Merge branch 'master' into change_conv_size

.circleci/config.yml

@@ -106,7 +106,7 @@ pytorch_tutorial_build_defaults: &pytorch_tutorial_build_defaults
         sudo pip -q install awscli==1.16.35
 
         if [ -n "${CUDA_VERSION}" ]; then
-          DRIVER_FN="NVIDIA-Linux-x86_64-440.59.run"
+          DRIVER_FN="NVIDIA-Linux-x86_64-460.39.run"
           wget "https://s3.amazonaws.com/ossci-linux/nvidia_driver/$DRIVER_FN"
           sudo /bin/bash "$DRIVER_FN" -s --no-drm || (sudo cat /var/log/nvidia-installer.log && false)
           nvidia-smi
@@ -116,13 +116,15 @@ pytorch_tutorial_build_defaults: &pytorch_tutorial_build_defaults
         export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_ECR_READ_ONLY}
         export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_ECR_READ_ONLY}
         eval $(aws ecr get-login --region us-east-1 --no-include-email)
+  - restore_cache:
+      key: v1.0-tutorial-{{ .Environment.CIRCLE_JOB }}
   - run:
       name: Build
       no_output_timeout: "20h"
       command: |
         set -e
 
-        export pyTorchDockerImageTag=291
+        export pyTorchDockerImageTag=9de29bef4a5dc0dd1dd19428d83e5a66a44a1ed2
         echo "PyTorchDockerImageTag: "${pyTorchDockerImageTag}
 
         cat >/home/circleci/project/ci_build_script.sh \<<EOL
@@ -164,21 +166,45 @@ pytorch_tutorial_build_defaults: &pytorch_tutorial_build_defaults
         fi
         set -x
 
+        # This also copies the cached build to docker.
         docker cp /home/circleci/project/. "$id:/var/lib/jenkins/workspace"
 
         export COMMAND='((echo "source ./workspace/env" && echo "sudo chown -R jenkins workspace && cd workspace && ./ci_build_script.sh") | docker exec -u jenkins -i "$id" bash) 2>&1'
         echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
 
+        # Copy the last build from docker
+        docker cp "$id:/var/lib/jenkins/workspace/_build" /home/circleci/project
+        docker cp "$id:/var/lib/jenkins/workspace/docs" /home/circleci/project
+        docker cp "$id:/var/lib/jenkins/workspace/advanced" /home/circleci/project
+        docker cp "$id:/var/lib/jenkins/workspace/beginner" /home/circleci/project
+        docker cp "$id:/var/lib/jenkins/workspace/intermediate" /home/circleci/project
+        docker cp "$id:/var/lib/jenkins/workspace/prototype" /home/circleci/project
+        docker cp "$id:/var/lib/jenkins/workspace/recipes" /home/circleci/project
+        docker cp "$id:/var/lib/jenkins/workspace/src" /home/circleci/project
+
+  - save_cache:
+      # Save to cache for incremental build
+      key: v1.0-tutorial-{{ .Environment.CIRCLE_JOB }}
+      paths:
+        - /home/circleci/project/_build
+        - /home/circleci/project/docs
+        - /home/circleci/project/advanced
+        - /home/circleci/project/beginner
+        - /home/circleci/project/intermediate
+        - /home/circleci/project/prototype
+        - /home/circleci/project/recipes
+        - /home/circleci/project/src
+
 pytorch_tutorial_build_worker_defaults: &pytorch_tutorial_build_worker_defaults
   environment:
-    DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda9-cudnn7-py3"
+    DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7"
     CUDA_VERSION: "9"
   resource_class: gpu.medium
   <<: *pytorch_tutorial_build_defaults
 
 pytorch_tutorial_build_manager_defaults: &pytorch_tutorial_build_manager_defaults
   environment:
-    DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda9-cudnn7-py3"
+    DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7"
   resource_class: medium
   <<: *pytorch_tutorial_build_defaults
 

.circleci/scripts/build_for_windows.sh

@@ -31,12 +31,13 @@ eval "$(conda shell.bash hook)"
 conda create -qyn testenv python=3.7
 conda activate testenv
 
