Merge branch 'master' into patch-1

Author: brianjo

.circleci/config.yml

@@ -562,10 +562,11 @@ workflows:
             branches:
               only:
                 - master
-      - pytorch_windows_build_worker:
-          name: win_test_worker
-          filters:
-            branches:
-              only:
-                - master
+#      - pytorch_windows_build_worker:
+#          name: win_test_worker
+#          type: approval
+#          filters:
+#            branches:
+#              only:
+#                - master
 

index.rst

@@ -206,7 +206,7 @@ Welcome to PyTorch Tutorials
    :header: (prototype) Introduction to Named Tensors in PyTorch
    :card_description: Learn how to use PyTorch to train a Deep Q Learning (DQN) agent on the CartPole-v0 task from the OpenAI Gym.
    :image: _static/img/thumbnails/cropped/experimental-Introduction-to-Named-Tensors-in-PyTorch.png
-   :link: intermediate/memory_format_tutorial.html
+   :link: /intermediate/named_tensor_tutorial.html
    :tags: Frontend-APIs,Named-Tensor,Best-Practice
 
 .. customcarditem::

intermediate_source/model_parallel_tutorial.py

@@ -86,7 +86,7 @@ def forward(self, x):
 #
 # It is also possible to run an existing single-GPU module on multiple GPUs
 # with just a few lines of changes. The code below shows how to decompose
-# ``torchvision.models.reset50()`` to two GPUs. The idea is to inherit from
+# ``torchvision.models.resnet50()`` to two GPUs. The idea is to inherit from
 # the existing ``ResNet`` module, and split the layers to two GPUs during
 # construction. Then, override the ``forward`` method to stitch two
 # sub-networks by moving the intermediate outputs accordingly.
@@ -136,7 +136,7 @@ def forward(self, x):
 #
 # Let us run an experiment to get a more quantitative view of the execution
 # time. In this experiment, we train ``ModelParallelResNet50`` and the existing
-# ``torchvision.models.reset50()`` by running random inputs and labels through
+# ``torchvision.models.resnet50()`` by running random inputs and labels through
 # them. After the training, the models will not produce any useful predictions,
 # but we can get a reasonable understanding of the execution times.
 

recipes_source/recipes_index.rst

@@ -1,6 +1,6 @@
 PyTorch Recipes
 ---------------------------------------------
-Recipes are bite-sized bite-sized, actionable examples of how to use specific PyTorch features, different from our full-length tutorials.
+Recipes are bite-sized, actionable examples of how to use specific PyTorch features, different from our full-length tutorials.
 
 .. raw:: html
 
@@ -40,14 +40,14 @@ Recipes are bite-sized bite-sized, actionable examples of how to use specific Py
 
 .. customcarditem::
    :header: Defining a Neural Network
-   :card_description: Learn how to use PyTorch's torch.nn package to create and define a neural network the MNIST dataset.
+   :card_description: Learn how to use PyTorch's torch.nn package to create and define a neural network for the MNIST dataset.
    :image: ../_static/img/thumbnails/cropped/defining-a-network.PNG
    :link: ../recipes/recipes/defining_a_neural_network.html
    :tags: Basics
 
 .. customcarditem::
    :header: What is a state_dict in PyTorch
-   :card_description: Learn how state_dict objects, Python dictionaries, are used in saving or loading models from PyTorch.
+   :card_description: Learn how state_dict objects and Python dictionaries are used in saving or loading models from PyTorch.
    :image: ../_static/img/thumbnails/cropped/what-is-a-state-dict.PNG
    :link: ../recipes/recipes/what_is_state_dict.html
    :tags: Basics
@@ -90,7 +90,7 @@ Recipes are bite-sized bite-sized, actionable examples of how to use specific Py
 
 .. customcarditem::
    :header: Zeroing out gradients in PyTorch
-   :card_description: Learn when you should zero out graidents and how doing so can help increase the accuracy of your model.
+   :card_description: Learn when you should zero out gradients and how doing so can help increase the accuracy of your model.
    :image: ../_static/img/thumbnails/cropped/zeroing-out-gradients.PNG
    :link: ../recipes/recipes/zeroing_out_gradients.html
    :tags: Basics