PyTorch Recipes — PyTorch Tutorials 2.6.0+cu124 documentation

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googleSearchboxText.style.fontSize = "1.2rem"; googleSearchboxText.style.color = '#262626'; } }; }); </script> </div> <p class="caption" role="heading"><span class="caption-text">PyTorch Recipes</span></p> <ul class="current"> <li class="toctree-l1 current"><a class="current reference internal" href="#">See All Recipes</a></li> <li class="toctree-l1"><a class="reference internal" href="../prototype/prototype_index.html">See All Prototype Recipes</a></li> </ul> <p class="caption" role="heading"><span class="caption-text">Introduction to PyTorch</span></p> <ul> <li class="toctree-l1"><a class="reference internal" href="../beginner/basics/intro.html">Learn the Basics</a><ul> <li class="toctree-l2"><a class="reference internal" href="../beginner/basics/quickstart_tutorial.html">Quickstart</a></li> <li class="toctree-l2"><a class="reference internal" href="../beginner/basics/tensorqs_tutorial.html">Tensors</a></li> <li class="toctree-l2"><a class="reference internal" href="../beginner/basics/data_tutorial.html">Datasets & DataLoaders</a></li> <li class="toctree-l2"><a class="reference internal" href="../beginner/basics/transforms_tutorial.html">Transforms</a></li> <li class="toctree-l2"><a class="reference internal" href="../beginner/basics/buildmodel_tutorial.html">Build the Neural Network</a></li> <li class="toctree-l2"><a class="reference internal" href="../beginner/basics/autogradqs_tutorial.html">Automatic Differentiation with <code class="docutils literal notranslate"><span class="pre">torch.autograd</span></code></a></li> <li class="toctree-l2"><a class="reference internal" href="../beginner/basics/optimization_tutorial.html">Optimizing Model Parameters</a></li> <li class="toctree-l2"><a class="reference internal" href="../beginner/basics/saveloadrun_tutorial.html">Save and Load the Model</a></li> </ul> </li> <li class="toctree-l1"><a class="reference internal" href="../beginner/introyt/introyt_index.html">Introduction to PyTorch - YouTube Series</a><ul> <li class="toctree-l2"><a class="reference internal" href="../beginner/introyt/introyt1_tutorial.html">Introduction to PyTorch</a></li> <li class="toctree-l2"><a class="reference internal" href="../beginner/introyt/tensors_deeper_tutorial.html">Introduction to PyTorch Tensors</a></li> <li class="toctree-l2"><a class="reference internal" href="../beginner/introyt/autogradyt_tutorial.html">The Fundamentals of Autograd</a></li> <li class="toctree-l2"><a class="reference internal" href="../beginner/introyt/modelsyt_tutorial.html">Building Models with PyTorch</a></li> <li class="toctree-l2"><a class="reference internal" href="../beginner/introyt/tensorboardyt_tutorial.html">PyTorch TensorBoard Support</a></li> <li class="toctree-l2"><a class="reference internal" href="../beginner/introyt/trainingyt.html">Training with PyTorch</a></li> <li class="toctree-l2"><a class="reference internal" href="../beginner/introyt/captumyt.html">Model Understanding with Captum</a></li> </ul> </li> </ul> <p class="caption" role="heading"><span class="caption-text">Learning PyTorch</span></p> <ul> <li class="toctree-l1"><a class="reference internal" href="../beginner/deep_learning_60min_blitz.html">Deep Learning with PyTorch: A 60 Minute Blitz</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/pytorch_with_examples.html">Learning PyTorch with Examples</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/nn_tutorial.html">What is <cite>torch.nn</cite> <em>really</em>?</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/nlp_from_scratch_index.html">NLP from Scratch</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/tensorboard_tutorial.html">Visualizing Models, Data, and Training with TensorBoard</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/pinmem_nonblock.html">A guide on good usage of <code class="docutils literal notranslate"><span class="pre">non_blocking</span></code> and <code class="docutils literal notranslate"><span class="pre">pin_memory()</span></code> in PyTorch</a></li> </ul> <p class="caption" role="heading"><span class="caption-text">Image and Video</span></p> <ul> <li class="toctree-l1"><a class="reference internal" href="../intermediate/torchvision_tutorial.html">TorchVision Object Detection Finetuning Tutorial</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/transfer_learning_tutorial.html">Transfer Learning for Computer Vision Tutorial</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/fgsm_tutorial.html">Adversarial Example Generation</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/dcgan_faces_tutorial.html">DCGAN