-conda install sphinx
-pip install sphinx_gallery==0.3.1 sphinx-copybutton flask pandas spacy ipython scipy pySoundFile scikit-image
-pip install -e git+git://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme
-pip install ray[tune] tabulate
-conda install -yq -c pytorch "cudatoolkit=10.1" pytorch torchvision torchtext
-conda install torchaudio -c pytorch-test
+REQUIREMENTS="$(grep -v '^ *#\|^torch\|^torchaudio\|^torchvision|^torchtext' $PROJECT_DIR/requirements.txt  | grep .)"
+echo $REQUIREMENTS > requirements.txt
+pip install -r requirements.txt
+pip install pySoundFile
+# Force uninstall torch & related packages, we'll install them using conda later.
+pip uninstall -y torch torchvision torchtext
+conda install -yq -c pytorch "cudatoolkit=10.1" pytorch torchvision torchtext torchaudio
 python -m spacy download de
 python -m spacy download en
 pushd ${PROJECT_DIR}
@@ -47,6 +48,11 @@ if [[ "${CIRCLE_JOB}" == *worker_* ]]; then
   python $DIR/remove_runnable_code.py intermediate_source/model_parallel_tutorial.py intermediate_source/model_parallel_tutorial.py || true
   python $DIR/remove_runnable_code.py advanced_source/static_quantization_tutorial.py advanced_source/static_quantization_tutorial.py || true
   python $DIR/remove_runnable_code.py beginner_source/hyperparameter_tuning_tutorial.py beginner_source/hyperparameter_tuning_tutorial.py || true
+  python $DIR/remove_runnable_code.py beginner_source/audio_preprocessing_tutorial.py  beginner_source/audio_preprocessing_tutorial.py || true
+  python $DIR/remove_runnable_code.py beginner_source/dcgan_faces_tutorial.py  beginner_source/dcgan_faces_tutorial.py || true
+  python $DIR/remove_runnable_code.py intermediate_source/tensorboard_profiler_tutorial.py intermediate_source/tensorboard_profiler_tutorial.py || true
+  # Temp remove for mnist download issue. (Re-enabled for 1.8.1)
+  # python $DIR/remove_runnable_code.py beginner_source/fgsm_tutorial.py  beginner_source/fgsm_tutorial.py || true
 
   export WORKER_ID=$(echo "${CIRCLE_JOB}" | tr -dc '0-9')
   count=0

.devcontainer/Dockerfile

@@ -0,0 +1,8 @@
+FROM mcr.microsoft.com/vscode/devcontainers/python:3.8
+
+COPY requirements.txt /tmp/pip-tmp/
+
+RUN apt-get update && export DEBIAN_FRONTEND=noninteractive \
+    && apt-get install git gcc unzip make -y \
+    && pip3 install --disable-pip-version-check --no-cache-dir -r /tmp/pip-tmp/requirements.txt \
+    && rm -rf /tmp/pip-tmp

.devcontainer/devcontainer.json

@@ -0,0 +1,18 @@
+{
+  "name": "PyTorch Tutorials",
+  "build": {
+    "context": "..",
+    "dockerfile": "Dockerfile",
+    "args": {}
+  },
+  "settings": {
+    "terminal.integrated.shell.linux": "/bin/bash",
+    "workbench.startupEditor": "none",
+    "files.autoSave": "afterDelay",
+    "python.dataScience.enabled": true,
+    "python.dataScience.alwaysTrustNotebooks": true,
+    "python.insidersChannel": "weekly",
+    "python.showStartPage": false
+  },
+  "extensions": ["ms-python.python", "lextudio.restructuredtext"]
+}

.devcontainer/requirements.txt

@@ -0,0 +1,31 @@
+# Refer to ./jenkins/build.sh for tutorial build instructions
+
+sphinx==1.8.2
+sphinx-gallery==0.3.1
+tqdm
+numpy
+matplotlib
+torch
+torchvision
+torchtext
+torchaudio
+PyHamcrest
+bs4
+awscli==1.16.35
+flask
+spacy
+ray[tune]
+
+# PyTorch Theme
+-e git+git://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme
+
+ipython
+
+# to run examples
+pandas
+scikit-image
+pillow==8.1.1
+wget
+
+# for codespaces env
+pylint

.gitignore

@@ -120,4 +120,4 @@ cleanup.sh
 *.swp
 
 # PyTorch things
-*.pt
+*.pt

.jenkins/build.sh

@@ -6,6 +6,10 @@ else
   export BUCKET_NAME=pytorch-tutorial-build-pull-request
 fi
 
+# set locale for click dependency in spacy
+export LC_ALL=C.UTF-8
+export LANG=C.UTF-8
+
 DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null && pwd )"
 
 sudo apt-get update
@@ -18,6 +22,12 @@ pip install -r $DIR/../requirements.txt
 # export PATH=/opt/conda/bin:$PATH
 # pip install sphinx==1.8.2 pandas
 
