends \ 11 | build-essential \ 12 | ca-certificates \ 13 | cmake=3.22* \ 14 | curl \ 15 | git \ 16 | wget \ 17 | sudo \ 18 | vim \ 19 | jq \ 20 | vim \ 21 | unzip \ 22 | gdb \ 23 | rsync \ 24 | libssl-dev \ 25 | p7zip-full \ 26 | libglfw3 \ 27 | libglfw3-dev \ 28 | sox \ 29 | libsox-dev \ 30 | libsox-fmt-all \ 31 | python3-pip \ 32 | python3-dev 33 | 34 | # Cleanup package manager 35 | apt-get autoclean && apt-get clean 36 | rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* 37 | } 38 | 39 | # Install base packages depending on the base OS 40 | ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"') 41 | case "$ID" in 42 | ubuntu) 43 | install_ubuntu 44 | ;; 45 | *) 46 | echo "Unable to determine OS..." 47 | exit 1 48 | ;; 49 | esac 50 | -------------------------------------------------------------------------------- /.ci/docker/common/install_docs_reqs.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | # Based off of https://github.com/pytorch/pytorch/tree/b52e0bf131a4e55cd987176f9c5a8d2ad6783b4f/.ci/docker 3 | set -ex 4 | 5 | apt-get update 6 | apt-get install -y gpg-agent 7 | 8 | curl --retry 3 -sL https://deb.nodesource.com/setup_20.x | sudo -E bash - 9 | sudo apt-get install -y nodejs 10 | 11 | curl --retry 3 -sS https://dl.yarnpkg.com/debian/pubkey.gpg | sudo apt-key add - 12 | echo "deb https://dl.yarnpkg.com/debian/ stable main" | sudo tee /etc/apt/sources.list.d/yarn.list 13 | 14 | apt-get update 15 | apt-get install -y --no-install-recommends yarn 16 | yarn global add katex --prefix /usr/local 17 | 18 | sudo apt-get -y install doxygen 19 | 20 | apt-get autoclean && apt-get clean 21 | rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* 22 | -------------------------------------------------------------------------------- /.ci/docker/common/install_pip_requirements.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -ex 4 | 5 | # Install pip packages 6 | pip install --upgrade pip 7 | pip install -r ./requirements.txt 8 | -------------------------------------------------------------------------------- /.ci/docker/common/install_user.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | # Copyright (c) Meta Platforms, Inc. and affiliates. 3 | # All rights reserved. 4 | # 5 | # This source code is licensed under the BSD-style license found in the 6 | # LICENSE file in the root directory of this source tree. 7 | 8 | # Copied from https://github.com/pytorch/executorch/blob/6e431355a554e5f84c3a05dfa2b981ead90c2b48/.ci/docker/common/install_user.sh#L1 9 | 10 | set -ex 11 | 12 | # Same as ec2-user 13 | echo "ci-user:x:1000:1000::/var/lib/ci-user:" >> /etc/passwd 14 | echo "ci-user:x:1000:" >> /etc/group 15 | # Needed on Focal or newer 16 | echo "ci-user:*:19110:0:99999:7:::" >> /etc/shadow 17 | 18 | # Create $HOME 19 | mkdir -p /var/lib/ci-user 20 | chown ci-user:ci-user /var/lib/ci-user 21 | 22 | # Allow sudo 23 | echo 'ci-user ALL=(ALL) NOPASSWD:ALL' > /etc/sudoers.d/ci-user 24 | 25 | # Test that sudo works 26 | sudo -u ci-user sudo -v 27 | -------------------------------------------------------------------------------- /.devcontainer/Dockerfile: -------------------------------------------------------------------------------- 1 | FROM mcr.microsoft.com/vscode/devcontainers/python:3.8 2 | 3 | COPY requirements.txt /tmp/pip-tmp/ 4 | 5 | RUN apt-get update && export DEBIAN_FRONTEND=noninteractive \ 6 | && apt-get install git gcc unzip make -y \ 7 | && pip3 install --disable-pip-version-check --no-cache-dir -r /tmp/pip-tmp/requirements.txt \ 8 | && rm -rf /tmp/pip-tmp 9 | -------------------------------------------------------------------------------- /.devcontainer/devcontainer.json: -------------------------------------------------------------------------------- 1 | { 2 | "name": "PyTorch Tutorials", 3 | "build": { 4 | "context": "..", 5 | "dockerfile": "Dockerfile", 6 | "args": {} 7 | }, 8 | "settings": { 9 | "terminal.integrated.shell.linux": "/bin/bash", 10 | "workbench.startupEditor": "none", 11 | "files.autoSave": "afterDelay", 12 | "python.dataScience.enabled": true, 13 | "python.dataScience.alwaysTrustNotebooks": true, 14 | "python.insidersChannel": "weekly", 15 | "python.showStartPage": false 16 | }, 17 | "extensions": ["ms-python.python", "lextudio.restructuredtext"] 18 | } 19 | -------------------------------------------------------------------------------- /.devcontainer/requirements.txt: -------------------------------------------------------------------------------- 1 | # Refer to ./jenkins/build.sh for tutorial build instructions 2 | 3 | sphinx==1.8.2 4 | sphinx-gallery==0.3.1 5 | tqdm 6 | numpy 7 | matplotlib 8 | torch 9 | torchvision 10 | torchtext 11 | torchaudio 12 | PyHamcrest 13 | bs4 14 | awscli==1.16.35 15 | flask 16 | spacy 17 | ray[tune] 18 | 19 | # PyTorch Theme 20 | -e git+https://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme 21 | 22 | ipython 23 | 24 | # to run examples 25 | pandas 26 | scikit-image 27 | pillow==10.3.0 28 | wget 29 | 30 | # for codespaces env 31 | pylint 32 | -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE/feature-request.yml: -------------------------------------------------------------------------------- 1 | name: 🚀 Feature request 2 | description: Submit a proposal for a new PyTorch tutorial or improvement of an existing tutorial 3 | title: "💡 [REQUEST] - " 4 | labels: [ 5 | "feature" 6 | ] 7 | 8 | body: 9 | - type: textarea 10 | attributes: 11 | label: 🚀 Describe the improvement or the new tutorial 12 | description: | 13 | **Describe the improvement** 14 | placeholder: | 15 | Explain why this improvement or new tutorial is important. For example, *"This tutorial will help users to better understand feature X of PyTorch."* If there is a tutorial that you propose to replace, add here. If this is related to another GitHub issue, add a link here. 16 | validations: 17 | required: true 18 | - type: textarea 19 | attributes: 20 | label: Existing tutorials on this topic 21 | description: | 22 | **Add a list of existing tutorials on the same topic.** 23 | placeholder: | 24 | List tutorials that already explain this functionality if exist. On pytorch.org or elsewhere. 25 | * Link 26 | * Link 27 | - type: textarea 28 | attributes: 29 | label: Additional context 30 | description: | 31 | **Add additional context** 32 | placeholder: | 33 | Add any other context or screenshots about the feature request. 34 | - type: markdown 35 | attributes: 36 | value: > 37 | Thanks for contributing 🎉! 38 | -------------------------------------------------------------------------------- /.github/PULL_REQUEST_TEMPLATE.md: -------------------------------------------------------------------------------- 1 | Fixes #ISSUE_NUMBER 2 | 3 | ## Description 4 | <!--- Describe your changes in detail --> 5 | 6 | ## Checklist 7 | <!--- Make sure to add `x` to all items in the following checklist: --> 8 | - [ ] The issue that is being fixed is referred in the description (see above "Fixes #ISSUE_NUMBER") 9 | - [ ] Only one issue is addressed in this pull request 10 | - [ ] Labels from the issue that this PR is fixing are added to this pull request 11 | - [ ] No unnecessary issues are included into this pull request. 12 | -------------------------------------------------------------------------------- /.github/pytorch-probot.yml: -------------------------------------------------------------------------------- 1 | tracking_issue: 1896 2 | -------------------------------------------------------------------------------- /.github/workflows/check-redirects.yml: -------------------------------------------------------------------------------- 1 | name: Check Redirects for Deleted or Renamed Files 2 | 3 | on: 4 | pull_request: 5 | paths: 6 | - '*/**/*.rst' 7 | - '*/**/*.py' 8 | - '*/**/*.md' 9 | 10 | jobs: 11 | check-redirects: 12 | runs-on: ubuntu-latest 13 | steps: 14 | - name: Checkout code 15 | uses: actions/checkout@v4 16 | with: 17 | fetch-depth: 0 18 | 19 | - name: Run redirect check script 20 | run: | 21 | chmod +x ./.github/scripts/check_redirects.sh 22 | ./.github/scripts/check_redirects.sh 23 | env: 24 | BASE_BRANCH: ${{ github.base_ref }} 25 | CURRENT_BRANCH: ${{ github.head_ref }} 26 | -------------------------------------------------------------------------------- /.github/workflows/docathon-label-sync.yml: -------------------------------------------------------------------------------- 1 | name: Docathon Labels Sync 2 | 3 | on: 4 | pull_request_target: 5 | types: [opened, synchronize, edited] 6 | 7 | jobs: 8 | check-labels: 9 | runs-on: ubuntu-latest 10 | permissions: 11 | issues: write 12 | pull-requests: write 13 | steps: 14 | - name: Check if PR mentions an issue and get labels 15 | uses: actions/checkout@v2 16 | with: 17 | fetch-depth: 1 18 | - name: Set up Python 19 | uses: actions/setup-python@v2 20 | with: 21 | python-version: 3.x 22 | - name: Install dependencies 23 | run: | 24 | pip install requests 25 | pip install PyGithub 26 | - name: Run Python script 27 | env: 28 | GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} 29 | run: python ./.github/scripts/docathon-label-sync.py ${{ github.event.pull_request.number }} 30 | -------------------------------------------------------------------------------- /.gitmodules: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/pytorch/tutorials/fee83dd33ab594bcdf49bd9c9da3fa2b07ffe219/.gitmodules -------------------------------------------------------------------------------- /.jenkins/delete_html_file_with_runnable_code_removed.