Tutorial</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/spatial_transformer_tutorial.html">Spatial Transformer Networks Tutorial</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/vt_tutorial.html">Optimizing Vision Transformer Model for Deployment</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/tiatoolbox_tutorial.html">Whole Slide Image Classification Using PyTorch and TIAToolbox</a></li> </ul> <p class="caption" role="heading"><span class="caption-text">Audio</span></p> <ul> <li class="toctree-l1"><a class="reference internal" href="../beginner/audio_io_tutorial.html">Audio I/O</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/audio_resampling_tutorial.html">Audio Resampling</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/audio_data_augmentation_tutorial.html">Audio Data Augmentation</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/audio_feature_extractions_tutorial.html">Audio Feature Extractions</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/audio_feature_augmentation_tutorial.html">Audio Feature Augmentation</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/audio_datasets_tutorial.html">Audio Datasets</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/speech_recognition_pipeline_tutorial.html">Speech Recognition with Wav2Vec2</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/text_to_speech_with_torchaudio.html">Text-to-speech with Tacotron2</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/forced_alignment_with_torchaudio_tutorial.html">Forced Alignment with Wav2Vec2</a></li> </ul> <p class="caption" role="heading"><span class="caption-text">Backends</span></p> <ul> <li class="toctree-l1"><a class="reference internal" href="../beginner/onnx/intro_onnx.html">Introduction to ONNX</a></li> </ul> <p class="caption" role="heading"><span class="caption-text">Reinforcement Learning</span></p> <ul> <li class="toctree-l1"><a class="reference internal" href="../intermediate/reinforcement_q_learning.html">Reinforcement Learning (DQN) Tutorial</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/reinforcement_ppo.html">Reinforcement Learning (PPO) with TorchRL Tutorial</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/mario_rl_tutorial.html">Train a Mario-playing RL Agent</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/pendulum.html">Pendulum: Writing your environment and transforms with TorchRL</a></li> </ul> <p class="caption" role="heading"><span class="caption-text">Deploying PyTorch Models in Production</span></p> <ul> <li class="toctree-l1"><a class="reference internal" href="../beginner/onnx/intro_onnx.html">Introduction to ONNX</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/flask_rest_api_tutorial.html">Deploying PyTorch in Python via a REST API with Flask</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/Intro_to_TorchScript_tutorial.html">Introduction to TorchScript</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/cpp_export.html">Loading a TorchScript Model in C++</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/super_resolution_with_onnxruntime.html">(optional) Exporting a Model from PyTorch to ONNX and Running it using ONNX Runtime</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/realtime_rpi.html">Real Time Inference on Raspberry Pi 4 (30 fps!)</a></li> </ul> <p class="caption" role="heading"><span class="caption-text">Profiling PyTorch</span></p> <ul> <li class="toctree-l1"><a class="reference internal" href="../beginner/profiler.html">Profiling your PyTorch Module</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/hta_intro_tutorial.html">Introduction to Holistic Trace Analysis</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/hta_trace_diff_tutorial.html">Trace Diff using Holistic Trace Analysis</a></li> </ul> <p class="caption" role="heading"><span class="caption-text">Code Transforms with FX</span></p> <ul> <li class="toctree-l1"><a class="reference internal" href="../intermediate/fx_conv_bn_fuser.html">(beta) Building a Convolution/Batch Norm fuser in FX</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/fx_profiling_tutorial.html">(beta) Building a Simple CPU Performance Profiler with FX</a></li> </ul> <p class="caption" role="heading"><span class="caption-text">Frontend APIs</span></p> <ul> <li class="toctree-l1"><a class="reference internal" href="../intermediate/memory_format_tutorial.html">(beta) Channels Last Memory Format in PyTorch</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/forward_ad_usage.html">Forward-mode Automatic Differentiation (Beta)</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/jacobians_hessians.html">Jacobians, Hessians, hvp, vhp, and more: composing function