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.jenkins/validate_tutorials_built.py

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"prototype_source/nestedtensor",
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"recipes_source/recipes/saving_and_loading_models_for_inference",
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"recipes_source/recipes/saving_multiple_models_in_one_file",
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"recipes_source/recipes/loading_data_recipe",
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"recipes_source/recipes/tensorboard_with_pytorch",
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"recipes_source/recipes/what_is_state_dict",
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"recipes_source/recipes/profiler_recipe",

beginner_source/dist_overview.rst

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en-wordlist.txt

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deallocation
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decompositions
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decorrelated
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devicemesh
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deserialize
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deserialized
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desynchronization
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downsample
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downsamples
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dropdown
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dtensor
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duration
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elementwise
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embeddings
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pretrained
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prewritten
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primals
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processgroup
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profiler
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profilers
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protobuf
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reproducibility
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rescale
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rescaling
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reshard
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resnet
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restride
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rewinded
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runtime
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runtimes
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scalable
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sharded
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Sharding
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softmax
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sparsified
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sparsifier
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Loading data in PyTorch
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=======================
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The content is deprecated. See `Datasets & DataLoaders <https://pytorch.org/tutorials/beginner/basics/data_tutorial.html>`__ instead.
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.. raw:: html
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<meta http-equiv="Refresh" content="1; url='https://pytorch.org/tutorials/beginner/basics/data_tutorial.html'" />

recipes_source/recipes/README.txt

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PyTorch Recipes
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---------------------------------------------
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1. loading_data_recipe.py
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Loading Data in PyTorch
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https://pytorch.org/tutorials/recipes/recipes/loading_data_recipe.html
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2. defining_a_neural_network.py
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1. defining_a_neural_network.py
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Defining a Neural Network in PyTorch
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https://pytorch.org/tutorials/recipes/recipes/defining_a_neural_network.html
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3. what_is_state_dict.py
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2. what_is_state_dict.py
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What is a state_dict in PyTorch
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https://pytorch.org/tutorials/recipes/recipes/what_is_state_dict.html
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4. saving_and_loading_models_for_inference.py
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3. saving_and_loading_models_for_inference.py
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Saving and loading models for inference in PyTorch
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https://pytorch.org/tutorials/recipes/recipes/saving_and_loading_models_for_inference.html
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5. custom_dataset_transforms_loader.py
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4. custom_dataset_transforms_loader.py
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Developing Custom PyTorch Dataloaders
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https://pytorch.org/tutorials/recipes/recipes/custom_dataset_transforms_loader.html
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6. Captum_Recipe.py
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5. Captum_Recipe.py
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Model Interpretability using Captum
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https://pytorch.org/tutorials/recipes/recipes/Captum_Recipe.html
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7. dynamic_quantization.py
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6. dynamic_quantization.py
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Dynamic Quantization
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https://pytorch.org/tutorials/recipes/recipes/dynamic_quantization.html
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8. save_load_across_devices.py
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7. save_load_across_devices.py
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Saving and loading models across devices in PyTorch
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https://pytorch.org/tutorials/recipes/recipes/save_load_across_devices.html
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9. saving_and_loading_a_general_checkpoint.py
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8. saving_and_loading_a_general_checkpoint.py
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Saving and loading a general checkpoint in PyTorch
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https://pytorch.org/tutorials/recipes/recipes/saving_and_loading_a_general_checkpoint.html
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10. saving_and_loading_models_for_inference.py
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9. saving_and_loading_models_for_inference.py
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Saving and loading models for inference in PyTorch
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https://pytorch.org/tutorials/recipes/recipes/saving_and_loading_models_for_inference.html
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11. saving_multiple_models_in_one_file.py
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10. saving_multiple_models_in_one_file.py
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Saving and loading multiple models in one file using PyTorch
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https://pytorch.org/tutorials/recipes/recipes/saving_multiple_models_in_one_file.html
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12. warmstarting_model_using_parameters_from_a_different_model.py
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11. warmstarting_model_using_parameters_from_a_different_model.py
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Warmstarting models using parameters from different model
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https://pytorch.org/tutorials/recipes/recipes/warmstarting_model_using_parameters_from_a_different_model.html
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13. zeroing_out_gradients.py
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12. zeroing_out_gradients.py
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Zeroing out gradients
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https://pytorch.org/tutorials/recipes/recipes/zeroing_out_gradients.html
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14. mobile_perf.py
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13. mobile_perf.py
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PyTorch Mobile Performance Recipes
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https://pytorch.org/tutorials/recipes/mobile_perf.html
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15. amp_recipe.py
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14. amp_recipe.py
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Automatic Mixed Precision
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https://pytorch.org/tutorials/recipes/amp_recipe.html

recipes_source/recipes/loading_data_recipe.py

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