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import os 3 | 4 | html_file_path = sys.argv[1] 5 | 6 | with open(html_file_path, 'r', encoding='utf-8') as html_file: 7 | html = html_file.read() 8 | 9 | if "%%%%%%RUNNABLE_CODE_REMOVED%%%%%%" in html: 10 | print("Removing " + html_file_path) 11 | os.remove(html_file_path) 12 | -------------------------------------------------------------------------------- /.jenkins/get_docker_tag.py: -------------------------------------------------------------------------------- 1 | import requests 2 | 3 | REQUEST_HEADERS = { 4 | "Accept": "application/vnd.github.v3+json", 5 | } 6 | 7 | if __name__ == "__main__": 8 | url = "https://api.github.com/repos/pytorch/pytorch/contents/.ci" 9 | 10 | response = requests.get(url, headers=REQUEST_HEADERS) 11 | docker_sha = None 12 | for finfo in response.json(): 13 | if finfo["name"] == "docker": 14 | docker_sha = finfo["sha"] 15 | break 16 | if docker_sha is None: 17 | raise RuntimeError("Can't find sha sum of docker folder") 18 | print(docker_sha) 19 | -------------------------------------------------------------------------------- /.jenkins/get_sphinx_filenames.py: -------------------------------------------------------------------------------- 1 | from pathlib import Path 2 | from typing import List 3 | 4 | from get_files_to_run import get_all_files 5 | from validate_tutorials_built import NOT_RUN 6 | 7 | 8 | def get_files_for_sphinx() -> List[str]: 9 | all_py_files = get_all_files() 10 | return [x for x in all_py_files if all(y not in x for y in NOT_RUN)] 11 | 12 | 13 | SPHINX_SHOULD_RUN = "|".join(get_files_for_sphinx()) 14 | -------------------------------------------------------------------------------- /.jenkins/remove_invisible_code_block_batch.sh: -------------------------------------------------------------------------------- 1 | BUILDDIR=$1 2 | 3 | DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null && pwd )" 4 | 5 | # Remove INVISIBLE_CODE_BLOCK from .html/.rst/.rst.txt/.ipynb/.py files 6 | for filename in $(find $BUILDDIR/beginner $BUILDDIR/intermediate $BUILDDIR/advanced -name '*.html'); do 7 | echo "Removing INVISIBLE_CODE_BLOCK from " $filename 8 | python $DIR/remove_invisible_code_block_from_html.py $filename $filename 9 | done 10 | for filename in $(find $BUILDDIR/_sources/beginner $BUILDDIR/_sources/intermediate $BUILDDIR/_sources/advanced -name '*.rst.txt'); do 11 | echo "Removing INVISIBLE_CODE_BLOCK from " $filename 12 | python $DIR/remove_invisible_code_block_from_rst_txt.py $filename $filename 13 | done 14 | for filename in $(find $BUILDDIR/_downloads -name '*.ipynb'); do 15 | echo "Removing INVISIBLE_CODE_BLOCK from " $filename 16 | python $DIR/remove_invisible_code_block_from_ipynb.py $filename $filename 17 | done 18 | for filename in $(find $BUILDDIR/_downloads -name '*.py'); do 19 | echo "Removing INVISIBLE_CODE_BLOCK from " $filename 20 | python $DIR/remove_invisible_code_block_from_py.py $filename $filename 21 | done 22 | -------------------------------------------------------------------------------- /.jenkins/remove_invisible_code_block_from_html.py: -------------------------------------------------------------------------------- 1 | import sys 2 | from bs4 import BeautifulSoup 3 | 4 | html_file_path = sys.argv[1] 5 | output_file_path = sys.argv[2] 6 | 7 | with open(html_file_path, 'r', encoding='utf-8') as html_file: 8 | html = html_file.read() 9 | html_soup = BeautifulSoup(html, 'html.parser') 10 | 11 | elems = html_soup.find_all("div", {"class": "highlight-default"}) 12 | for elem in elems: 13 | if "%%%%%%INVISIBLE_CODE_BLOCK%%%%%%" in str(elem): 14 | elem.decompose() 15 | 16 | with open(output_file_path, "w", encoding='utf-8') as output_file: 17 | output_file.write(str(html_soup)) 18 | -------------------------------------------------------------------------------- /.jenkins/remove_invisible_code_block_from_ipynb.py: -------------------------------------------------------------------------------- 1 | import sys 2 | from bs4 import BeautifulSoup 3 | 4 | ipynb_file_path = sys.argv[1] 5 | output_file_path = sys.argv[2] 6 | 7 | with open(ipynb_file_path, 'r', encoding='utf-8') as ipynb_file: 8 | ipynb_lines = ipynb_file.readlines() 9 | 10 | ipynb_out_lines = [] 11 | 12 | for line in ipynb_lines: 13 | if not '%%%%%%INVISIBLE_CODE_BLOCK%%%%%%' in line: 14 | ipynb_out_lines.append(line) 15 | 16 | with open(output_file_path, "w", encoding='utf-8') as output_file: 17 | for line in ipynb_out_lines: 18 | output_file.write(line) 19 | -------------------------------------------------------------------------------- /.jenkins/remove_invisible_code_block_from_py.py: -------------------------------------------------------------------------------- 1 | import sys 2 | from bs4 import BeautifulSoup 3 | 4 | py_file_path = sys.argv[1] 5 | output_file_path = sys.argv[2] 6 | 7 | with open(py_file_path, 'r', encoding='utf-8') as py_file: 8 | py_lines = py_file.readlines() 9 | 10 | py_out_lines = [] 11 | 12 | in_invisible_block = False 13 | for line in py_lines: 14 | if not in_invisible_block: 15 | if '%%%%%%INVISIBLE_CODE_BLOCK%%%%%%' in line: 16 | in_invisible_block = True 17 | else: 18 | py_out_lines.append(line) 19 | else: 20 | if '%%%%%%INVISIBLE_CODE_BLOCK%%%%%%' in line: 21 | in_invisible_block = False 22 | 23 | with open(output_file_path, "w", encoding='utf-8') as output_file: 24 | for line in py_out_lines: 25 | output_file.write(line) 26 | -------------------------------------------------------------------------------- /.jenkins/remove_invisible_code_block_from_rst_txt.py: -------------------------------------------------------------------------------- 1 | import sys 2 | from bs4 import BeautifulSoup 3 | 4 | rst_txt_file_path = sys.argv[1] 5 | output_file_path = sys.argv[2] 6 | 7 | with open(rst_txt_file_path, 'r', encoding='utf-8') as rst_txt_file: 8 | rst_txt = rst_txt_file.read() 9 | 10 | splits = rst_txt.split('.. code-block:: default\n\n\n # %%%%%%INVISIBLE_CODE_BLOCK%%%%%%\n') 11 | if len(splits) == 2: 12 | code_before_invisible_block = splits[0] 13 | code_after_invisible_block = splits[1].split(' # %%%%%%INVISIBLE_CODE_BLOCK%%%%%%\n')[1] 14 | rst_txt_out = code_before_invisible_block + code_after_invisible_block 15 | else: 16 | rst_txt_out = rst_txt 17 | 18 | with open(output_file_path, "w", encoding='utf-8') as output_file: 19 | output_file.write(rst_txt_out) 20 | -------------------------------------------------------------------------------- /.jenkins/replace_tutorial_html_content.py: -------------------------------------------------------------------------------- 1 | import sys 2 | 3 | noplot_html_file_path = sys.argv[1] 4 | hasplot_html_file_path = sys.argv[2] 5 | output_html_file_path = sys.argv[3] 6 | 7 | from bs4 import BeautifulSoup 8 | with open(noplot_html_file_path, 'r', encoding='utf-8') as noplot_html_file: 9 | noplot_html = noplot_html_file.read() 10 | with open(hasplot_html_file_path, 'r', encoding='utf-8') as hasplot_html_file: 11 | hasplot_html = hasplot_html_file.read() 12 | 13 | noplot_html_soup = BeautifulSoup(noplot_html, 'html.parser') 14 | elems = noplot_html_soup.find_all("div", {"class": "sphx-glr-example-title"}) 15 | if len(elems) == 0: 16 | print("No match found, not replacing HTML content in "+noplot_html_file_path) 17 | elif len(elems) == 1: 18 | print("Match found in "+noplot_html_file_path+". Replacing its content.") 19 | elem = elems[0] 20 | elem.replace_with(BeautifulSoup(hasplot_html, 'html.parser').find_all("div", {"class": "sphx-glr-example-title"})[0]) 21 | with open(output_html_file_path, "w", encoding='utf-8') as output_html_file: 22 | output_html_file.write(str(noplot_html_soup)) 23 | else: 24 | raise Exception("Found more than one match in "+noplot_html_file_path+". Aborting.") 25 | -------------------------------------------------------------------------------- /.jenkins/test_files_to_run.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | from get_files_to_run import get_all_files, calculate_shards 3 | from unittest import TestCase, main 4 | from functools import reduce 5 | 6 | class TestSharding(TestCase): 7 | def test_no_sharding(self): 8 | all_files=get_all_files() 9 | sharded_files = calculate_shards(all_files, 1) 10 | self.assertSetEqual(set(all_files), set(sharded_files[0])) 11 | 12 | def test_sharding(self, num_shards=20): 13 | all_files=get_all_files() 14 | sharded_files = map(set, calculate_shards(all_files, num_shards)) 15 | self.assertSetEqual(set(all_files), reduce(lambda x,y: x.union(y), sharded_files, set())) 16 | 17 | 18 | 19 | if __name__ == "__main__": 20 | main() 21 | -------------------------------------------------------------------------------- /.lycheeignore: -------------------------------------------------------------------------------- 1 | # Used for links to be ignored during the link check. 