Fix cosine similarity dim checks (#66214)

* fix cosine similarity dimensionality check

* fix shapes in the doc

.azure_pipelines/build-pipeline.yml

@@ -0,0 +1,63 @@
+# PyTorch CI Builds Pipeline on Azure DevOps
+#
+# This pipeline:
+#   1) builds PyTorch on select configurations
+#   2) runs only TestTorch unit tests.
+
+stages:
+- stage: 'Build'
+  displayName: 'Build PyTorch'
+  jobs:
+  - template: job_templates/build-verify-publish-template-unix.yml
+    parameters:
+      name: ubuntu_1804_CPU_docker
+      pool: 'PyTorch-Linux-CPU'
+      container_endpoint: pytorchms.azurecr.io
+      build_stage: True
+      is_ci_build: True
+      os: ubuntu
+      cuda: cpu
+      customMatrixes:
+        Py_38:
+          configuration: ubuntu_1804_py_38_cpu
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cpu_dev
+
+  - template: job_templates/build-verify-publish-template-unix.yml
+    parameters:
+      name: ubuntu_1804_GPU_docker
+      pool: 'PyTorch-Linux-GPU'
+      container_endpoint: pytorchms.azurecr.io
+      build_stage: True
+      is_ci_build: True
+      os: ubuntu
+      cuda: gpu
+      customMatrixes:
+        Py_39_CUDA_112_cuDNN_810:
+          configuration: ubuntu_1804_py_39_cuda_112_cudnn_810
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_39_cuda_112_cudnn_8_dev
+          CUDA_VERSION: 112
+
+  - template: job_templates/build-verify-publish-template-win.yml
+    parameters:
+      name: windows_2019_CPU
+      pool: 'PyTorch-Win-CPU'
+      build_stage: True
+      is_ci_build: True
+      os: windows
+      cuda: cpu
+      customMatrixes:
+        Py_37:
+          configuration: windows_2019_py_37_cpu
+
+  - template: job_templates/build-verify-publish-template-win.yml
+    parameters:
+      name: windows_2019_GPU
+      pool: 'PyTorch-Win-GPU'
+      build_stage: True
+      is_ci_build: True
+      os: windows
+      cuda: gpu
+      customMatrixes:
+        Py_38_CUDA_102_cuDNN_765:
+          configuration: windows_2019_py_38_cuda_102_cudnn_765
+          CUDA_VERSION: 102

.azure_pipelines/daily-pipeline.yml

@@ -0,0 +1,82 @@
+# PyTorch Daily Builds Pipeline on Azure DevOps
+#
+# This pipeline:
+#   1) builds PyTorch on all available configurations
+#   2) runs all PyTorch unit tests
+
+stages:
+- stage: 'BuildTest'
+  displayName: 'Build and Test PyTorch'
+  jobs:
+  - template: job_templates/build-verify-publish-template-unix.yml
+    parameters:
+      name: ubuntu_1804_CPU_docker
+      pool: 'PyTorch-Linux-CPU'
+      container_endpoint: pytorchms.azurecr.io
+      build_stage: True
+      is_daily_build: True
+      os: ubuntu
+      cuda: cpu
+      customMatrixes:
+        Py_38:
+          configuration: ubuntu_1804_py_38_cpu
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cpu_dev
+        Py_37:
+          configuration: ubuntu_1804_py_37_cpu
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cpu_dev
+
+  - template: job_templates/build-verify-publish-template-unix.yml
+    parameters:
+      name: ubuntu_1804_GPU_docker
+      pool: 'PyTorch-Linux-GPU'
+      container_endpoint: pytorchms.azurecr.io
+      build_stage: True
+      is_daily_build: True
+      os: ubuntu
+      cuda: gpu
+      customMatrixes:
+        Py_39_CUDA_112_cuDNN_810:
+          configuration: ubuntu_1804_py_39_cuda_112_cudnn_810
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_39_cuda_112_cudnn_8_dev
+          CUDA_VERSION: 112
+        Py_38_CUDA_102_cuDNN_810:
+          configuration: ubuntu_1804_py_38_cuda_102_cudnn_810
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cuda_102_cudnn_8_dev
+          CUDA_VERSION: 102
+        Py_37_CUDA_101_cuDNN_765:
+          configuration: ubuntu_1804_py_37_cuda_101_cudnn_765
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cuda_101_cudnn_7_dev
+          CUDA_VERSION: 101
+
+  - template: job_templates/build-verify-publish-template-win.yml
+    parameters:
+      name: windows_2019_CPU
+      pool: 'PyTorch-Win-CPU'
+      build_stage: True
+      is_daily_build: True
+      os: windows
+      cuda: cpu
+      customMatrixes:
+        Py_38:
+          configuration: windows_2019_py_38_cpu
+        Py_37:
+          configuration: windows_2019_py_37_cpu
+
+  - template: job_templates/build-verify-publish-template-win.yml
+    parameters:
+      name: windows_2019_GPU
+      pool: 'PyTorch-Win-GPU'
+      build_stage: True
+      is_daily_build: True
+      os: windows
+      cuda: gpu
+      customMatrixes:
+        Py_39_CUDA_112_cuDNN_810:
+          configuration: windows_2019_py_39_cuda_112_cudnn_810
+          CUDA_VERSION: 112
+        Py_38_CUDA_102_cuDNN_765:
+          configuration: windows_2019_py_38_cuda_102_cudnn_765
+          CUDA_VERSION: 102
+        Py_37_CUDA_101_cuDNN_764:
+          configuration: windows_2019_py_37_cuda_101_cudnn_764
+          CUDA_VERSION: 101

