Merge branch 'main' into improve_dqn_tutorial

Author: svekars

.jenkins/validate_tutorials_built.py

@@ -26,7 +26,6 @@
     "beginner_source/text_sentiment_ngrams_tutorial", # not building with 2.3 RC, might be able to turn on with GA
     "beginner_source/t5_tutorial", # re-enable after this is fixed: https://github.com/pytorch/text/issues/1756
     "intermediate_source/mnist_train_nas",  # used by ax_multiobjective_nas_tutorial.py
-    "intermediate_source/torchvision_tutorial", # disable due to RuntimeError: DataLoader worker (pid(s) 20092) exited unexpectedly
     "intermediate_source/fx_conv_bn_fuser",
     "intermediate_source/_torch_export_nightly_tutorial",  # does not work on release
     "advanced_source/super_resolution_with_onnxruntime",
@@ -38,7 +37,6 @@
     "prototype_source/nestedtensor",
     "recipes_source/recipes/saving_and_loading_models_for_inference",
     "recipes_source/recipes/saving_multiple_models_in_one_file",
-    "recipes_source/recipes/loading_data_recipe",
     "recipes_source/recipes/tensorboard_with_pytorch",
     "recipes_source/recipes/what_is_state_dict",
     "recipes_source/recipes/profiler_recipe",

CONTRIBUTING.md

@@ -326,9 +326,9 @@ example](https://github.com/pytorch/tutorials/blob/main/_static/img/thumbnails/c
 
 The following command builds an HTML version of the tutorial website.
 
-    ```
-    make html-noplot
-    ```
+```
+make html-noplot
+```
 
 This command does not run your tutorial code. To build the tutorial in a
 way that executes the code, use `make docs`. However, unless you have a

beginner_source/dist_overview.rst

@@ -0,0 +1,7 @@
+Language Modeling with ``nn.Transformer`` and torchtext
+===========================================================
+
+The content is deprecated.
+
+.. raw:: html
+   <meta http-equiv="refresh" content="0; url=https://pytorch.org/tutorials/">

beginner_source/transformer_tutorial.rst

@@ -335,6 +335,7 @@ dataset’s
 deallocation
 decompositions
 decorrelated
+devicemesh
 deserialize
 deserialized
 desynchronization
@@ -346,6 +347,7 @@ distractor
 downsample
 downsamples
 dropdown
+dtensor
 duration
 elementwise
 embeddings
@@ -482,6 +484,7 @@ prespecified
 pretrained
 prewritten
 primals
+processgroup
 profiler
 profilers
 protobuf
@@ -503,6 +506,7 @@ relu
 reproducibility
 rescale
 rescaling
+reshard
 resnet
 restride
 rewinded
@@ -515,6 +519,8 @@ runtime
 runtime
 runtimes
 scalable
+sharded
+Sharding
 softmax
 sparsified
 sparsifier

en-wordlist.txt

@@ -135,7 +135,7 @@ def init_model():
 ######################################################################
 # First, let's compare inference.
 #
-# Note that in the call to ``torch.compile``, we have have the additional
+# Note that in the call to ``torch.compile``, we have the additional
 # ``mode`` argument, which we will discuss below.
 
 model = init_model()

intermediate_source/torch_compile_tutorial.py

@@ -382,14 +382,12 @@ def get_transform(train):
 # expects during training and inference time on sample data.
 import utils
 
-
 model = torchvision.models.detection.fasterrcnn_resnet50_fpn(weights="DEFAULT")
 dataset = PennFudanDataset('data/PennFudanPed', get_transform(train=True))
 data_loader = torch.utils.data.DataLoader(
     dataset,
     batch_size=2,
     shuffle=True,
-    num_workers=4,
     collate_fn=utils.collate_fn
 )
 