2 | # Add link to file along with comment as to why it should be ignored 3 | 4 | #Example link in some of the tutorials that should be ignored 5 | file:///f:/libtmp/some_file 6 | 7 | #Ignore links with "file:///" to catch any other example links 8 | file:\/\/\/.* 9 | 10 | # Ignore colab link in the setting of conf.py 11 | https://pytorch.org/tutorials/beginner/colab/n 12 | 13 | # Ignore local host link from intermediate_source/tensorboard_tutorial.rst 14 | http://localhost:6006 15 | 16 | # Ignore local host link from advanced_source/cpp_frontend.rst 17 | https://www.uber.com/blog/deep-neuroevolution/ 18 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | BSD 3-Clause License 2 | 3 | Copyright (c) 2017-2022, Pytorch contributors 4 | All rights reserved. 5 | 6 | Redistribution and use in source and binary forms, with or without 7 | modification, are permitted provided that the following conditions are met: 8 | 9 | * Redistributions of source code must retain the above copyright notice, this 10 | list of conditions and the following disclaimer. 11 | 12 | * Redistributions in binary form must reproduce the above copyright notice, 13 | this list of conditions and the following disclaimer in the documentation 14 | and/or other materials provided with the distribution. 15 | 16 | * Neither the name of the copyright holder nor the names of its 17 | contributors may be used to endorse or promote products derived from 18 | this software without specific prior written permission. 19 | 20 | THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" 21 | AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 22 | IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 23 | DISCLAIMED. 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attn_combine -> relu -> gru; 28 | prev_hidden -> gru; 29 | gru -> out; 30 | gru -> hidden; 31 | 32 | out -> softmax; 33 | softmax -> output; 34 | 35 | {rank=same;output;hidden} 36 | 37 | // Layer nodes 38 | embedding [fillcolor=dodgerblue, fontcolor=white]; 39 | attn [fillcolor=dodgerblue, fontcolor=white]; 40 | attn_combine [fillcolor=dodgerblue, fontcolor=white]; 41 | bmm [fillcolor=dodgerblue, fontcolor=white]; 42 | gru [fillcolor=dodgerblue, fontcolor=white]; 43 | out [fillcolor=dodgerblue, fontcolor=white]; 44 | 45 | // Function nodes 46 | dropout [fillcolor=palegreen]; 47 | relu [fillcolor=palegreen]; 48 | softmax [fillcolor=palegreen]; 49 | attn_softmax [fillcolor=palegreen]; 50 | 51 | } 52 | -------------------------------------------------------------------------------- /_static/img/seq-seq-images/attention-decoder-network.png: -------------------------------------------------------------------------------- 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| out [fillcolor=dodgerblue, fontcolor=white]; 29 | 30 | // Function nodes 31 | relu [fillcolor=palegreen]; 32 | softmax [fillcolor=palegreen]; 33 | 34 | } 35 | -------------------------------------------------------------------------------- /_static/img/seq-seq-images/decoder-network.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/pytorch/tutorials/fee83dd33ab594bcdf49bd9c9da3fa2b07ffe219/_static/img/seq-seq-images/decoder-network.png -------------------------------------------------------------------------------- /_static/img/seq-seq-images/decoder.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/pytorch/tutorials/fee83dd33ab594bcdf49bd9c9da3fa2b07ffe219/_static/img/seq-seq-images/decoder.png -------------------------------------------------------------------------------- /_static/img/seq-seq-images/decoder@2x.png: 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-------------------------------------------------------------------------------- 1 | Advanced Tutorials 2 | ------------------ 3 | 4 | 1. neural_style_tutorial.py 5 | Neural Transfer with PyTorch 6 | https://pytorch.org/tutorials/advanced/neural_style_tutorial.html 7 | 8 | 2. numpy_extensions_tutorial.py 9 | Creating Extensions Using numpy and scipy 10 | https://pytorch.org/tutorials/advanced/numpy_extensions_tutorial.html 11 | 12 | 3. c_extension.rst 13 | Custom C Extensions for PyTorch 14 | https://pytorch.org/tutorials/advanced/c_extension.html 15 | 16 | 4. super_resolution_with_onnxruntime.py 17 | Exporting a Model from PyTorch to ONNX and Running it using ONNXRuntime 18 | https://pytorch.org/tutorials/advanced/super_resolution_with_onnxruntime.html 19 | -------------------------------------------------------------------------------- /advanced_source/cpp_cuda_graphs/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | cmake_minimum_required(VERSION 3.18 FATAL_ERROR) 2 | project(mnist) 3 | set(CMAKE_CXX_STANDARD 17) 4 | 5 | find_package(Torch REQUIRED) 6 | find_package(Threads REQUIRED) 7 | 8 | option(DOWNLOAD_MNIST "Download the MNIST dataset from the internet" ON) 9 | if (DOWNLOAD_MNIST) 10 | message(STATUS "Downloading MNIST dataset") 11 | execute_process( 12 | COMMAND python ${CMAKE_CURRENT_LIST_DIR}/../tools/download_mnist.py 13 | -d ${CMAKE_BINARY_DIR}/data 14 | ERROR_VARIABLE DOWNLOAD_ERROR) 15 | if (DOWNLOAD_ERROR) 16 | message(FATAL_ERROR "Error downloading MNIST dataset: ${DOWNLOAD_ERROR}") 17 | endif() 18 | endif() 19 | 20 | add_executable(mnist mnist.cpp) 21 | target_compile_features(mnist PUBLIC cxx_range_for) 22 | target_link_libraries(mnist ${TORCH_LIBRARIES} ${CMAKE_THREAD_LIBS_INIT}) 23 | 24 | if (MSVC) 25 | file(GLOB TORCH_DLLS "${TORCH_INSTALL_PREFIX}/lib/*.dll") 26 | add_custom_command(TARGET mnist 27 | POST_BUILD 28 | COMMAND ${CMAKE_COMMAND} -E copy_if_different 29 | ${TORCH_DLLS} 30 | $) 31 | endif (MSVC) 32 | -------------------------------------------------------------------------------- /advanced_source/cpp_cuda_graphs/README.md: -------------------------------------------------------------------------------- 1 | # MNIST Example with the PyTorch C++ Frontend 2 | 3 | This folder contains an example of training a computer vision model to recognize 4 | digits in images from the MNIST dataset, using the PyTorch C++ frontend. 5 | 6 | The entire training code is contained in `mnist.cpp`. 7 | 8 | To build the code, run the following commands from your terminal: 9 | 10 | ```shell 11 | $ cd mnist 12 | $ mkdir build 13 | $ cd build 14 | $ cmake -DCMAKE_PREFIX_PATH=/path/to/libtorch .. 15 | $ make 16 | ``` 17 | 18 | where `/path/to/libtorch` should be the path to the unzipped _LibTorch_ 19 | distribution, which you can get from the [PyTorch 20 | homepage](https://pytorch.org/get-started/locally/). 21 | 22 | Execute the compiled binary to train the model: 23 | 24 | ```shell 25 | $ ./mnist 26 | Train Epoch: 1 [59584/60000] Loss: 0.4232 27 | Test set: Average loss: 0.1989 | Accuracy: 0.940 28 | Train Epoch: 2 [59584/60000] Loss: 0.1926 29 | Test set: Average loss: 0.1338 | Accuracy: 0.959 30 | Train Epoch: 3 [59584/60000] Loss: 0.1390 31 | Test set: Average loss: 0.0997 | Accuracy: 0.969 32 | Train Epoch: 4 [59584/60000] Loss: 0.1239 33 | Test set: Average loss: 0.0875 | Accuracy: 0.972 34 | ... 35 | ``` 36 | 37 | For running with CUDA Graphs add `--use-train-graph` and/or `--use-test-graph` 38 | for training and testing passes respectively. 39 | -------------------------------------------------------------------------------- /advanced_source/ddp_pipeline.rst: -------------------------------------------------------------------------------- 1 | Training Transformer models using Distributed Data Parallel and Pipeline Parallelism 2 | ==================================================================================== 3 | 4 | This tutorial has been deprecated. 5 | 6 | Redirecting to the latest parallelism APIs in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /advanced_source/dispatcher/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | cmake_minimum_required(VERSION 3.1 FATAL_ERROR) 2 | project(dispatcher) 3 | 4 | find_package(Torch REQUIRED) 5 | 6 | add_library(dispatcher SHARED op.cpp) 7 | target_compile_features(dispatcher PRIVATE cxx_std_14) 8 | target_link_libraries(dispatcher "${TORCH_LIBRARIES}") 9 | -------------------------------------------------------------------------------- /advanced_source/dispatcher/test.py: -------------------------------------------------------------------------------- 1 | import torch 2 | 3 | torch.ops.load_library("build/libdispatcher.so") 4 | print(torch.ops.myops.myadd(torch.randn(32, 32), torch.rand(32, 32))) 5 | """ 6 | # Doesn't currently work, because Python frontend on torch.ops doesn't 7 | # support names (for not a good reason?) 