.azure_pipelines/job_templates/build-verify-publish-template-unix.yml

@@ -0,0 +1,134 @@
+# PyTorch build steps template with Unix images Azure DevOps Instances
+#
+# This build depends on 3 parameters set as environment variables in the pipeline:
+#   - AZURE_DEVOPS_CLI_PAT: Secret var for authenticating to Azure DevOps
+#   - AZURE_DEVOPS_ARTIFACTS_ORGANIZATION: Azure Artifacts Organization name to publish artifacts
+#   - AZURE_DEVOPS_ARTIFACTS_PROJECT: Azure Artifacts Project name to publish artifacts
+
+parameters:
+  name: ''
+  pool: ''
+  container_endpoint: ''
+  os: ''
+  cuda: ''
+  is_ci_build: False
+  is_official_build: False
+  is_daily_build: False
+  build_stage: False
+  verify_stage: False
+  publish_stage: False
+  customMatrixes: ''
+
+jobs:
+- job: ${{parameters.name}}
+  timeoutInMinutes: 300
+  strategy:
+    matrix:
+      ${{ insert }}: ${{parameters.customMatrixes}}
+  pool:
+    name: ${{ parameters.pool}}
+  variables:
+    DECODE_PERCENTS: false
+  container:
+    image: $[variables['container_image']]
+    endpoint: ${{parameters.container_endpoint}}
+
+  steps:
+  # Build stage
+  - ${{ if eq(parameters.build_stage, 'True') }}:
+    # Set up environment variables for specific pipeline build
+    - template: set-environment-variables.yml
+      parameters:
+        os: ${{ parameters.os}}
+        cuda: ${{ parameters.cuda}}
+        is_official_build: ${{ parameters.is_official_build}}
+
+    # Sync and update PyTorch submodules
+    - bash: git submodule update --init --recursive --jobs 0
+      displayName: Update PyTorch submodules
+
+    # Build PyTorch and run unit tests - no packaging
+    - ${{ if or(eq(parameters.is_ci_build, 'True'), eq(parameters.is_daily_build, 'True')) }}:
+      # Build PyTorch from source in develop mode
+      - bash: python setup.py develop
+        displayName: Build PyTorch from source
+
+      - ${{ if eq(parameters.is_ci_build, 'True') }}:
+        # Run TestTorch unit tests to demonstrate successful PyTorch build
+        - bash: python test/test_torch.py TestTorch
+          displayName: Run TestTorch unit tests
+
+      - ${{ if eq(parameters.is_daily_build, 'True') }}:
+        # Run all unit tests to demonstrate successful PyTorch build
+        - bash: python test/run_test.py --continue-through-error --exclude-jit-executor --verbose
+          displayName: Run all unit tests
+
+      # Run ComponentGovernance
+      - task: ComponentGovernanceComponentDetection@0
+        inputs:
+          scanType: 'Register'
+          verbosity: 'Verbose'
+          alertWarningLevel: 'High'
+
+    # Build PyTorch and produce artifacts for verification stage
+    - ${{ if eq(parameters.is_official_build, 'True') }}:
+      # Build PyTorch from source in install mode and exclude test binaries
+      - bash: python setup.py install
+        displayName: Build PyTorch from source without test binaries
+
+      # Package PyTorch Wheel
+      - bash: python setup.py bdist_wheel
+        displayName: Package PyTorch Wheel
+
+      # Publish PyTorch Wheel
+      - task: PublishPipelineArtifact@1
+        inputs:
+          targetPath: $(Build.SourcesDirectory)/dist/
+          artifactName: Build_$(Build.BuildNumber)_$(configuration)
+        displayName: Publish PyTorch Wheel to Pipeline Artifacts
+
+  # Verification stage
+  - ${{ if eq(parameters.verify_stage, 'True') }}:
+    # Download PyTorch Wheel
+    - task: DownloadPipelineArtifact@2
+      inputs:
+        artifact: Build_$(Build.BuildNumber)_$(configuration)
+        path: $(Build.SourcesDirectory)/verify
+      displayName: Download PyTorch Wheel
+
+    # Install PyTorch Wheel on Windows
+    - bash: python -m pip install $(Build.SourcesDirectory)/verify/torch*linux*.whl
+      displayName: Install PyTorch Wheel
+
+    # Ensure PyTorch installed correctly from produced wheel
+    - bash: |
+        cd $(Build.SourcesDirectory)/verify
+        python -c "import torch; print('Installed Torch version: ' + torch.__version__)"
+      displayName: Check PyTorch correctly installed from wheel
+
+  # Publishing stage
+  - ${{ if eq(parameters.publish_stage, 'True') }}:
+    # Download PyTorch Wheel
+    - task: DownloadPipelineArtifact@2
+      inputs:
+        artifact: Build_$(Build.BuildNumber)_$(configuration)
+        path: $(Build.SourcesDirectory)/publish
+      displayName: Download PyTorch Wheel
+
+    # Publish wheel to Azure Artifacts
+    # The flag continueOnError=true is needed as the artifact to be published
+    # may already exist, because the artifact is differentiated based on the
+    # last commit date.
+    - bash: |
+        export TORCH_VERSION=$(head -c 5 ./version.txt)
+        export LAST_COMMIT=$(git rev-parse --short HEAD)
+        export LAST_COMMIT_DATE=$(git log -1 --pretty=%ad --date=format:%Y%m%d)
+        cd $(Build.SourcesDirectory)/publish
+        export TORCH_WHEEL=$(echo torch*linux*whl)
+        az extension add -n azure-devops
+        echo $ADOTOKEN | az devops login
+        az artifacts universal publish --organization $AZURE_DEVOPS_ARTIFACTS_ORGANIZATION --project $AZURE_DEVOPS_ARTIFACTS_PROJECT --scope project --feed "PyTorch" --name $TORCH_WHEEL --description "PyTorch Official Build Artifact" --version $TORCH_VERSION-$LAST_COMMIT_DATE-$LAST_COMMIT --path .
+      env:
+        ADOTOKEN: $(AZURE_DEVOPS_CLI_PAT)
+      continueOnError: true
+      displayName: Upload PyTorch Official Build package to Azure Artifacts