+#Install PyTorch Nightly for test. 
+# Nightly - pip install --pre torch torchvision torchaudio -f https://download.pytorch.org/whl/nightly/cu102/torch_nightly.html
+# RC Link
+# pip uninstall -y torch torchvision torchaudio torchtext
+# pip install -f https://download.pytorch.org/whl/test/cu102/torch_test.html torch torchvision torchaudio torchtext
+
 # For Tensorboard. Until 1.14 moves to the release channel.
 pip install tb-nightly
 
@@ -28,9 +38,7 @@ python -m spacy download de
 # PyTorch Theme
 rm -rf src
 pip install -e git+git://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme
-# pillow >= 4.2 will throw error when trying to write mode RGBA as JPEG,
-# this is a workaround to the issue.
-pip install sphinx-gallery==0.3.1 tqdm matplotlib ipython pillow==4.1.1
+pip install sphinx-gallery==0.3.1 tqdm matplotlib ipython pillow==8.1.0
 
 aws configure set default.s3.multipart_threshold 5120MB
 
@@ -39,6 +47,11 @@ export NUM_WORKERS=20
 if [[ "${JOB_BASE_NAME}" == *worker_* ]]; then
   # Step 1: Remove runnable code from tutorials that are not supposed to be run
   python $DIR/remove_runnable_code.py beginner_source/aws_distributed_training_tutorial.py beginner_source/aws_distributed_training_tutorial.py || true
+  # python $DIR/remove_runnable_code.py advanced_source/ddp_pipeline_tutorial.py advanced_source/ddp_pipeline_tutorial.py || true
+  # Temp remove for mnist download issue. (Re-enabled for 1.8.1)
+  # python $DIR/remove_runnable_code.py beginner_source/fgsm_tutorial.py beginner_source/fgsm_tutorial.py || true
+  # python $DIR/remove_runnable_code.py intermediate_source/spatial_transformer_tutorial.py intermediate_source/spatial_transformer_tutorial.py || true
+
   # TODO: Fix bugs in these tutorials to make them runnable again
   # python $DIR/remove_runnable_code.py beginner_source/audio_classifier_tutorial.py beginner_source/audio_classifier_tutorial.py || true
 

Makefile

@@ -97,17 +97,11 @@ download:
 	wget -N https://download.pytorch.org/models/mobilenet_v2-b0353104.pth -P $(DATADIR)
 	cp $(DATADIR)/mobilenet_v2-b0353104.pth advanced_source/data/mobilenet_pretrained_float.pth
 
-	# Download dataset for advanced_source/static_quantization_tutorial.py
-	wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/imagenet_1k.zip -P $(DATADIR)
-	unzip $(ZIPOPTS) $(DATADIR)/imagenet_1k.zip -d advanced_source/data/
 
 	# Download model for prototype_source/graph_mode_static_quantization_tutorial.py
 	wget -N https://download.pytorch.org/models/resnet18-5c106cde.pth -P $(DATADIR)
 	cp $(DATADIR)/resnet18-5c106cde.pth prototype_source/data/resnet18_pretrained_float.pth
 
-	# Download dataset for prototype_source/graph_mode_static_quantization_tutorial.py
-	wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/imagenet_1k.zip -P $(DATADIR)
-	unzip $(ZIPOPTS) $(DATADIR)/imagenet_1k.zip -d prototype_source/data/
 
 docs:
 	make download

README.md

@@ -28,11 +28,10 @@ In case you prefer to write your tutorial in jupyter, you can use [this script](
 - Then you can build using `make docs`. This will download the data, execute the tutorials and build the documentation to `docs/` directory. This will take about 60-120 min for systems with GPUs. If you do not have a GPU installed on your system, then see next step.
 - You can skip the computationally intensive graph generation by running `make html-noplot` to build basic html documentation to `_build/html`. This way, you can quickly preview your tutorial.
 
-> If you get **ModuleNotFoundError: No module named 'pytorch_sphinx_theme' make: *** [html-noplot] Error 2**, from /tutorials/src/pytorch-sphinx-theme run `python setup.py install`. 
+> If you get **ModuleNotFoundError: No module named 'pytorch_sphinx_theme' make: *** [html-noplot] Error 2** from /tutorials/src/pytorch-sphinx-theme or /venv/src/pytorch-sphinx-theme (while using virtualenv), run `python setup.py install`. 
 
 
 ## About contributing to PyTorch Documentation and Tutorials
 * You can find information about contributing to PyTorch documentation in the 
 PyTorch Repo [README.md](https://github.com/pytorch/pytorch/blob/master/README.md) file. 
-* Additional information can be found in [PyTorch CONTRIBUTING.md](https://github.com/pytorch/pytorch/blob/master/CONTRIBUTING.md).
-
+* Additional information can be found in [PyTorch CONTRIBUTING.md](https://github.com/pytorch/pytorch/blob/master/CONTRIBUTING.md).