8 | x = torch.randn(32, 32, names=('A', 'B')) 9 | y = torch.rand(32, 32, names=('A', 'B')) 10 | print(torch.ops.myops.myadd(x, y)) 11 | """ 12 | -------------------------------------------------------------------------------- /advanced_source/torch_script_custom_classes/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | cmake_minimum_required(VERSION 3.1 FATAL_ERROR) 2 | project(infer) 3 | 4 | find_package(Torch REQUIRED) 5 | 6 | add_subdirectory(custom_class_project) 7 | 8 | # Define our library target 9 | add_executable(infer infer.cpp) 10 | set(CMAKE_CXX_STANDARD 14) 11 | # Link against LibTorch 12 | target_link_libraries(infer "${TORCH_LIBRARIES}") 13 | # This is where we link in our libcustom_class code, making our 14 | # custom class available in our binary. 15 | target_link_libraries(infer -Wl,--no-as-needed custom_class) 16 | -------------------------------------------------------------------------------- /advanced_source/torch_script_custom_classes/custom_class_project/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | cmake_minimum_required(VERSION 3.1 FATAL_ERROR) 2 | project(custom_class) 3 | 4 | find_package(Torch REQUIRED) 5 | 6 | # Define our library target 7 | add_library(custom_class SHARED class.cpp) 8 | set(CMAKE_CXX_STANDARD 14) 9 | # Link against LibTorch 10 | target_link_libraries(custom_class "${TORCH_LIBRARIES}") 11 | -------------------------------------------------------------------------------- /advanced_source/torch_script_custom_classes/custom_class_project/export_attr.py: -------------------------------------------------------------------------------- 1 | # export_attr.py 2 | import torch 3 | 4 | torch.classes.load_library('build/libcustom_class.so') 5 | 6 | 7 | class Foo(torch.nn.Module): 8 | def __init__(self): 9 | super().__init__() 10 | self.stack = torch.classes.my_classes.MyStackClass(["just", "testing"]) 11 | 12 | def forward(self, s: str) -> str: 13 | return self.stack.pop() + s 14 | 15 | 16 | scripted_foo = torch.jit.script(Foo()) 17 | 18 | scripted_foo.save('foo.pt') 19 | loaded = torch.jit.load('foo.pt') 20 | 21 | print(loaded.stack.pop()) 22 | -------------------------------------------------------------------------------- /advanced_source/torch_script_custom_classes/custom_class_project/save.py: -------------------------------------------------------------------------------- 1 | import torch 2 | 3 | torch.classes.load_library('build/libcustom_class.so') 4 | 5 | 6 | class Foo(torch.nn.Module): 7 | def __init__(self): 8 | super().__init__() 9 | 10 | def forward(self, s: str) -> str: 11 | stack = torch.classes.my_classes.MyStackClass(["hi", "mom"]) 12 | return stack.pop() + s 13 | 14 | 15 | scripted_foo = torch.jit.script(Foo()) 16 | print(scripted_foo.graph) 17 | 18 | scripted_foo.save('foo.pt') 19 | -------------------------------------------------------------------------------- /advanced_source/torch_script_custom_classes/infer.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include 4 | #include 5 | 6 | int main(int argc, const char* argv[]) { 7 | torch::jit::Module module; 8 | try { 9 | // Deserialize the ScriptModule from a file using torch::jit::load(). 10 | module = torch::jit::load("foo.pt"); 11 | } 12 | catch (const c10::Error& e) { 13 | std::cerr << "error loading the model\n"; 14 | return -1; 15 | } 16 | 17 | std::vector inputs = {"foobarbaz"}; 18 | auto output = module.forward(inputs).toString(); 19 | std::cout << output->string() << std::endl; 20 | } 21 | -------------------------------------------------------------------------------- /advanced_source/torch_script_custom_classes/run.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -ex 4 | 5 | rm -rf build 6 | rm -rf custom_class_project/build 7 | 8 | pushd custom_class_project 9 | mkdir build 10 | (cd build && cmake CXXFLAGS="-DNO_PICKLE" -DCMAKE_PREFIX_PATH="$(python -c 'import torch.utils; print(torch.utils.cmake_prefix_path)')" ..) 11 | (cd build && make) 12 | python custom_test.py 13 | python save.py 14 | ! python export_attr.py 15 | popd 16 | 17 | mkdir build 18 | (cd build && cmake -DCMAKE_PREFIX_PATH="$(python -c 'import torch.utils; print(torch.utils.cmake_prefix_path)')" ..) 19 | (cd build && make) 20 | mv custom_class_project/foo.pt build/foo.pt 21 | (cd build && ./infer) 22 | -------------------------------------------------------------------------------- /advanced_source/torch_script_custom_classes/run2.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -ex 4 | 5 | rm -rf build 6 | rm -rf custom_class_project/build 7 | 8 | pushd custom_class_project 9 | mkdir build 10 | (cd build && cmake -DCMAKE_PREFIX_PATH="$(python -c 'import torch.utils; print(torch.utils.cmake_prefix_path)')" ..) 11 | (cd build && make) 12 | python export_attr.py 13 | popd 14 | -------------------------------------------------------------------------------- /advanced_source/torch_script_custom_ops/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | cmake_minimum_required(VERSION 3.1 FATAL_ERROR) 2 | project(warp_perspective) 3 | 4 | find_package(Torch REQUIRED) 5 | find_package(OpenCV REQUIRED) 6 | 7 | # Define our library target 8 | add_library(warp_perspective SHARED op.cpp) 9 | # Enable C++14 10 | target_compile_features(warp_perspective PRIVATE cxx_std_14) 11 | # Link against LibTorch 12 | target_link_libraries(warp_perspective "${TORCH_LIBRARIES}") 13 | # Link against OpenCV 14 | target_link_libraries(warp_perspective opencv_core opencv_imgproc) 15 | -------------------------------------------------------------------------------- /advanced_source/torch_script_custom_ops/op.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | 4 | // BEGIN warp_perspective 5 | torch::Tensor warp_perspective(torch::Tensor image, torch::Tensor warp) { 6 | // BEGIN image_mat 7 | cv::Mat image_mat(/*rows=*/image.size(0), 8 | /*cols=*/image.size(1), 9 | /*type=*/CV_32FC1, 10 | /*data=*/image.data_ptr()); 11 | // END image_mat 12 | 13 | // BEGIN warp_mat 14 | cv::Mat warp_mat(/*rows=*/warp.size(0), 15 | /*cols=*/warp.size(1), 16 | /*type=*/CV_32FC1, 17 | /*data=*/warp.data_ptr()); 18 | // END warp_mat 19 | 20 | // BEGIN output_mat 21 | cv::Mat output_mat; 22 | cv::warpPerspective(image_mat, output_mat, warp_mat, /*dsize=*/{8, 8}); 23 | // END output_mat 24 | 25 | // BEGIN output_tensor 26 | torch::Tensor output = torch::from_blob(output_mat.ptr(), /*sizes=*/{8, 8}); 27 | return output.clone(); 28 | // END output_tensor 29 | } 30 | // END warp_perspective 31 | 32 | // BEGIN registry 33 | TORCH_LIBRARY(my_ops, m) { 34 | m.def("warp_perspective", warp_perspective); 35 | } 36 | // END registry 37 | -------------------------------------------------------------------------------- /advanced_source/torch_script_custom_ops/smoke_test.py: -------------------------------------------------------------------------------- 1 | import torch 2 | torch.ops.load_library("build/libwarp_perspective.so") 3 | print(torch.ops.my_ops.warp_perspective) 4 | -------------------------------------------------------------------------------- /advanced_source/torch_script_custom_ops/test.py: -------------------------------------------------------------------------------- 1 | import torch 2 | 3 | 4 | print("BEGIN preamble") 5 | torch.ops.load_library("build/libwarp_perspective.so") 6 | print(torch.ops.my_ops.warp_perspective(torch.randn(32, 32), torch.rand(3, 3))) 7 | print("END preamble") 8 | 9 | 10 | # BEGIN compute 11 | def compute(x, y, z): 12 | return x.matmul(y) + torch.relu(z) 13 | # END compute 14 | 15 | 16 | print("BEGIN trace") 17 | inputs = [torch.randn(4, 8), torch.randn(8, 5), torch.randn(4, 5)] 18 | trace = torch.jit.trace(compute, inputs) 19 | print(trace.graph) 20 | print("END trace") 21 | 22 | 23 | # BEGIN compute2 24 | def compute(x, y, z): 25 | x = torch.ops.my_ops.warp_perspective(x, torch.eye(3)) 26 | return x.matmul(y) + torch.relu(z) 27 | # END compute2 28 | 29 | 30 | print("BEGIN trace2") 31 | inputs = [torch.randn(4, 8), torch.randn(8, 5), torch.randn(8, 5)] 32 | trace = torch.jit.trace(compute, inputs) 33 | print(trace.graph) 34 | print("END trace2") 35 | -------------------------------------------------------------------------------- /advanced_source/transformer__timeseries_cpp_tutorial/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | cmake_minimum_required(VERSION 3.0 FATAL_ERROR) 2 | project(custom_ops) 3 | 4 | find_package(Torch REQUIRED) 5 | 6 | add_executable(transformer_ts transformer_timeseries.cpp) 7 | target_link_libraries(transformer_ts "${TORCH_LIBRARIES}") 8 | set_property(TARGET transformer_ts PROPERTY CXX_STANDARD 14) 9 | -------------------------------------------------------------------------------- /beginner_source/README.txt: -------------------------------------------------------------------------------- 1 | Beginner Tutorials 2 | ------------------ 3 | 4 | 1. blitz/* and deep_learning_60min_blitz.rst 5 | Deep Learning with PyTorch: A 60 Minute Blitz 6 | https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html 7 | 8 | 2. former_torches/* and former_torchies_tutorial.rst 9 | PyTorch for Former Torch Users 10 | https://pytorch.org/tutorials/beginner/former_torchies_tutorial.html 11 | 12 | 3. examples_*/* and pytorch_with_examples.rst 13 | Learning PyTorch with Examples 14 | https://pytorch.org/tutorials/beginner/pytorch_with_examples.html 15 | 16 | 4. transfer_learning_tutorial.py 17 | Transfer Learning Tutorial 18 | https://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html 19 | 20 | 5. nlp/* and deep_learning_nlp_tutorial.rst 21 | Deep Learning for NLP with Pytorch 22 | https://pytorch.org/tutorials/beginner/deep_learning_nlp_tutorial.html 23 | -------------------------------------------------------------------------------- /beginner_source/audio_data_augmentation_tutorial.rst: -------------------------------------------------------------------------------- 1 | Audio Data Augmentation 2 | ======================= 3 | 4 | This tutorial has been moved to https://pytorch.org/audio/stable/tutorials/audio_data_augmentation_tutorial.html 5 | 6 | It will redirect in 3 seconds. 