.azure_pipelines/job_templates/build-verify-publish-template-win.yml

@@ -0,0 +1,150 @@
+# PyTorch build steps template with Windows images Azure DevOps Instances
+#
+# This build depends on 3 parameters set as environment variables in the pipeline:
+#   - AZURE_DEVOPS_CLI_PAT: Secret var for authenticating to Azure DevOps
+#   - AZURE_DEVOPS_ARTIFACTS_ORGANIZATION: Azure Artifacts Organization name to publish artifacts
+#   - AZURE_DEVOPS_ARTIFACTS_PROJECT: Azure Artifacts Project name to publish artifacts
+
+parameters:
+  name: ''
+  pool: ''
+  os: ''
+  cuda: ''
+  is_ci_build: False
+  is_official_build: False
+  is_daily_build: False
+  build_stage: False
+  verify_stage: False
+  publish_stage: False
+  customMatrixes: ''
+
+jobs:
+- job: ${{parameters.name}}
+  timeoutInMinutes: 300
+  strategy:
+    matrix:
+      ${{ insert }}: ${{parameters.customMatrixes}}
+  pool:
+    name: ${{ parameters.pool}}
+  variables:
+    CMAKE_GENERATOR: Ninja
+    PACKAGE_PDBS: 0
+
+  steps:
+  # Prepare for PyTorch build on Windows
+  - template: prepare-build-template.yml
+    parameters:
+      configuration: $(configuration)
+      build_stage: ${{ parameters.build_stage}}
+
+  # Build Stage
+  - ${{ if eq(parameters.build_stage, 'True') }}:
+    # Set up environment variables for specific pipeline build
+    - template: set-environment-variables.yml
+      parameters:
+        os: ${{ parameters.os}}
+        cuda: ${{ parameters.cuda}}
+        is_official_build: ${{ parameters.is_official_build}}
+
+    # Sync and update PyTorch submodules
+    - script: git submodule update --init --recursive --jobs 0
+      displayName: Update PyTorch submodules
+
+    # Build PyTorch and run unit tests - no packaging
+    - ${{ if or(eq(parameters.is_ci_build, 'True'), eq(parameters.is_daily_build, 'True')) }}:
+      # Build PyTorch from source in develop mode with Ninja
+      - script: call activate $(configuration) && python setup.py develop
+        displayName: Build PyTorch from source
+
+      - ${{ if eq(parameters.is_ci_build, 'True') }}:
+        # Run TestTorch unit tests to demonstrate successful PyTorch build
+        - script: call activate $(configuration) && python test\test_torch.py TestTorch
+          displayName: Run TestTorch unit tests
+
+      - ${{ if eq(parameters.is_daily_build, 'True') }}:
+        # Run all unit tests to demonstrate successful PyTorch build
+        - script: call activate $(configuration) && python test/run_test.py --continue-through-error --exclude-jit-executor --verbose
+          displayName: Run all unit tests
+
+      # Run ComponentGovernance
+      - task: ComponentGovernanceComponentDetection@0
+        inputs:
+          scanType: 'Register'
+          verbosity: 'Verbose'
+          alertWarningLevel: 'High'
+
+    # Build PyTorch and produce artifacts for verification stage
+    - ${{ if eq(parameters.is_official_build, 'True') }}:
+      # Build PyTorch from source in install mode with Ninja and exclude test binaries
+      - script: call activate $(configuration) && python setup.py install
+        displayName: Build PyTorch from source without test binaries
+
+      # Package PyTorch Wheel
+      - script: call activate $(configuration) && python setup.py bdist_wheel
+        displayName: Package PyTorch Wheel
+
+      # Publish PyTorch Wheel
+      - task: PublishPipelineArtifact@1
+        inputs:
+          targetPath: $(Build.SourcesDirectory)\dist\
+          artifactName: Build_$(Build.BuildNumber)_$(configuration)
+        displayName: Publish PyTorch Wheel to Pipeline Artifacts
+
+  # Verification Stage
+  - ${{ if eq(parameters.verify_stage, 'True') }}:
+    # Download PyTorch Wheel
+    - task: DownloadPipelineArtifact@2
+      inputs:
+        artifact: Build_$(Build.BuildNumber)_$(configuration)
+        path: $(Build.SourcesDirectory)\verify
+      displayName: Download PyTorch Wheel
+
+    # Install PyTorch Wheel on Windows
+    - script: |
+        call activate $(configuration)
+        cd $(Build.SourcesDirectory)\verify
+        dir torch*win*.whl /b > whl.txt
+        set /p whl= < whl.txt
+        python -m pip install %whl%
+      displayName: Install PyTorch Wheel
+
+    # Ensure PyTorch installed correctly from produced wheel
+    - script: |
+        call activate $(configuration)
+        cd $(Build.SourcesDirectory)\verify
+        python -c "import torch; print('Installed Torch version: ' + torch.__version__)"
+      displayName: Check PyTorch correctly installed from wheel
+
+  # Publishing stage
+  - ${{ if eq(parameters.publish_stage, 'True') }}:
+    # Download PyTorch Wheel
+    - task: DownloadPipelineArtifact@2
+      inputs:
+        artifact: Build_$(Build.BuildNumber)_$(configuration)
+        path: $(Build.SourcesDirectory)\publish
+      displayName: Download PyTorch Wheel
+
+    # Set up Azure Artifacts for Windows
+    # The pip install --upgrade command is a bug fix for Azure CLI on Windows
+    # More info: https://github.com/Azure/azure-cli/issues/16858
+    - script: |
+        pip install --upgrade pip --target \opt\az\lib\python3.6\site-packages\
+        az extension add -n azure-devops
+      displayName: Set up Azure Artifacts download on Windows
+
+    # Publish wheel to Azure Artifacts
+    # The flag continueOnError=true is needed as the artifact to be published
+    # may already exist, because the artifact is differentiated based on the
+    # last commit date.
+    - script: |
+        set /p TORCH_VERSION= < version.txt
+        cd $(Build.SourcesDirectory)\publish
+        git rev-parse --short HEAD > last_commit.txt && set /p LAST_COMMIT= < last_commit.txt
+        git log -1 --pretty=%ad --date=format:%Y%m%d > last_commit_date.txt && set /p LAST_COMMIT_DATE= < last_commit_date.txt
+        dir torch*win*.whl /b > whl.txt && set /p TORCH_WHEEL= < whl.txt
+        echo %ADOTOKEN% | az devops login
+        az artifacts universal publish --organization %AZURE_DEVOPS_ARTIFACTS_ORGANIZATION% --project %AZURE_DEVOPS_ARTIFACTS_PROJECT% --scope project --feed "PyTorch" --name %TORCH_WHEEL% --description "PyTorch Official Build Artifact" --version %TORCH_VERSION:~0,5%-%LAST_COMMIT_DATE%-%LAST_COMMIT% --path .
+      env:
+        ADOTOKEN: $(AZURE_DEVOPS_CLI_PAT)
+      continueOnError: true
+      displayName: Upload PyTorch nigthly package to Azure Artifacts