transforms</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/ensembling.html">Model ensembling</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/per_sample_grads.html">Per-sample-gradients</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/cpp_frontend.html">Using the PyTorch C++ Frontend</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/torch-script-parallelism.html">Dynamic Parallelism in TorchScript</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/cpp_autograd.html">Autograd in C++ Frontend</a></li> </ul> <p class="caption" role="heading"><span class="caption-text">Extending PyTorch</span></p> <ul> <li class="toctree-l1"><a class="reference internal" href="../advanced/custom_ops_landing_page.html">PyTorch Custom Operators</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/python_custom_ops.html">Custom Python Operators</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/cpp_custom_ops.html">Custom C++ and CUDA Operators</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/custom_function_double_backward_tutorial.html">Double Backward with Custom Functions</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/custom_function_conv_bn_tutorial.html">Fusing Convolution and Batch Norm using Custom Function</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/cpp_extension.html">Custom C++ and CUDA Extensions</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/torch_script_custom_ops.html">Extending TorchScript with Custom C++ Operators</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/torch_script_custom_classes.html">Extending TorchScript with Custom C++ Classes</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/dispatcher.html">Registering a Dispatched Operator in C++</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/extend_dispatcher.html">Extending dispatcher for a new backend in C++</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/privateuseone.html">Facilitating New Backend Integration by PrivateUse1</a></li> </ul> <p class="caption" role="heading"><span class="caption-text">Model Optimization</span></p> <ul> <li class="toctree-l1"><a class="reference internal" href="../beginner/profiler.html">Profiling your PyTorch Module</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/tensorboard_profiler_tutorial.html">PyTorch Profiler With TensorBoard</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/hyperparameter_tuning_tutorial.html">Hyperparameter tuning with Ray Tune</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/vt_tutorial.html">Optimizing Vision Transformer Model for Deployment</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/parametrizations.html">Parametrizations Tutorial</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/pruning_tutorial.html">Pruning Tutorial</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/dynamic_quantization_tutorial.html">(beta) Dynamic Quantization on an LSTM Word Language Model</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/dynamic_quantization_bert_tutorial.html">(beta) Dynamic Quantization on BERT</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/quantized_transfer_learning_tutorial.html">(beta) Quantized Transfer Learning for Computer Vision Tutorial</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/static_quantization_tutorial.html">(beta) Static Quantization with Eager Mode in PyTorch</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/torchserve_with_ipex.html">Grokking PyTorch Intel CPU performance from first principles</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/torchserve_with_ipex_2.html">Grokking PyTorch Intel CPU performance from first principles (Part 2)</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/nvfuser_intro_tutorial.html">Getting Started - Accelerate Your Scripts with nvFuser</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/ax_multiobjective_nas_tutorial.html">Multi-Objective NAS with Ax</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/torch_compile_tutorial.html">Introduction to <code class="docutils literal notranslate"><span class="pre">torch.compile</span></code></a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/compiled_autograd_tutorial.html">Compiled Autograd: Capturing a larger backward graph for <code class="docutils literal notranslate"><span class="pre">torch.compile</span></code></a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/inductor_debug_cpu.html">Inductor CPU backend debugging and profiling</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/scaled_dot_product_attention_tutorial.html">(Beta) Implementing High-Performance Transformers with Scaled Dot Product Attention (SDPA)</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/knowledge_distillation_tutorial.html">Knowledge