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /beginner_source/audio_datasets_tutorial.rst: -------------------------------------------------------------------------------- 1 | Audio Datasets 2 | ============== 3 | 4 | This tutorial has been moved to https://pytorch.org/audio/stable/tutorials/audio_datasets_tutorial.html 5 | 6 | It will redirect in 3 seconds. 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /beginner_source/audio_feature_augmentation_tutorial.rst: -------------------------------------------------------------------------------- 1 | Audio Feature Augmentation 2 | ========================== 3 | 4 | This tutorial has been moved to https://pytorch.org/audio/stable/tutorials/audio_data_augmentation_tutorial.html 5 | 6 | It will redirect in 3 seconds. 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /beginner_source/audio_feature_extractions_tutorial.rst: -------------------------------------------------------------------------------- 1 | Audio Feature Extractions 2 | ========================= 3 | 4 | This tutorial has been moved to https://pytorch.org/audio/stable/tutorials/audio_feature_extractions_tutorial.html 5 | 6 | It will redirect in 3 seconds. 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /beginner_source/audio_io_tutorial.rst: -------------------------------------------------------------------------------- 1 | Audio I/O 2 | ========= 3 | 4 | This tutorial has been moved to https://pytorch.org/audio/stable/tutorials/audio_io_tutorial.html 5 | 6 | It will redirect in 3 seconds. 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /beginner_source/audio_resampling_tutorial.rst: -------------------------------------------------------------------------------- 1 | Audio Resampling 2 | ================ 3 | 4 | This tutorial has been moved to `a new location `_ 5 | You will be redirected in 3 seconds. 6 | 7 | .. raw:: html 8 | 9 | 10 | -------------------------------------------------------------------------------- /beginner_source/basics/README.txt: -------------------------------------------------------------------------------- 1 | Learn the Basics 2 | ------------------ 3 | 4 | 1. intro.py 5 | Learn the Basics 6 | https://pytorch.org/tutorials/beginner/basics/intro.html 7 | 8 | 2. quickstart_tutorial.py 9 | Quickstart 10 | https://pytorch.org/tutorials/beginner/basics/quickstart_tutorial.html 11 | 12 | 3. tensorqs_tutorial.py 13 | Tensors 14 | https://pytorch.org/tutorials/beginner/basics/tensor_tutorial.html 15 | 16 | 4. data_tutorial.py 17 | Datasets & DataLoaders 18 | https://pytorch.org/tutorials/beginner/basics/data_tutorial.html 19 | 20 | 5. transforms_tutorial.py 21 | Transforms 22 | https://pytorch.org/tutorials/beginner/basics/transforms_tutorial.html 23 | 24 | 6. buildmodel_tutorial.py 25 | Building the Neural Network 26 | https://pytorch.org/tutorials/beginner/basics/buildmodel_tutorial.html 27 | 28 | 7. autogradqs_tutorial.py 29 | Automatic Differentiation with torch.autograd_tutorial 30 | https://pytorch.org/tutorials/beginner/basics/autograd_tutorial.html 31 | 32 | 8. optimization_tutorial.py 33 | Optimizing Model Parameters 34 | https://pytorch.org/tutorials/beginner/basics/optimization_tutorial.html 35 | 36 | 9. saveloadrun_tutorial.py 37 | Save and Load the Model 38 | https://pytorch.org/tutorials/beginner/basics/saveloadrun_tutorial.html 39 | -------------------------------------------------------------------------------- /beginner_source/basics/qs_toc.txt: -------------------------------------------------------------------------------- 1 | | 0. `Quickstart `_ 2 | | 1. `Tensors `_ 3 | | 2. `Datasets and DataLoaders `_ 4 | | 3. `Transforms `_ 5 | | 4. `Build Model `_ 6 | | 5. `Automatic Differentiation `_ 7 | | 6. `Optimization Loop `_ 8 | | 7. `Save, Load and Use Model `_ 9 | -------------------------------------------------------------------------------- /beginner_source/bettertransformer_tutorial.rst: -------------------------------------------------------------------------------- 1 | Fast Transformer Inference with Better Transformer 2 | ================================================== 3 | 4 | This tutorial has been deprecated. 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /beginner_source/blitz/README.txt: -------------------------------------------------------------------------------- 1 | Deep Learning with PyTorch: A 60 Minute Blitz 2 | --------------------------------------------- 3 | 4 | 1. tensor_tutorial.py 5 | What is PyTorch? 6 | https://pytorch.org/tutorials/beginner/blitz/tensor_tutorial.html 7 | 8 | 2. autograd_tutorial.py 9 | Autograd: Automatic Differentiation 10 | https://pytorch.org/tutorials/beginner/blitz/autograd_tutorial.html 11 | 12 | 3. neural_networks_tutorial.py 13 | Neural Networks 14 | https://pytorch.org/tutorials/beginner/blitz/neural_networks_tutorial.html# 15 | 16 | 4. cifar10_tutorial.py 17 | Training a Classifier 18 | https://pytorch.org/tutorials/beginner/blitz/cifar10_tutorial.html 19 | 20 | 5. data_parallel_tutorial.py 21 | Optional: Data Parallelism 22 | https://pytorch.org/tutorials/beginner/blitz/data_parallel_tutorial.html 23 | 24 | -------------------------------------------------------------------------------- /beginner_source/deeplabv3_on_android.rst: -------------------------------------------------------------------------------- 1 | Image Segmentation DeepLabV3 on Android 2 | ================================================= 3 | 4 | PyTorch Mobile is no longer actively supported. Please check out `ExecuTorch `__. 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /beginner_source/deeplabv3_on_ios.rst: -------------------------------------------------------------------------------- 1 | Image Segmentation DeepLabV3 on iOS 2 | ============================================== 3 | 4 | PyTorch Mobile is no longer actively supported. Please check out `ExecuTorch `__. 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /beginner_source/examples_autograd/README.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/pytorch/tutorials/fee83dd33ab594bcdf49bd9c9da3fa2b07ffe219/beginner_source/examples_autograd/README.txt -------------------------------------------------------------------------------- /beginner_source/examples_nn/README.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/pytorch/tutorials/fee83dd33ab594bcdf49bd9c9da3fa2b07ffe219/beginner_source/examples_nn/README.txt -------------------------------------------------------------------------------- /beginner_source/examples_tensor/README.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/pytorch/tutorials/fee83dd33ab594bcdf49bd9c9da3fa2b07ffe219/beginner_source/examples_tensor/README.txt -------------------------------------------------------------------------------- /beginner_source/finetuning_torchvision_models_tutorial.rst: -------------------------------------------------------------------------------- 1 | Finetuning Torchvision Models 2 | ============================= 3 | 4 | This tutorial has been moved to https://pytorch.org/tutorials/intermediate/torchvision_tutorial.html 5 | 6 | It will redirect in 3 seconds. 