.azure_pipelines/job_templates/common-packages.yml

@@ -0,0 +1,17 @@
+dependencies:
+  - python=PYTHON_VERSION
+  - numpy
+  - ninja
+  - pyyaml
+  - mkl
+  - mkl-include
+  - setuptools
+  - cmake
+  - cffi
+  - typing_extensions
+  - future
+  - six
+  - requests
+  - dataclasses
+  - pip:
+    - -r ../../requirements.txt

.azure_pipelines/job_templates/notify-webapp-template.yml

@@ -0,0 +1,26 @@
+parameters:
+  name: ''
+  pool: ''
+  customMatrixes: ''
+
+jobs:
+- job: ${{parameters.name}}
+  timeoutInMinutes: 600
+  strategy:
+    matrix:
+      ${{ insert }}: ${{parameters.customMatrixes}}
+  pool:
+    name: ${{ parameters.pool}}
+  steps:
+  # Clone PyTorch Tests repository
+  - bash: |
+      B64_PAT=$(echo -n ":$_ADOTOKEN" | base64)
+      git -c http.extraHeader="Authorization: Basic ${B64_PAT}" clone $(AZURE_DEVOPS_PYTORCH_TESTS_REPO_URL)
+      cd pytorch_tests
+      git checkout $(PYTORCH_TESTS_CHECKOUT_BRANCH)
+    env:
+      _ADOTOKEN: $(AZURE_DEVOPS_CLI_PAT)
+    displayName: Clone PyTorch Tests repo
+  - bash: |
+      bash $(Build.SourcesDirectory)/pytorch_tests/webapp/notify_webapp.sh
+    displayName: Notify Webapp

.azure_pipelines/job_templates/prepare-build-template.yml

@@ -0,0 +1,62 @@
+# Build prepare steps for PyTorch on Azure DevOps to build from source.
+# These steps share between normal build process and semmle security scan tasks
+
+parameters:
+  build_stage: False
+  configuration: ''
+
+steps:
+# End Python tasks that may be lingering over from previous runs
+# Note: If python.exe isn't currently running, exit code becomes 128,
+# which fails the run. Here exit code is set to 0 to avoid failed run.
+- script: |
+    taskkill /f /im python.exe
+    IF %ERRORLEVEL% EQU 128 exit 0
+  displayName: End previous Python processes
+
+# Clean up env directory in conda for fresh builds and set up conda environment YAML
+- powershell: |
+    Remove-Item 'C:\Miniconda\envs' -Recurse -ErrorAction Ignore
+    $env:PYTHON_VERSION = $env:SYSTEM_JOBNAME.Substring(3,1) + '.' + $env:SYSTEM_JOBNAME.Substring(4,1)
+    (Get-Content .azure_pipelines\job_templates\common-packages.yml) -replace 'PYTHON_VERSION', $env:PYTHON_VERSION | Out-File -encoding ASCII .azure_pipelines\job_templates\common-packages.yml
+  displayName: Clean up previous environments and Set up conda environment YAML
+
+# Make conda environment and install required packages
+- script: |
+    call conda clean --all -y
+    call conda env create -n $(configuration) --file .azure_pipelines\job_templates\common-packages.yml
+    call activate $(configuration)
+    call conda install -c conda-forge libuv=1.39
+  displayName: Set up conda environment for building from source
+
+- ${{ if eq(parameters.build_stage, 'True') }}:
+  # Install MKL
+  - script: |
+      rmdir /s /q mkl
+      del mkl_2020.2.254.7z
+      curl https://s3.amazonaws.com/ossci-windows/mkl_2020.2.254.7z -k -O
+      7z x -aoa mkl_2020.2.254.7z -omkl
+    displayName: Install MKL
+
+  # Install sccache and randomtemp
+  # Related PyTorch GitHub issue: https://github.com/pytorch/pytorch/issues/25393
+  # Related fix: https://github.com/pytorch/builder/pull/448/
+  - script: |
+      mkdir .\tmp_bin
+      curl -k https://s3.amazonaws.com/ossci-windows/sccache.exe --output .\tmp_bin\sccache.exe
+      curl -k https://s3.amazonaws.com/ossci-windows/sccache-cl.exe --output .\tmp_bin\sccache-cl.exe
+      copy .\tmp_bin\sccache.exe .\tmp_bin\nvcc.exe
+      curl -kL https://github.com/peterjc123/randomtemp-rust/releases/download/v0.3/randomtemp.exe --output .\tmp_bin\randomtemp.exe
+    displayName: Install sccache and randomtemp
+    condition: not(eq(variables.CUDA_VERSION, ''))
+
+  # CUDA 11.2's CUB directory conflicts with CUDA 10.2 and 10.1
+  # builds, where CUDA 11.2's CUB is injected into non-CUDA
+  # 11.2 builds.
+  - powershell: Remove-Item "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\include\cub" -Recurse -ErrorAction Ignore
+    displayName: Remove conflicting CUB from CUDA installation
+    condition: not(eq(variables.CUDA_VERSION, ''))
+
+  - powershell: Copy-Item -Path "F:\cuda_11_2\cub\" -Destination "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\include" -Recurse
+    displayName: Copy CUDA CUB for CUDA 11.2 build
+    condition: eq(variables.CUDA_VERSION, '112')