Distillation Tutorial</a></li> </ul> <p class="caption" role="heading"><span class="caption-text">Parallel and Distributed Training</span></p> <ul> <li class="toctree-l1"><a class="reference internal" href="../distributed/home.html">Distributed and Parallel Training Tutorials</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/dist_overview.html">PyTorch Distributed Overview</a></li> <li class="toctree-l1"><a class="reference internal" href="../beginner/ddp_series_intro.html">Distributed Data Parallel in PyTorch - Video Tutorials</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/model_parallel_tutorial.html">Single-Machine Model Parallel Best Practices</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/ddp_tutorial.html">Getting Started with Distributed Data Parallel</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/dist_tuto.html">Writing Distributed Applications with PyTorch</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/FSDP_tutorial.html">Getting Started with Fully Sharded Data Parallel(FSDP)</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/FSDP_advanced_tutorial.html">Advanced Model Training with Fully Sharded Data Parallel (FSDP)</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/TCPStore_libuv_backend.html">Introduction to Libuv TCPStore Backend</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/TP_tutorial.html">Large Scale Transformer model training with Tensor Parallel (TP)</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/pipelining_tutorial.html">Introduction to Distributed Pipeline Parallelism</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/process_group_cpp_extension_tutorial.html">Customize Process Group Backends Using Cpp Extensions</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/rpc_tutorial.html">Getting Started with Distributed RPC Framework</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/rpc_param_server_tutorial.html">Implementing a Parameter Server Using Distributed RPC Framework</a></li> <li class="toctree-l1"><a class="reference internal" href="../intermediate/rpc_async_execution.html">Implementing Batch RPC Processing Using Asynchronous Executions</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/rpc_ddp_tutorial.html">Combining Distributed DataParallel with Distributed RPC Framework</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/generic_join.html">Distributed Training with Uneven Inputs Using the Join Context Manager</a></li> </ul> <p class="caption" role="heading"><span class="caption-text">Edge with ExecuTorch</span></p> <ul> <li class="toctree-l1"><a class="reference external" href="https://pytorch.org/executorch/stable/tutorials/export-to-executorch-tutorial.html">Exporting to ExecuTorch Tutorial</a></li> <li class="toctree-l1"><a class="reference external" href=" https://pytorch.org/executorch/stable/running-a-model-cpp-tutorial.html">Running an ExecuTorch Model in C++ Tutorial</a></li> <li class="toctree-l1"><a class="reference external" href="https://pytorch.org/executorch/stable/tutorials/sdk-integration-tutorial.html">Using the ExecuTorch SDK to Profile a Model</a></li> <li class="toctree-l1"><a class="reference external" href="https://pytorch.org/executorch/stable/demo-apps-ios.html">Building an ExecuTorch iOS Demo App</a></li> <li class="toctree-l1"><a class="reference external" href="https://pytorch.org/executorch/stable/demo-apps-android.html">Building an ExecuTorch Android Demo App</a></li> <li class="toctree-l1"><a class="reference external" href="https://pytorch.org/executorch/stable/examples-end-to-end-to-lower-model-to-delegate.html">Lowering a Model as a Delegate</a></li> </ul> <p class="caption" role="heading"><span class="caption-text">Recommendation Systems</span></p> <ul> <li class="toctree-l1"><a class="reference internal" href="../intermediate/torchrec_intro_tutorial.html">Introduction to TorchRec</a></li> <li class="toctree-l1"><a class="reference internal" href="../advanced/sharding.html">Exploring TorchRec sharding</a></li> </ul> <p class="caption" role="heading"><span class="caption-text">Multimodality</span></p> <ul> <li class="toctree-l1"><a class="reference internal" href="../beginner/flava_finetuning_tutorial.html">TorchMultimodal Tutorial: Finetuning FLAVA</a></li> </ul> </div> </div> </nav> <div class="pytorch-container"> <div class="pytorch-page-level-bar" id="pytorch-page-level-bar"> <div class="pytorch-breadcrumbs-wrapper"> <div role="navigation" aria-label="breadcrumbs navigation"> <ul class="pytorch-breadcrumbs"> <li> <a href="../index.html"> Tutorials </a> > </li> <li>PyTorch Recipes</li> <li class="pytorch-breadcrumbs-aside"> <a href="../_sources/recipes/recipes_index.rst.txt" rel="nofollow"><img