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /beginner_source/former_torchies/autograd_tutorial_old.rst: -------------------------------------------------------------------------------- 1 | Autograd 2 | ============== 3 | 4 | This tutorial is out of date. You'll be redirected to the new tutorial in 3 seconds: https://pytorch.org/tutorials/beginner/basics/autogradqs_tutorial.html 5 | 6 | .. raw:: html 7 | 8 | 9 | -------------------------------------------------------------------------------- /beginner_source/former_torchies/nnft_tutorial.rst: -------------------------------------------------------------------------------- 1 | nn Package 2 | =============== 3 | 4 | This tutorial is out of date. You'll be redirected to the new tutorial in 3 seconds: https://pytorch.org/tutorials/beginner/nn_tutorial.html 5 | 6 | .. raw:: html 7 | 8 | 9 | -------------------------------------------------------------------------------- /beginner_source/former_torchies/parallelism_tutorial.rst: -------------------------------------------------------------------------------- 1 | Multi-GPU Examples 2 | ============== 3 | 4 | This tutorial is out of date. You'll be redirected to the new tutorial in 3 seconds: https://pytorch.org/tutorials/beginner/blitz/data_parallel_tutorial.html 5 | 6 | .. raw:: html 7 | 8 | 9 | -------------------------------------------------------------------------------- /beginner_source/former_torchies/tensor_tutorial_old.rst: -------------------------------------------------------------------------------- 1 | Tensors 2 | ============== 3 | 4 | This tutorial is out of date. You'll be redirected to the new tutorial in 3 seconds: https://pytorch.org/tutorials/beginner/basics/tensorqs_tutorial.html 5 | 6 | .. raw:: html 7 | 8 | 9 | -------------------------------------------------------------------------------- /beginner_source/former_torchies_tutorial.rst: -------------------------------------------------------------------------------- 1 | PyTorch for Former Torch Users 2 | ============== 3 | This tutorial is out of date. Please check out the PyTorch tutorials here: https://pytorch.org/tutorials/ 4 | 5 | You will be redirected in 3 seconds. 6 | 7 | .. raw:: html 8 | 9 | 10 | -------------------------------------------------------------------------------- /beginner_source/hybrid_frontend/README.txt: -------------------------------------------------------------------------------- 1 | Hybrid Frontend Tutorials 2 | ------------------------- 3 | 4 | 1. learning_hybrid_frontend_through_example_tutorial.py 5 | Learning Hybrid Frontend Through Example 6 | https://pytorch.org/tutorials/beginner/hybrid_frontend/learning_hybrid_frontend_through_example_tutorial.html 7 | 8 | 2. introduction_to_hybrid_frontend_tutorial.py 9 | Introduction to Hybrid Frontend 10 | https://pytorch.org/tutorials/beginner/hybrid_frontend/introduction_to_hybrid_frontend_tutorial.html 11 | -------------------------------------------------------------------------------- /beginner_source/hybrid_frontend_tutorial.rst: -------------------------------------------------------------------------------- 1 | Hybrid Frontend Tutorials 2 | ------------------------- 3 | **Authors**: `Nathan Inkawhich `_ and `Matthew Inkawhich `_ 4 | 5 | In this set of tutorials, you will learn the following: 6 | 7 | 1. What the hybrid frontend is and the suggested workflow 8 | 2. Basic syntax 9 | 3. How to transition an eager model to graph mode 10 | 11 | 12 | .. toctree:: 13 | :hidden: 14 | 15 | /beginner/hybrid_frontend/learning_hybrid_frontend_through_example_tutorial 16 | 17 | .. galleryitem:: /beginner/hybrid_frontend/learning_hybrid_frontend_through_example_tutorial.py 18 | 19 | .. raw:: html 20 | 21 |
22 | -------------------------------------------------------------------------------- /beginner_source/introyt.rst: -------------------------------------------------------------------------------- 1 | Introduction to PyTorch - YouTube Series 2 | ======================================== 3 | 4 | This page has been moved. 5 | 6 | Redirecting now... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /beginner_source/introyt/README.txt: -------------------------------------------------------------------------------- 1 | Introduction to PyTorch on YouTube 2 | ---------------------------------- 3 | 4 | 1. introyt.py 5 | Introduction to PyTorch - Youtube Series 6 | https://pytorch.org/tutorials/beginner/introyt/introyt.html 7 | 8 | 2. introyt1_tutorial.py 9 | Introduction to PyTorch 10 | https://pytorch.org/tutorials/beginner/introyt/introyt1_tutorial.html 11 | 12 | 3. tensors_deeper_tutorial.py 13 | PyTorch Tensors 14 | https://pytorch.org/tutorials/beginner/introyt/tensors_deeper_tutorial.html 15 | 16 | 4. autogradyt_tutorial.py 17 | The Fundamentals of Autograd 18 | https://pytorch.org/tutorials/beginner/introyt/autogradyt_tutorial.html 19 | 20 | 5. modelsyt_tutorial.py 21 | Building Models with PyTorch 22 | https://pytorch.org/tutorials/beginner/introyt/modelsyt_tutorial.html 23 | 24 | 6. tensorboardyt_tutorial.py 25 | PyTorch TensorBoard Support 26 | https://pytorch.org/tutorials/beginner/introyt/tensorboardyt_tutorial.html 27 | 28 | 7. trainingyt_tutorial.py 29 | Training with PyTorch 30 | https://pytorch.org/tutorials/beginner/introyt/trainingyt_tutorial.html 31 | 32 | 8. captumyt_tutorial.py 33 | Model Understanding with Captum 34 | https://pytorch.org/tutorials/beginner/introyt/captumyt_tutorial.html 35 | -------------------------------------------------------------------------------- /beginner_source/introyt/tocyt.txt: -------------------------------------------------------------------------------- 1 | 1. `Introduction to PyTorch `_ 2 | 2. `Introduction to PyTorch Tensors `_ 3 | 3. `The Fundamentals of Autograd `_ 4 | 4. `Building Models with PyTorch `_ 5 | 5. `PyTorch TensorBoard Support `_ 6 | 6. `Training with PyTorch `_ 7 | 7. `Model Understanding with Captum `_ 8 | -------------------------------------------------------------------------------- /beginner_source/onnx/README.txt: -------------------------------------------------------------------------------- 1 | ONNX 2 | ---- 3 | 4 | 1. intro_onnx.py 5 | Introduction to ONNX 6 | https://pytorch.org/tutorials/beginner/onnx/intro_onnx.html 7 | 8 | 2. export_simple_model_to_onnx_tutorial.py 9 | Exporting a PyTorch model to ONNX 10 | https://pytorch.org/tutorials/beginner/onnx/export_simple_model_to_onnx_tutorial.html 11 | 12 | 3. onnx_registry_tutorial.py 13 | Extending the ONNX exporter operator support 14 | https://pytorch.org/tutorials/beginner/onnx/onnx_registry_tutorial.html 15 | 16 | 4. export_control_flow_model_to_onnx_tutorial.py 17 | Export a model with control flow to ONNX 18 | https://pytorch.org/tutorials/beginner/onnx/export_control_flow_model_to_onnx_tutorial.html -------------------------------------------------------------------------------- /beginner_source/onnx/onnx_toc.txt: -------------------------------------------------------------------------------- 1 | | 1. `Exporting a PyTorch model to ONNX `_ 2 | | 2. `Extending the ONNX exporter operator support `_ 3 | | 3. `Export a model with control flow to ONNX `_ -------------------------------------------------------------------------------- /beginner_source/t5_tutoria.rst: -------------------------------------------------------------------------------- 1 | T5-Base Model for Summarization, Sentiment Classification, and Translation 2 | ========================================================================== 3 | 4 | This tutorial has been deprecated. 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /beginner_source/text_sentiment_ngrams_tutorial.rst: -------------------------------------------------------------------------------- 1 | :orphan: 2 | 3 | Text classification with the torchtext library 4 | ============================================== 5 | 6 | This tutorial has been deprecated. 7 | 8 | Redirecting in 3 seconds... 9 | 10 | .. raw:: html 11 | 12 | 13 | -------------------------------------------------------------------------------- /beginner_source/torchtext_custom_dataset_tutorial.rst: -------------------------------------------------------------------------------- 1 | :orphan: 2 | 3 | Preprocess custom text dataset using torchtext 4 | ============================================== 5 | 6 | This tutorial has been deprecated. 7 | 8 | Redirecting in 3 seconds... 9 | 10 | .. raw:: html 11 | 12 | 13 | -------------------------------------------------------------------------------- /beginner_source/transformer_tutorial.rst: -------------------------------------------------------------------------------- 1 | Language Modeling with ``nn.Transformer`` and torchtext 2 | ======================================================= 3 | 4 | The content is deprecated. 5 | 6 | .. raw:: html 7 | 8 | 9 | -------------------------------------------------------------------------------- /beginner_source/translation_transformer.rst: -------------------------------------------------------------------------------- 1 | Language Translation with ``nn.Transformer`` and torchtext 2 | ========================================================== 3 | 4 | This tutorial has been deprecated. 