.azure_pipelines/job_templates/pytorch-template-unix.yml

@@ -0,0 +1,61 @@
+# PyTorch build steps template with Unix images Azure DevOps Instances
+#
+# This build depends on 5 parameters set as an environment variables in the pipeline:
+#   - AZURE_DEVOPS_CLI_PAT: Secret var for authenticating to Azure DevOps
+#   - AZURE_STORAGE_KEY: Secret var for authenticating to Azure Storage
+#   - _TS_CLONE_P, _TS_P, _TS_SM_P: Secret vars for specific unit tests
+
+parameters:
+  name: ''
+  pool: ''
+  container_endpoint: ''
+  customMatrixes: ''
+
+jobs:
+- job: ${{parameters.name}}
+  timeoutInMinutes: 600
+  strategy:
+    matrix:
+      ${{ insert }}: ${{parameters.customMatrixes}}
+  pool:
+    name: ${{ parameters.pool}}
+  variables:
+    DECODE_PERCENTS: false
+
+  steps:
+  # Don't checkout repo contents to save time and CPU compute. Environment variables
+  # related to checkout branch such as $(BUILD_SOURCEBRANCH) are still available.
+  - checkout: none
+
+  # Delete pytorch_tests repo from previous builds if exists
+  - bash: rm -rf pytorch_tests/
+    displayName: Delete pytorch_tests repo from previous builds if exists
+
+  # Clone PyTorch Tests repository
+  - bash: |
+      B64_PAT=$(echo -n ":$_ADOTOKEN" | base64)
+      git -c http.extraHeader="Authorization: Basic ${B64_PAT}" clone $(AZURE_DEVOPS_PYTORCH_TESTS_REPO_URL)
+      cd pytorch_tests
+      git checkout $(PYTORCH_TESTS_CHECKOUT_BRANCH)
+    env:
+      _ADOTOKEN: $(AZURE_DEVOPS_CLI_PAT)
+    displayName: Clone PyTorch Tests repo
+
+  # Run PyTorch Unit Tests
+  - bash: bash $(Build.SourcesDirectory)/pytorch_tests/scripts/linux/run.sh
+    env:
+      _AZURE_STORAGE_KEY: $(AZURE_STORAGE_KEY)
+      _TS_CLONE_P: $(TS_CLONE_PASSWORD)
+      _TS_P: $(TS_PAT)
+      _TS_SM_P: $(TS_SM_PAT)
+      _AZUREML_CLONE_PASSWORD: $(AZUREML_CLONE_PASSWORD)
+      _SPPASSWORD: $(SPPASSWORD)
+    displayName: Run PyTorch Unit Tests
+
+  # Tests results are available outside the docker container since
+  # the current directory is mounted as a volume of the container.
+  - task: PublishTestResults@2
+    condition: always()
+    inputs:
+      testResultsFiles: '**/test-*.xml'
+      testRunTitle: 'Publish test results for Python'

.azure_pipelines/job_templates/pytorch-template-win.yml

@@ -0,0 +1,57 @@
+# PyTorch build steps template with Windows images Azure DevOps Instances
+#
+# This build depends on 5 parameters set as an environment variables in the pipeline:
+#   - AZURE_DEVOPS_CLI_PAT: Secret var for authenticating to Azure DevOps
+#   - AZURE_STORAGE_KEY: Secret var for authenticating to Azure Storage
+#   - _TS_CLONE_P, _TS_P, _TS_SM_P: Secret vars for specific unit tests
+
+parameters:
+  name: ''
+  pool: ''
+  customMatrixes: ''
+
+jobs:
+- job: ${{parameters.name}}
+  timeoutInMinutes: 600
+  strategy:
+    matrix:
+      ${{ insert }}: ${{parameters.customMatrixes}}
+  pool:
+    name: ${{ parameters.pool}}
+
+  steps:
+  # Don't checkout repo contents to save time and CPU compute. Environment variables
+  # related to checkout branch such as $(BUILD_SOURCEBRANCH) are still available.
+  - checkout: none
+
+  # Delete pytorch_tests repo from previous builds if exists
+  - script: if exist "pytorch_tests/" rmdir "pytorch_tests/" /q /s
+    displayName: Delete pytorch_tests repo from previous builds if exists
+
+  # Clone PyTorch Tests repository
+  - powershell: |
+      $env:B64Pat = [Convert]::ToBase64String([System.Text.Encoding]::UTF8.GetBytes(":$env:_ADOTOKEN"))
+      git -c http.extraHeader="Authorization: Basic $env:B64Pat" clone $env:AZURE_DEVOPS_pytorch_tests_REPO_URL
+      cd pytorch_tests
+      git checkout $(PYTORCH_TESTS_CHECKOUT_BRANCH)
+    env:
+      _ADOTOKEN: $(AZURE_DEVOPS_CLI_PAT)
+    displayName: Clone PyTorch Tests repo
+
+  # Run PyTorch Unit Tests
+  - script: call $(Build.SourcesDirectory)\pytorch_tests\scripts\windows\run.bat
+    env:
+      _ADOTOKEN: $(AZURE_DEVOPS_CLI_PAT)
+      _AZURE_STORAGE_KEY: $(AZURE_STORAGE_KEY)
+      _TS_CLONE_P: $(TS_CLONE_PASSWORD)
+      _TS_P: $(TS_PAT)
+      _TS_SM_P: $(TS_SM_PAT)
+    displayName: Run PyTorch Unit Tests
+
+  # Tests results are available outside the docker container since
+  # the current directory is mounted as a volume of the container.
+  - task: PublishTestResults@2
+    condition: always()
+    inputs:
+      testResultsFiles: '**\test-*.xml'
+      testRunTitle: 'Publish test results for Python'