src="../_static/images/view-page-source-icon.svg"></a> </li> </ul> </div> </div> <div class="pytorch-shortcuts-wrapper" id="pytorch-shortcuts-wrapper"> Shortcuts </div> </div> <section data-toggle="wy-nav-shift" id="pytorch-content-wrap" class="pytorch-content-wrap"> <div class="pytorch-content-left"> <div class="pytorch-call-to-action-links"> <div id="tutorial-type">recipes/recipes_index</div> <div id="google-colab-link"> <img class="call-to-action-img" src="../_static/images/pytorch-colab.svg"/> <div class="call-to-action-desktop-view">Run in Google Colab</div> <div class="call-to-action-mobile-view">Colab</div> </div> <div id="download-notebook-link"> <img class="call-to-action-notebook-img" src="../_static/images/pytorch-download.svg"/> <div class="call-to-action-desktop-view">Download Notebook</div> <div class="call-to-action-mobile-view">Notebook</div> </div> <div id="github-view-link"> <img class="call-to-action-img" src="../_static/images/pytorch-github.svg"/> <div class="call-to-action-desktop-view">View on GitHub</div> <div class="call-to-action-mobile-view">GitHub</div> </div> </div>  <noscript><iframe src="https://www.googletagmanager.com/ns.html?id=GTM-T8XT4PS" height="0" width="0" style="display:none;visibility:hidden"></iframe></noscript>  <div class="rst-content"> <div role="main" class="main-content" itemscope="itemscope" itemtype="http://schema.org/Article"> <article itemprop="articleBody" id="pytorch-article" class="pytorch-article"> <div class="section" id="pytorch-recipes"> <h1>PyTorch Recipes<a class="headerlink" href="#pytorch-recipes" title="Permalink to this heading">¶</a></h1> <p>Recipes are bite-sized, actionable examples of how to use specific PyTorch features, different from our full-length tutorials.</p> </div> </div> <div id="tutorial-cards-container"> <nav class="navbar navbar-expand-lg navbar-light tutorials-nav col-12"> <div class="tutorial-tags-container"> <div id="dropdown-filter-tags"> <div class="tutorial-filter-menu"> <div class="tutorial-filter filter-btn all-tag-selected" data-tag="all">All</div> </div> </div> </div> </nav> <hr class="tutorials-hr"> <div class="row"> <div id="tutorial-cards"> <div class="list"><p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/recipes/defining_a_neural_network.html"> <div class="card-body"> <div class="card-title-container"> <h4>Defining a Neural Network</h4> </div> <p class="card-summary">Learn how to use PyTorch's torch.nn package to create and define a neural network for the MNIST dataset.</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/defining-a-network.PNG'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/recipes/what_is_state_dict.html"> <div class="card-body"> <div class="card-title-container"> <h4>What is a state_dict in PyTorch</h4> </div> <p class="card-summary">Learn how state_dict objects and Python dictionaries are used in saving or loading models from PyTorch.</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/what-is-a-state-dict.PNG'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/recipes/saving_and_loading_models_for_inference.html"> <div class="card-body"> <div class="card-title-container"> <h4>Saving and loading models for inference in PyTorch</h4> </div> <p class="card-summary">Learn about the two approaches for saving and loading models for inference in PyTorch - via the state_dict and via the entire model.</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/saving-and-loading-models-for-inference.PNG'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/recipes/saving_and_loading_a_general_checkpoint.html"> <div class="card-body"> <div class="card-title-container"> <h4>Saving and loading a general checkpoint in PyTorch</h4> </div> <p class="card-summary">Saving and loading a general checkpoint model for inference or resuming training can be helpful for picking up where you last left off. In this recipe, explore how to save and load multiple checkpoints.</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/saving-and-loading-general-checkpoint.PNG'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/recipes/saving_multiple_models_in_one_file.html"> <div class="card-body"> <div class="card-title-container"> <h4>Saving and loading multiple models in one file using PyTorch</h4> </div> <p class="card-summary">In this recipe, learn how saving and loading multiple models can be helpful for reusing models that you have previously trained.