@@ -433,15 +431,13 @@ def get_transform(train):
     dataset,
     batch_size=2,
     shuffle=True,
-    num_workers=4,
     collate_fn=utils.collate_fn
 )
 
 data_loader_test = torch.utils.data.DataLoader(
     dataset_test,
     batch_size=1,
     shuffle=False,
-    num_workers=4,
     collate_fn=utils.collate_fn
 )
 

intermediate_source/torchvision_tutorial.py

@@ -0,0 +1,8 @@
+Loading data in PyTorch
+=======================
+
+The content is deprecated. See `Datasets & DataLoaders <https://pytorch.org/tutorials/beginner/basics/data_tutorial.html>`__ instead.
+
+.. raw:: html
+
+   <meta http-equiv="Refresh" content="1; url='https://pytorch.org/tutorials/beginner/basics/data_tutorial.html'" />

recipes_source/loading_data_recipe.rst

@@ -1,62 +1,58 @@
 PyTorch Recipes
 ---------------------------------------------
-1. loading_data_recipe.py
-	 Loading Data in PyTorch
-         https://pytorch.org/tutorials/recipes/recipes/loading_data_recipe.html
-
-2. defining_a_neural_network.py
+1. defining_a_neural_network.py
 	 Defining a Neural Network in PyTorch
          https://pytorch.org/tutorials/recipes/recipes/defining_a_neural_network.html
 
-3. what_is_state_dict.py
+2. what_is_state_dict.py
 	 What is a state_dict in PyTorch
          https://pytorch.org/tutorials/recipes/recipes/what_is_state_dict.html
 
-4. saving_and_loading_models_for_inference.py
+3. saving_and_loading_models_for_inference.py
 	 Saving and loading models for inference in PyTorch
          https://pytorch.org/tutorials/recipes/recipes/saving_and_loading_models_for_inference.html
 
-5. custom_dataset_transforms_loader.py 
+4. custom_dataset_transforms_loader.py
 	 Developing Custom PyTorch Dataloaders
          https://pytorch.org/tutorials/recipes/recipes/custom_dataset_transforms_loader.html
 
 
-6. Captum_Recipe.py 
+5. Captum_Recipe.py
 	 Model Interpretability using Captum
          https://pytorch.org/tutorials/recipes/recipes/Captum_Recipe.html
 
-7. dynamic_quantization.py
+6. dynamic_quantization.py
          Dynamic Quantization
          https://pytorch.org/tutorials/recipes/recipes/dynamic_quantization.html
 
-8. save_load_across_devices.py
+7. save_load_across_devices.py
          Saving and loading models across devices in PyTorch
          https://pytorch.org/tutorials/recipes/recipes/save_load_across_devices.html
 
-9. saving_and_loading_a_general_checkpoint.py
+8. saving_and_loading_a_general_checkpoint.py
          Saving and loading a general checkpoint in PyTorch
          https://pytorch.org/tutorials/recipes/recipes/saving_and_loading_a_general_checkpoint.html
 
-10. saving_and_loading_models_for_inference.py
+9. saving_and_loading_models_for_inference.py
          Saving and loading models for inference in PyTorch
          https://pytorch.org/tutorials/recipes/recipes/saving_and_loading_models_for_inference.html
 
-11. saving_multiple_models_in_one_file.py
+10. saving_multiple_models_in_one_file.py
          Saving and loading multiple models in one file using PyTorch
          https://pytorch.org/tutorials/recipes/recipes/saving_multiple_models_in_one_file.html
 
-12. warmstarting_model_using_parameters_from_a_different_model.py 
+11. warmstarting_model_using_parameters_from_a_different_model.py
          Warmstarting models using parameters from different model
          https://pytorch.org/tutorials/recipes/recipes/warmstarting_model_using_parameters_from_a_different_model.html
 
-13. zeroing_out_gradients.py
+12. zeroing_out_gradients.py
          Zeroing out gradients
          https://pytorch.org/tutorials/recipes/recipes/zeroing_out_gradients.html
 
-14. mobile_perf.py
+13. mobile_perf.py
          PyTorch Mobile Performance Recipes
          https://pytorch.org/tutorials/recipes/mobile_perf.html
 
-15. amp_recipe.py
+14. amp_recipe.py
          Automatic Mixed Precision
          https://pytorch.org/tutorials/recipes/amp_recipe.html