.azure_pipelines/job_templates/set-environment-variables.yml

@@ -0,0 +1,131 @@
+# Set environment variables for specific configurations
+
+parameters:
+  is_official_build: False
+  os: ''
+  cuda: ''
+
+steps:
+  # Environment configuration steps for Ubuntu builds
+  - ${{ if contains(parameters.os, 'ubuntu') }}:
+    # Set configuration specific build flags
+    - ${{ if eq(parameters.is_official_build, True) }}:
+      - bash: |
+          echo "##vso[task.setvariable variable=INSTALL_TEST;]0"
+          echo "##vso[task.setvariable variable=PYTORCH_BUILD_NUMBER;]1"
+          export PYTORCH_VERSION=$(head -c 5 ./version.txt)
+          echo "##vso[task.setvariable variable=PYTORCH_BUILD_VERSION;]$PYTORCH_VERSION.dev"
+        displayName: Set configuration-specific build flags
+
+      # Set PyTorch CPU/GPU build flags.
+      - ${{ if contains(parameters.cuda, 'cpu') }}:
+        - bash: |
+            echo "##vso[task.setvariable variable=USE_CUDA;]0"
+            echo "##vso[task.setvariable variable=PYTORCH_BUILD_VERSION;]$(PYTORCH_BUILD_VERSION).cpu"
+          displayName: Set CUDA-specific build flag for CPU builds
+
+      - ${{ if contains(parameters.cuda, 'gpu') }}:
+        - bash: |
+            echo "##vso[task.setvariable variable=USE_CUDA;]1"
+            echo "##vso[task.setvariable variable=PYTORCH_BUILD_VERSION;]$(PYTORCH_BUILD_VERSION).cu$(CUDA_VERSION)"
+          displayName: Set CUDA-specific build flag for GPU builds
+
+    # Set MKL environment variables
+    - bash: |
+        echo "##vso[task.setvariable variable=CMAKE_LIBRARY_PATH;]/opt/intel/lib:$CMAKE_LIBRARY_PATH"
+        echo "##vso[task.setvariable variable=CMAKE_INCLUDE_PATH;]/opt/intel/include:$CMAKE_INCLUDE_PATH"
+      displayName: Set MKL paths
+
+    # View current environment variables
+    - bash:
+        printenv
+      displayName: Show environment variables
+
+  # Environment configuration steps for Windows builds
+  - ${{ if contains(parameters.os, 'windows') }}:
+    # Set Conda Lib Path
+    - powershell: Write-Host "##vso[task.setvariable variable=CONDA_LIB_PATH;]C:\Miniconda\envs\$(configuration)\Library\bin"
+      displayName: Set Conda Lib Path
+
+    # Set configuration specific build flags
+    - ${{ if eq(parameters.is_official_build, True) }}:
+      - powershell: |
+          Write-Host "##vso[task.setvariable variable=INSTALL_TEST;]0"
+          Write-Host "##vso[task.setvariable variable=PYTORCH_BUILD_NUMBER;]1"
+          Set-Variable -Name PYTORCH_VERSION -Value (Get-Content .\version.txt).Substring(0,5)
+          Write-Host "##vso[task.setvariable variable=PYTORCH_BUILD_VERSION;]$PYTORCH_VERSION.dev"
+        displayName: Set configuration-specific build flags
+
+      # Set PyTorch CPU/GPU build flags..
+      - ${{ if contains(parameters.cuda, 'cpu') }}:
+        - powershell: |
+            Write-Host "##vso[task.setvariable variable=USE_CUDA;]0"
+            Write-Host "##vso[task.setvariable variable=PYTORCH_BUILD_VERSION;]$(PYTORCH_BUILD_VERSION).cpu"
+          displayName: Set CUDA-specific build flag for CPU build
+
+      - ${{ if contains(parameters.cuda, 'gpu') }}:
+        - powershell: |
+            Write-Host "##vso[task.setvariable variable=USE_CUDA;]1"
+            Write-Host "##vso[task.setvariable variable=PYTORCH_BUILD_VERSION;]$(PYTORCH_BUILD_VERSION).cu$(CUDA_VERSION)"
+          displayName: Set CUDA-specific build flag for GPU build
+
+    # Set CUDA 11.2, 10.2 or 10.1 specific build flags
+    - ${{ if eq(parameters.cuda, 'gpu') }}:
+      - powershell: |
+          Write-Host "##vso[task.setvariable variable=TORCH_CUDA_ARCH_LIST;]3.7+PTX;5.0;6.0;6.1;7.0;7.5;8.0;8.6"
+          Write-Host "##vso[task.setvariable variable=CUDA_PATH;]C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\"
+        displayName: Set CUDA 11.2 specific build flags
+        condition: eq(variables.CUDA_VERSION, '112')
+
+      - powershell: |
+          Write-Host "##vso[task.setvariable variable=TORCH_CUDA_ARCH_LIST;]3.7+PTX;5.0;6.0;6.1;7.0;7.5"
+          Write-Host "##vso[task.setvariable variable=CUDA_PATH;]C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.2\"
+        displayName: Set CUDA 10.2 specific build flags
+        condition: eq(variables.CUDA_VERSION, '102')
+
+      - powershell: |
+          Write-Host "##vso[task.setvariable variable=TORCH_CUDA_ARCH_LIST;]3.7+PTX;5.0;6.0;6.1;7.0;7.5"
+          Write-Host "##vso[task.setvariable variable=CUDA_PATH;]C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\"
+        displayName: Set CUDA 10.1 specific build flags
+        condition: eq(variables.CUDA_VERSION, '101')
+
+      - powershell: |
+          Write-Host "##vso[task.setvariable variable=CUDA_BIN_PATH;]$env:CUDA_PATH\bin\"
+          Write-Host "##vso[task.setvariable variable=CUDNN_ROOT;]$env:CUDA_PATH"
+          Write-Host "##vso[task.setvariable variable=CUDNN_INCLUDE_DIR;]$env:CUDA_PATH\include\"
+          Write-Host "##vso[task.setvariable variable=CUDNN_LIBRARY;]$env:CUDA_PATH\lib\x64\"
+          Write-Host "##vso[task.prependpath]$env:CUDA_PATH\bin"
+          Write-Host "##vso[task.setvariable variable=TORCH_NVCC_FLAGS;]-Xfatbin -compress-all --no-host-device-move-forward"
+          Write-Host "##vso[task.setvariable variable=THRUST_IGNORE_CUB_VERSION_CHECK;]1"
+          Write-Host "##vso[task.setvariable variable=NVTOOLSEXT_PATH;]C:\Program Files\NVIDIA Corporation\NvToolsExt\"
+        displayName: Set CUDA environment variables
+
+      - powershell: |
+          copy "$(CUDA_BIN_PATH)\cusparse*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
+          copy "$(CUDA_BIN_PATH)\cublas*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
+          copy "$(CUDA_BIN_PATH)\cudart*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
+          copy "$(CUDA_BIN_PATH)\curand*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
+          copy "$(CUDA_BIN_PATH)\cufft*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
+          copy "$(CUDA_BIN_PATH)\cusolver*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
+          copy "$(CUDA_BIN_PATH)\cudnn*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
+          copy "$(CUDA_BIN_PATH)\nvrtc*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
+          copy "C:\Program Files\NVIDIA Corporation\NvToolsExt\bin\x64\nvToolsExt64_1.dll*" $(Build.SourcesDirectory)\torch\lib
+          copy "$(CONDA_LIB_PATH)\libiomp*5md.dll" $(Build.SourcesDirectory)\torch\lib
+          copy "$(CONDA_LIB_PATH)\uv.dll" $(Build.SourcesDirectory)\torch\lib
+        displayName: Copy CUDA/cuDNN/libomp/libuv dlls to torch\lib
+
+    # Set MKL, sccache and randomtemp environment variables
+    - powershell: |
+        Write-Host "##vso[task.setvariable variable=CMAKE_INCLUDE_PATH;]$(Build.SourcesDirectory)\mkl\include"
+        Write-Host "##vso[task.setvariable variable=CMAKE_LIBRARY_PATH;]$(Build.SourcesDirectory)\mkl\lib;$env:CMAKE_LIBRARY_PATH"
+        Write-Host "##vso[task.setvariable variable=ADDITIONAL_PATH;]$(Build.SourcesDirectory)\tmp_bin"
+        Write-Host "##vso[task.setvariable variable=SCCACHE_IDLE_TIMEOUT;]1500"
+        Write-Host "##vso[task.setvariable variable=RANDOMTEMP_EXECUTABLE;]$(Build.SourcesDirectory)\tmp_bin\nvcc.exe"
+        Write-Host "##vso[task.setvariable variable=CUDA_NVCC_EXECUTABLE;]$(Build.SourcesDirectory)\tmp_bin\randomtemp.exe"
+        Write-Host "##vso[task.setvariable variable=RANDOMTEMP_BASEDIR;]$(Build.SourcesDirectory)\tmp_bin"
+      displayName: Set MKL, sccache and randomtemp environment variables
+
+    # View current environment variables
+    - script:
+        set
+      displayName: Show environment variables