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /build.sh: -------------------------------------------------------------------------------- 1 | # TODO: make sure pytorch installed 2 | pip install -r requirements.txt 3 | make docs 4 | -------------------------------------------------------------------------------- /cleanup.sh: -------------------------------------------------------------------------------- 1 | rm -rf __pycache__/ _build/ advanced/ beginner/ intermediate/ 2 | -------------------------------------------------------------------------------- /intermediate_source/README.txt: -------------------------------------------------------------------------------- 1 | Intermediate tutorials 2 | ---------------------- 3 | 4 | 1. tensorboard_tutorial.py 5 | Classifying Names with a Character-Level RNN 6 | https://pytorch.org/tutorials/intermediate/tensorboard_tutorial.html 7 | 8 | 2. char_rnn_classification_tutorial.py 9 | Classifying Names with a Character-Level RNN 10 | https://pytorch.org/tutorials/intermediate/char_rnn_classification_tutorial.html 11 | 12 | 3. char_rnn_generation_tutorial.py 13 | Generating Names with a Character-Level RNN 14 | https://pytorch.org/tutorials/intermediate/char_rnn_generation_tutorial.html 15 | 16 | 4. seq2seq_translation_tutorial.py 17 | Translation with a Sequence to Sequence Network and Attention 18 | https://pytorch.org/tutorials/intermediate/seq2seq_translation_tutorial.html 19 | 20 | 5. reinforcement_q_learning.py 21 | Reinforcement Learning (DQN) Tutorial 22 | https://pytorch.org/tutorials/intermediate/reinforcement_q_learning.html 23 | 24 | 6. dist_tuto.rst 25 | Writing Distributed Applications with PyTorch 26 | https://pytorch.org/tutorials/intermediate/dist_tuto.html 27 | 28 | 7. spatial_transformer_tutorial 29 | Spatial Transformer Networks Tutorial 30 | https://pytorch.org/tutorials/intermediate/spatial_transformer_tutorial.html 31 | 32 | 8. nvfuser_intro_tutorial.py 33 | Introduction to nvFuser 34 | https://pytorch.org/tutorials/intermediate/nvfuser_intro_tutorial.html 35 | -------------------------------------------------------------------------------- /intermediate_source/dist_pipeline_parallel_tutorial.rst: -------------------------------------------------------------------------------- 1 | Distributed Pipeline Parallelism Using RPC 2 | ========================================== 3 | 4 | This tutorial has been deprecated. 5 | 6 | Redirecting to a newer tutorial in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /intermediate_source/forced_alignment_with_torchaudio_tutorial.rst: -------------------------------------------------------------------------------- 1 | Forced Alignment with Wav2Vec2 2 | ============================== 3 | 4 | This tutorial has been moved to https://pytorch.org/audio/stable/tutorials/forced_alignment_tutorial.html 5 | 6 | It will redirect in 3 seconds. 7 | 8 | .. raw:: html 9 | 10 | 11 | 12 | -------------------------------------------------------------------------------- /intermediate_source/model_parallel_tutorial.rst: -------------------------------------------------------------------------------- 1 | Single-Machine Model Parallel Best Practices 2 | ============================================ 3 | 4 | This tutorial has been deprecated. 5 | 6 | Redirecting to latest parallelism APIs in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /intermediate_source/nvfuser_intro_tutorial.rst: -------------------------------------------------------------------------------- 1 | Getting Started - Accelerate Your Scripts with nvFuser 2 | ====================================================== 3 | 4 | This tutorial has been deprecated. Redirecting to homepage in 3 seconds... 5 | 6 | .. raw:: html 7 | 8 | 9 | -------------------------------------------------------------------------------- /intermediate_source/pipeline_tutorial.rst: -------------------------------------------------------------------------------- 1 | Training Transformer models using Pipeline Parallelism 2 | ====================================================== 3 | 4 | This tutorial has been deprecated. 5 | 6 | Redirecting to the latest parallelism APIs in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | 12 | -------------------------------------------------------------------------------- /intermediate_source/speech_recognition_pipeline_tutorial.rst: -------------------------------------------------------------------------------- 1 | Speech Recognition with Wav2Vec2 2 | ================================ 3 | 4 | This tutorial has been moved to https://pytorch.org/audio/stable/tutorials/speech_recognition_pipeline_tutorial.html 5 | 6 | It will redirect in 3 seconds. 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /intermediate_source/text_to_speech_with_torchaudio.rst: -------------------------------------------------------------------------------- 1 | Text-to-speech with Tacotron2 2 | ============================= 3 | 4 | This tutorial has been moved to https://pytorch.org/audio/stable/tutorials/tacotron2_pipeline_tutorial.html 5 | 6 | It will redirect in 3 seconds. 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /intermediate_source/torch_export_nightly_tutorial.rst: -------------------------------------------------------------------------------- 1 | torch.export Nightly Tutorial 2 | ============================= 3 | 4 | This tutorial has been moved to https://pytorch.org/tutorials/intermediate/torch_export_tutorial.html 5 | 6 | It will redirect in 3 seconds. 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /intermediate_source/torchrec_tutorial.rst: -------------------------------------------------------------------------------- 1 | Introduction to TorchRec 2 | ======================== 3 | 4 | There is a newer tutorial on this topic. 5 | 6 | Redirecting... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /lychee.toml: -------------------------------------------------------------------------------- 1 | exclude_path = [".jenkins/build.sh", "_static/img/", "_static/images/"] 2 | -------------------------------------------------------------------------------- /prototype_source/README.md: -------------------------------------------------------------------------------- 1 | # Prototype Tutorials and Recipes 2 | 3 | This directory contains tutorials and recipes demonstrating prototype features in PyTorch. 4 | 5 | **Prototype features** are part of the release and are available as part of the binary distributions such as PyPI or Conda. To test these features you can, depending on the feature, build from the master branch or use the nightly wheels that are made available at pytorch.org. You can also by use the release wheels available from PyPI or Conda. Prototype features are provided as a technical preview and can be altered later on. The PyTorch team does not recommend using them in production pipelines. 6 | 7 | These are intentionally left out of the pytorch.org/tutorials build and will not show up on the website. 8 | 9 | *Level of commitment:* We are committing to gathering high bandwidth feedback only on these features. Based on this feedback and potential further engagement between community members, we as a community will decide if we want to upgrade the level of commitment or to fail fast. 10 | -------------------------------------------------------------------------------- /prototype_source/README.txt: -------------------------------------------------------------------------------- 1 | Prototype Tutorials 2 | ------------------ 3 | 1. distributed_rpc_profiling.rst 4 | Profiling PyTorch RPC-Based Workloads 5 | https://github.com/pytorch/tutorials/blob/main/prototype_source/distributed_rpc_profiling.rst 6 | 7 | 2. torchscript_freezing.py 8 | Model Freezing in TorchScript 9 | https://github.com/pytorch/tutorials/blob/main/prototype_source/torchscript_freezing.py 10 | 11 | 3. vulkan_workflow.rst 12 | Vulkan Backend User Workflow 13 | https://pytorch.org/tutorials/prototype/vulkan_workflow.html 14 | 15 | 4. flight_recorder_tutorial.rst 16 | Flight Recorder User Guide 17 | https://pytorch.org/tutorials/prototype/flight_recorder_tutorial.html 18 | 19 | 5. python_extension_autoload.rst 20 | Autoloading Out-of-Tree Extension 21 | https://pytorch.org/tutorials/prototype/python_extension_autoload.html 22 | -------------------------------------------------------------------------------- /prototype_source/distributed_rpc_profiling.rst: -------------------------------------------------------------------------------- 1 | Profiling PyTorch RPC-Based Workloads 2 | ====================================== 3 | 4 | This tutorial has been deprecated. 5 | 6 | Redirecting to homepage... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /prototype_source/inductor_windows_cpu.rst: -------------------------------------------------------------------------------- 1 | This tutorial has been moved to https://pytorch.org/tutorials/prototype/inductor_windows.html. 2 | 3 | Redirecting in 3 seconds... 4 | 5 | .. raw:: html 6 | 7 | 8 | -------------------------------------------------------------------------------- /prototype_source/ios_coreml_workflow.rst: -------------------------------------------------------------------------------- 1 | (Prototype) Convert Mobilenetv2 to Core ML 2 | ========================================== 3 | 4 | PyTorch Mobile is no longer actively supported. Please check out `ExecuTorch `__. 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /prototype_source/ios_gpu_workflow.rst: -------------------------------------------------------------------------------- 1 | (Prototype) Use iOS GPU in PyTorch 2 | ================================== 3 | 4 | PyTorch Mobile is no longer actively supported. Please check out `ExecuTorch `__. 