</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/saving-multiple-models.PNG'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/recipes/warmstarting_model_using_parameters_from_a_different_model.html"> <div class="card-body"> <div class="card-title-container"> <h4>Warmstarting model using parameters from a different model in PyTorch</h4> </div> <p class="card-summary">Learn how warmstarting the training process by partially loading a model or loading a partial model can help your model converge much faster than training from scratch.</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/warmstarting-models.PNG'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/recipes/save_load_across_devices.html"> <div class="card-body"> <div class="card-title-container"> <h4>Saving and loading models across devices in PyTorch</h4> </div> <p class="card-summary">Learn how saving and loading models across devices (CPUs and GPUs) is relatively straightforward using PyTorch.</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/saving-and-loading-models-across-devices.PNG'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/recipes/zeroing_out_gradients.html"> <div class="card-body"> <div class="card-title-container"> <h4>Zeroing out gradients in PyTorch</h4> </div> <p class="card-summary">Learn when you should zero out gradients and how doing so can help increase the accuracy of your model.</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/zeroing-out-gradients.PNG'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/recipes/benchmark.html"> <div class="card-body"> <div class="card-title-container"> <h4>PyTorch Benchmark</h4> </div> <p class="card-summary">Learn how to use PyTorch's benchmark module to measure and compare the performance of your code</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/profiler.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/recipes/timer_quick_start.html"> <div class="card-body"> <div class="card-title-container"> <h4>PyTorch Benchmark (quick start)</h4> </div> <p class="card-summary">Learn how to measure snippet run times and collect instructions.</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/profiler.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/recipes/profiler_recipe.html"> <div class="card-body"> <div class="card-title-container"> <h4>PyTorch Profiler</h4> </div> <p class="card-summary">Learn how to use PyTorch's profiler to measure operators time and memory consumption</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/profiler.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/profile_with_itt.html"> <div class="card-body"> <div class="card-title-container"> <h4>PyTorch Profiler with Instrumentation and Tracing Technology API (ITT API) support</h4> </div> <p class="card-summary">Learn how to use PyTorch's profiler with Instrumentation and Tracing Technology API (ITT API) to visualize operators labeling in Intel® VTune™ Profiler GUI</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/profiler.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/torch_compile_backend_ipex.html"> <div class="card-body"> <div class="card-title-container"> <h4>Torch Compile IPEX Backend</h4> </div> <p class="card-summary">Learn how to use torch.compile IPEX backend</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/generic-pytorch-logo.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Compiler> <div class="card tutorials-card"> <a href="../recipes/torch_compiler_set_stance_tutorial.html"> <div class="card-body"> <div class="card-title-container"> <h4>Dynamic Compilation Control with ``torch.compiler.set_stance``</h4> </div> <p class="card-summary">Learn how to use torch.compiler.set_stance</p> <p class="tags">Compiler</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/generic-pytorch-logo.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/recipes/reasoning_about_shapes.html"> <div class="card-body"> <div class="card-title-container"> <h4>Reasoning about Shapes in PyTorch</h4> </div> <p class="card-summary">Learn how to use the meta device to reason about shapes in your model.</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/generic-pytorch-logo.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/recipes/module_load_state_dict_tips.html"> <div class="card-body"> <div class="card-title-container"> <h4>Tips for Loading an nn.Module from a Checkpoint</h4> </div> <p class="card-summary">Learn tips for loading an nn.Module from a checkpoint.</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/generic-pytorch-logo.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/torch_logs.html"> <div class="card-body"> <div class="card-title-container"> <h4>(beta) Using TORCH_LOGS to observe torch.compile</h4> </div> <p class="card-summary">Learn how to use the torch logging APIs to observe the compilation process.</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/generic-pytorch-logo.