.azure_pipelines/job_templates/wheel-wait-job-template.yml

@@ -0,0 +1,14 @@
+# Main logic to initiate wait for PR artifact to be ready
+
+steps:
+- task: InvokeRESTAPI@1
+  displayName: 'Wait for job success and wheel ready'
+  timeoutInMinutes: 60
+  inputs:
+    connectionType: 'connectedServiceName'
+    serviceConnection: circleciconn
+    method: 'POST'
+    headers: '{"Content-Type":"application/json", "BranchName":"$(_TARGET_BRANCH_TO_CHECK)", "JobName":"$(TARGET_CIRCLECI_BUILD_PR)", "PRNumber":"$(_TARGET_PR_NUMBER)", "TargetCommit":"$(_TARGET_COMMIT)", "PlanUrl":"$(System.CollectionUri)", "ProjectId":"$(System.TeamProjectId)", "HubName":"$(System.HostType)", "PlanId":"$(System.PlanId)", "JobId":"$(System.JobId)", "TimelineId":"$(System.TimelineId)", "TaskInstanceId":"$(System.TaskInstanceId)", "AuthToken":"$(System.AccessToken)"}'
+    body: ''
+    urlSuffix: 'api/JobStatus'
+    waitForCompletion: true

.azure_pipelines/job_templates/wheel-wait-template.yml

@@ -0,0 +1,92 @@
+# Initiate 5 agentless-server waiting jobs to check on the
+# status of PR artifact builds, for a maximum wait time of
+# 11*60 min=660 mins. These jobs will pass immediately
+# once targeted CircleCI build is ready.
+
+jobs:
+- job: checkjob1
+  pool: server
+  timeoutInMinutes: 60
+  continueOnError: true
+  steps:
+  - template: wheel-wait-job-template.yml
+
+- job: checkjob2
+  pool: server
+  timeoutInMinutes: 60
+  dependsOn: checkjob1
+  continueOnError: true
+  steps:
+  - template: wheel-wait-job-template.yml
+
+- job: checkjob3
+  pool: server
+  timeoutInMinutes: 60
+  dependsOn: checkjob2
+  continueOnError: true
+  steps:
+  - template: wheel-wait-job-template.yml
+
+- job: checkjob4
+  pool: server
+  timeoutInMinutes: 60
+  dependsOn: checkjob3
+  continueOnError: true
+  steps:
+  - template: wheel-wait-job-template.yml
+
+- job: checkjob5
+  pool: server
+  timeoutInMinutes: 60
+  dependsOn: checkjob4
+  continueOnError: true
+  steps:
+  - template: wheel-wait-job-template.yml
+
+- job: checkjob6
+  pool: server
+  timeoutInMinutes: 60
+  dependsOn: checkjob5
+  continueOnError: true
+  steps:
+  - template: wheel-wait-job-template.yml
+
+- job: checkjob7
+  pool: server
+  timeoutInMinutes: 60
+  dependsOn: checkjob6
+  continueOnError: true
+  steps:
+  - template: wheel-wait-job-template.yml
+
+- job: checkjob8
+  pool: server
+  timeoutInMinutes: 60
+  dependsOn: checkjob7
+  continueOnError: true
+  steps:
+  - template: wheel-wait-job-template.yml
+
+- job: checkjob9
+  pool: server
+  timeoutInMinutes: 60
+  dependsOn: checkjob8
+  continueOnError: true
+  steps:
+  - template: wheel-wait-job-template.yml
+
+- job: checkjob10
+  pool: server
+  timeoutInMinutes: 60
+  dependsOn: checkjob9
+  continueOnError: true
+  steps:
+  - template: wheel-wait-job-template.yml
+
+- job: checkjob11
+  pool: server
+  timeoutInMinutes: 60
+  dependsOn: checkjob10
+  continueOnError: true
+  steps:
+  - template: wheel-wait-job-template.yml