_static/torchvision_finetuning_instance_segmentation.ipynb

@@ -1448,7 +1448,7 @@
         "        self.masks = list(sorted(os.listdir(os.path.join(root, \"PedMasks\"))))\n",
         "\n",
         "    def __getitem__(self, idx):\n",
-        "        # load images ad masks\n",
+        "        # load images and masks\n",
         "        img_path = os.path.join(self.root, \"PNGImages\", self.imgs[idx])\n",
         "        mask_path = os.path.join(self.root, \"PedMasks\", self.masks[idx])\n",
         "        img = Image.open(img_path).convert(\"RGB\")\n",

_static/tv-training-code.py

@@ -25,7 +25,7 @@ def __init__(self, root, transforms):
         self.masks = list(sorted(os.listdir(os.path.join(root, "PedMasks"))))
 
     def __getitem__(self, idx):
-        # load images ad masks
+        # load images and masks
         img_path = os.path.join(self.root, "PNGImages", self.imgs[idx])
         mask_path = os.path.join(self.root, "PedMasks", self.masks[idx])
         img = Image.open(img_path).convert("RGB")

_templates/layout.html

@@ -34,10 +34,11 @@
       tutorialLink: window.location.href,
       downloadTitle: $(this).attr("data-response")
     });
-
-    gtag('event', 'click', {
-      'event_category': 'Download',
-      'event_label': $(this).attr("data-response")
+    ga('send', {
+      hitType: 'event',
+      eventCategory: $(this).attr("data-response"),
+      eventAction: 'click',
+      eventLabel: window.location.href
     });
 
     gtag('event', 'click', {
@@ -47,29 +48,22 @@
     });
    });
 
-   $("[data-behavior='was-this-helpful-event']").on('click', function(){
-    $(".helpful-question").hide();
-    $(".was-helpful-thank-you").show();
-
-    fbq('trackCustom', "Was this Helpful?", {
+   $("[data-behavior='tutorial-rating']").on('click', function(){
+    fbq('trackCustom', "Tutorial Rating", {
       tutorialLink: window.location.href,
       tutorialTitle: $('h1:first').text(),
-      helpful: $(this).attr("data-response")
-    });
-
-    gtag('event', $(this).attr("data-response"), {
-      'event_category': 'Was this Helpful?',
-      'event_label': $(this).attr("data-response")
+      rating: $(this).attr("data-count")
     });
 
-    gtag('event', $(this).attr("data-response"), {
-      'event_category': 'Was this Helpful?',
-      'event_label': $("h1").first().text()
+    gtag('event', 'click', {
+      'event_category': 'Tutorial Rating',
+      'event_label': $("h1").first().text(),
+      'value': $(this).attr("data-count")
     });
    });
 
    if (location.pathname == "/") {
-     $(".helpful-container").hide();
+     $(".rating-container").hide();
      $(".hr-bottom").hide();
    }
 </script>
@@ -79,5 +73,10 @@
   src="https://www.facebook.com/tr?id=243028289693773&ev=PageView
   &noscript=1"/>
 </noscript>
+
+<script type="text/javascript">
+  var collapsedSections = ['PyTorch Recipes', 'Learning PyTorch', 'Image and Video', 'Audio', 'Text', 'Reinforcement Learning', 'Deploying PyTorch Models in Production', 'Code Transforms with FX', 'Frontend APIs', 'Extending PyTorch', 'Model Optimization', 'Parallel and Distributed Training', 'Mobile'];
+</script>
+
 <img height="1" width="1" style="border-style:none;" alt="" src="https://www.googleadservices.com/pagead/conversion/795629140/?label=txkmCPmdtosBENSssfsC&amp;guid=ON&amp;script=0"/>
 {% endblock %}

advanced_source/cpp_export.rst

@@ -115,7 +115,7 @@ If you need to exclude some methods in your ``nn.Module``
 because they use Python features that TorchScript doesn't support yet,
 you could annotate those with ``@torch.jit.ignore``
 
-``my_module`` is an instance of
+``sm`` is an instance of
 ``ScriptModule`` that is ready for serialization.
 
 Step 2: Serializing Your Script Module to a File
@@ -132,7 +132,7 @@ on the module and pass it a filename::
   traced_script_module.save("traced_resnet_model.pt")
 
 This will produce a ``traced_resnet_model.pt`` file in your working directory.
-If you also would like to serialize ``my_module``, call ``my_module.save("my_module_model.pt")``
+If you also would like to serialize ``sm``, call ``sm.save("my_module_model.pt")``
 We have now officially left the realm of Python and are ready to cross over to the sphere
 of C++.