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/recipes/swap_tensors.html"> <div class="card-body"> <div class="card-title-container"> <h4>Extension points in nn.Module for loading state_dict and tensor subclasses</h4> </div> <p class="card-summary">New extension points in nn.Module.</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/generic-pytorch-logo.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Basics> <div class="card tutorials-card"> <a href="../recipes/torch_export_aoti_python.html"> <div class="card-body"> <div class="card-title-container"> <h4>torch.export AOTInductor Tutorial for Python runtime</h4> </div> <p class="card-summary">Learn an end-to-end example of how to use AOTInductor for python runtime.</p> <p class="tags">Basics</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/generic-pytorch-logo.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Compiler,TorchCompile> <div class="card tutorials-card"> <a href="../recipes/torch_export_challenges_solutions.html"> <div class="card-body"> <div class="card-title-container"> <h4>Demonstration of torch.export flow, common 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class="tutorials-image"><img src='../_static/img/thumbnails/cropped/using-dynamic-post-training-quantization.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=TorchScript> <div class="card tutorials-card"> <a href="../recipes/torchscript_inference.html"> <div class="card-body"> <div class="card-title-container"> <h4>TorchScript for Deployment</h4> </div> <p class="card-summary">Learn how to export your trained model in TorchScript format and how to load your TorchScript model in C++ and do inference.</p> <p class="tags">TorchScript</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/torchscript_overview.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Production,TorchScript> <div class="card tutorials-card"> <a href="../recipes/deployment_with_flask.html"> <div class="card-body"> <div class="card-title-container"> <h4>Deploying with Flask</h4> </div> <p class="card-summary">Learn how to use Flask, a lightweight web server, to quickly setup a web API from your trained PyTorch model.</p> <p class="tags">Production,TorchScript</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/using-flask-create-restful-api.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Mobile,Model-Optimization> <div class="card tutorials-card"> <a href="../recipes/mobile_perf.html"> <div class="card-body"> <div class="card-title-container"> <h4>PyTorch Mobile Performance Recipes</h4> </div> <p class="card-summary">List of recipes for performance optimizations for using PyTorch on Mobile (Android and iOS).</p> <p class="tags">Mobile,Model-Optimization</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/mobile.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Mobile> <div class="card tutorials-card"> <a href="../recipes/android_native_app_with_custom_op.html"> <div class="card-body"> <div class="card-title-container"> <h4>Making Android Native Application That Uses PyTorch Android Prebuilt Libraries</h4> </div> <p class="card-summary">Learn how to make Android application from the scratch that uses LibTorch C++ API and uses TorchScript model with custom C++ operator.</p> <p class="tags">Mobile</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/android.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Mobile> <div class="card tutorials-card"> <a href="../recipes/fuse.html"> <div class="card-body"> <div class="card-title-container"> <h4>Fuse Modules recipe</h4> </div> <p class="card-summary">Learn how to fuse a list of PyTorch modules into a single module to reduce the model size before quantization.</p> <p class="tags">Mobile</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/mobile.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Mobile,Quantization> <div class="card tutorials-card"> <a href="../recipes/quantization.html"> <div class="card-body"> <div class="card-title-container"> <h4>Quantization for Mobile Recipe</h4> </div> <p class="card-summary">Learn how to reduce the model size and make it run faster without losing much on accuracy.</p> <p class="tags">Mobile,Quantization</p> <div class="tutorials-image"><img src='../_static/img/thumbnails/cropped/mobile.png'></div> </div> </a> </div> </div></p> <p><div class="col-md-12 tutorials-card-container" data-tags=Mobile> <div class="card tutorials-card"> <a href="../recipes/script_optimized.html"> <div class="card-body"> <div class="card-title-container"> <h4>Script and Optimize for Mobile</h4> </div> <p class="card-summary">Learn how to convert the model to TorchScipt and (optional) optimize it for mobile apps.</p> 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