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /prototype_source/lite_interpreter.rst: -------------------------------------------------------------------------------- 1 | (Prototype) Introduce lite interpreter workflow in Android and iOS 2 | ======================= 3 | 4 | This tutorial has been moved to https://pytorch.org/tutorials/recipes/mobile_interpreter.html 5 | 6 | 7 | .. raw:: html 8 | 9 | 10 | -------------------------------------------------------------------------------- /prototype_source/nnapi_mobilenetv2.rst: -------------------------------------------------------------------------------- 1 | (Beta) Convert MobileNetV2 to NNAPI 2 | ======================================== 3 | 4 | PyTorch Mobile is no longer actively supported. Please check out `ExecuTorch `__. 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /prototype_source/tracing_based_selective_build.rst: -------------------------------------------------------------------------------- 1 | (prototype) Tracing-based Selective Build Mobile Interpreter in Android and iOS 2 | =============================================================================== 3 | 4 | This tutorial has been replaced with a newer tutorial on this topic: https://pytorch.org/executorch/stable/kernel-library-selective-build.html 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /recipes_source/README.txt: -------------------------------------------------------------------------------- 1 | Recipes 2 | ------------------ 3 | 1. recipes/* and recipes_index.rst 4 | PyTorch Recipes 5 | https://pytorch.org/tutorials/recipes/recipes_index.html 6 | 7 | 8 | -------------------------------------------------------------------------------- /recipes_source/android_native_app_with_custom_op.rst: -------------------------------------------------------------------------------- 1 | Making Native Android Application that uses PyTorch prebuilt libraries 2 | ====================================================================== 3 | 4 | PyTorch Mobile is no longer actively supported. Please check out `ExecuTorch `__. 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /recipes_source/distributed_rpc_profiling.rst: -------------------------------------------------------------------------------- 1 | Profiling PyTorch RPC-Based Workloads 2 | ====================================== 3 | 4 | This tutorial has been deprecated. 5 | 6 | Redirecting to home page. 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /recipes_source/loading_data_recipe.rst: -------------------------------------------------------------------------------- 1 | Loading data in PyTorch 2 | ======================= 3 | 4 | The content is deprecated. See `Datasets & DataLoaders `__ instead. 5 | 6 | .. raw:: html 7 | 8 | 9 | -------------------------------------------------------------------------------- /recipes_source/mobile_interpreter.rst: -------------------------------------------------------------------------------- 1 | (beta) Efficient mobile interpreter in Android and iOS 2 | ================================================================== 3 | 4 | PyTorch Mobile is no longer actively supported. Please check out `ExecuTorch `__. 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /recipes_source/mobile_perf.rst: -------------------------------------------------------------------------------- 1 | Pytorch Mobile Performance Recipes 2 | ================================== 3 | 4 | PyTorch Mobile is no longer actively supported. Please check out `ExecuTorch `__. 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /recipes_source/model_preparation_android.rst: -------------------------------------------------------------------------------- 1 | Model Preparation for Android Recipe 2 | ===================================== 3 | 4 | PyTorch Mobile is no longer actively supported. Please check out `ExecuTorch `__. 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /recipes_source/model_preparation_ios.rst: -------------------------------------------------------------------------------- 1 | Model Preparation for iOS Recipe 2 | ===================================== 3 | 4 | PyTorch Mobile is no longer actively supported. Please check out `ExecuTorch `__. 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /recipes_source/ptmobile_recipes_summary.rst: -------------------------------------------------------------------------------- 1 | Summary of PyTorch Mobile Recipes 2 | ===================================== 3 | 4 | PyTorch Mobile is no longer actively supported. Please check out `ExecuTorch `__. 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /recipes_source/recipes/changing_default_device.py: -------------------------------------------------------------------------------- 1 | """ 2 | Changing default device 3 | ======================= 4 | 5 | It is common practice to write PyTorch code in a device-agnostic way, 6 | and then switch between CPU and CUDA depending on what hardware is available. 7 | Typically, to do this you might have used if-statements and ``cuda()`` calls 8 | to do this: 9 | 10 | .. note:: 11 | This recipe requires PyTorch 2.0.0 or later. 12 | 13 | """ 14 | import torch 15 | 16 | USE_CUDA = False 17 | 18 | mod = torch.nn.Linear(20, 30) 19 | if USE_CUDA: 20 | mod.cuda() 21 | 22 | device = 'cpu' 23 | if USE_CUDA: 24 | device = 'cuda' 25 | inp = torch.randn(128, 20, device=device) 26 | print(mod(inp).device) 27 | 28 | ################################################################### 29 | # PyTorch now also has a context manager which can take care of the 30 | # device transfer automatically. Here is an example: 31 | 32 | with torch.device('cuda'): 33 | mod = torch.nn.Linear(20, 30) 34 | print(mod.weight.device) 35 | print(mod(torch.randn(128, 20)).device) 36 | 37 | ######################################### 38 | # You can also set it globally like this: 39 | 40 | torch.set_default_device('cuda') 41 | 42 | mod = torch.nn.Linear(20, 30) 43 | print(mod.weight.device) 44 | print(mod(torch.randn(128, 20)).device) 45 | 46 | ################################################################ 47 | # This function imposes a slight performance cost on every Python 48 | # call to the torch API (not just factory functions). If this 49 | # is causing problems for you, please comment on 50 | # `this issue `__ 51 | -------------------------------------------------------------------------------- /recipes_source/recipes/save_load_across_devices.rst: -------------------------------------------------------------------------------- 1 | Save Load Across Devices 2 | ======================== 3 | 4 | This tutorial was deprecated. There is a newer tutorial that covers the same topic: https://pytorch.org/tutorials/beginner/saving_loading_models.html 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /recipes_source/recipes/saving_and_loading_a_general_checkpoint.rst: -------------------------------------------------------------------------------- 1 | Saving And Loading A General Checkpoint 2 | ======================================= 3 | 4 | This tutorial was deprecated. There is a newer tutorial that covers the same topic: https://pytorch.org/tutorials/beginner/saving_loading_models.html 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /recipes_source/recipes/saving_and_loading_models_for_inference.rst: -------------------------------------------------------------------------------- 1 | Saving And Loading Models For Inference 2 | ======================================= 3 | 4 | This tutorial was deprecated. There is a newer tutorial that covers the same topic: https://pytorch.org/tutorials/beginner/saving_loading_models.html 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /recipes_source/recipes/saving_multiple_models_in_one_file.rst: -------------------------------------------------------------------------------- 1 | Saving Multiple Models In One File 2 | ================================== 3 | 4 | This tutorial was deprecated. There is a newer tutorial that covers the same topic: https://pytorch.org/tutorials/beginner/saving_loading_models.html 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | -------------------------------------------------------------------------------- /recipes_source/script_optimized.rst: -------------------------------------------------------------------------------- 1 | Script and Optimize for Mobile Recipe 2 | ===================================== 3 | 4 | This tutorial has been deprecated. There is a new tutorial on this topic. 5 | 6 | Redirecting in 3 seconds... 7 | 8 | .. raw:: html 9 | 10 | 11 | 12 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | .ci/docker/requirements.txt -------------------------------------------------------------------------------- /runtime.txt: -------------------------------------------------------------------------------- 1 | 3.8 2 | --------------------------------------------------------------------------------