.azure_pipelines/nightly-pytorch-tests-pipeline.yml

@@ -0,0 +1,60 @@
+# PyTorch Nightly PyTorch Tests Builds Pipeline on Azure DevOps
+#
+# This pipeline runs custom PyTorch unit-tests on nightly
+# PyTorch wheels.
+
+stages:
+- stage: 'NightlyCustomTests'
+  displayName: 'Run custom unit tests on PyTorch wheels'
+  jobs:
+  - template: job_templates/pytorch-template-unix.yml
+    parameters:
+      name: ubuntu_1804_CPU_docker
+      pool: $(BUILD_POOL_LIN_1)
+      customMatrixes:
+        Nightly_Custom_Tests:
+          _DOCKER_IMAGE: $(DOCKER_IMAGE_LIN_1)
+          _PYTHON_VERSION: $(PYTHON_VERSION_LIN_1)
+          _CUDA_BUILD_VERSION: $(CUDA_BUILD_VERSION_LIN_1)
+          _RUN_TESTS: $(RUN_TESTS_LIN)
+
+  - template: job_templates/pytorch-template-unix.yml
+    parameters:
+      name: ubuntu_1804_GPU_docker
+      pool: $(BUILD_POOL_LIN_2)
+      customMatrixes:
+        Nightly_Custom_Tests:
+          _DOCKER_IMAGE: $(DOCKER_IMAGE_LIN_2)
+          _PYTHON_VERSION: $(PYTHON_VERSION_LIN_2)
+          _CUDA_BUILD_VERSION: $(CUDA_BUILD_VERSION_LIN_2)
+          _RUN_TESTS: $(RUN_TESTS_LIN)
+
+  - template: job_templates/pytorch-template-win.yml
+    parameters:
+      name: windows_2019_CPU
+      pool: $(BUILD_POOL_WIN_1)
+      customMatrixes:
+        Nightly_Custom_Tests:
+          _PYTHON_VERSION: $(PYTHON_VERSION_WIN_1)
+          _CUDA_BUILD_VERSION: $(CUDA_BUILD_VERSION_WIN_1)
+          _RUN_TESTS: $(RUN_TESTS_WIN)
+
+  - template: job_templates/pytorch-template-win.yml
+    parameters:
+      name: windows_2019_GPU
+      pool: $(BUILD_POOL_WIN_2)
+      customMatrixes:
+        Nightly_Custom_Tests:
+          _PYTHON_VERSION: $(PYTHON_VERSION_WIN_2)
+          _CUDA_BUILD_VERSION: $(CUDA_BUILD_VERSION_WIN_2)
+          _RUN_TESTS: $(RUN_TESTS_WIN)
+
+- stage: 'NotifyWebapp'
+  displayName: 'Notify Webapp that pipeline is finished'
+  dependsOn: NightlyCustomTests
+  condition: succeededOrFailed()
+  jobs:
+  - template: job_templates/notify-webapp-template.yml
+    parameters:
+      name: ubuntu_1804_CPU
+      pool: $(BUILD_POOL_LIN_1)

.azure_pipelines/pytorch-tests-pipeline.yml

@@ -0,0 +1,62 @@
+# PyTorch PR PyTorch Tests Builds Pipeline on Azure DevOps
+#
+# This pipeline:
+#   1) ensures that CircleCI builds for a given PR
+#      have finished, and that its artifacts are
+#      ready for download
+#   2) runs custom PyTorch unit-tests on PyTorch
+#      wheels generated during PR builds.
+
+resources:
+  webhooks:
+    - webhook: GitHubPyTorchPRTrigger
+      connection: GitHubPyTorchPRTriggerConnection
+      filters:
+        - path: repositoryName
+          value: pytorch_tests
+
+stages:
+- stage: 'EnsureArtifactsReady'
+  displayName: 'Ensure PyTorch PR Artifacts are ready'
+  jobs:
+  - template: job_templates/wheel-wait-template.yml
+  variables:
+    _TARGET_BRANCH_TO_CHECK: ${{parameters.GitHubPyTorchPRTrigger.TARGET_BRANCH_TO_CHECK_AZ_DEVOPS_PR}}
+    _TARGET_PR_NUMBER: ${{parameters.GitHubPyTorchPRTrigger.PR_NUMBER}}
+    _TARGET_COMMIT: ${{parameters.GitHubPyTorchPRTrigger.TARGET_COMMIT}}
+
+- stage: 'PRCustomTests'
+  displayName: 'Run custom unit tests on PyTorch wheels'
+  dependsOn: EnsureArtifactsReady
+  condition: succeeded()
+  jobs:
+  - template: job_templates/pytorch-template-unix.yml
+    parameters:
+      name: ubuntu_1804_GPU_docker
+      pool: $(BUILD_POOL_PR)
+      customMatrixes:
+        PR_Custom_Tests:
+          _PYTHON_VERSION: $(PYTHON_VERSION_PR)
+          _CUDA_BUILD_VERSION: $(CUDA_BUILD_VERSION_PR)
+          _TARGET_CIRCLECI_BUILD: $(TARGET_CIRCLECI_BUILD_PR)
+          _TARGET_BRANCH_TO_CHECK: ${{parameters.GitHubPyTorchPRTrigger.TARGET_BRANCH_TO_CHECK_AZ_DEVOPS_PR}}
+          _TARGET_PR_NUMBER: ${{parameters.GitHubPyTorchPRTrigger.PR_NUMBER}}
+          _TARGET_COMMIT: ${{parameters.GitHubPyTorchPRTrigger.TARGET_COMMIT}}
+          _DOCKER_IMAGE: $(DOCKER_IMAGE_PR)
+          _RUN_TESTS: $(RUN_TESTS_PR)
+
+- stage: 'NotifyWebapp'
+  displayName: 'Notify Webapp that pipeline is finished'
+  dependsOn: PRCustomTests
+  condition: succeededOrFailed()
+  jobs:
+  - template: job_templates/notify-webapp-template.yml
+    parameters:
+      name: ubuntu_1804_CPU
+      pool: $(BUILD_POOL_LIN_1)
+      customMatrixes:
+        PR_Notify_WebApp:
+          _TARGET_CIRCLECI_BUILD: $(TARGET_CIRCLECI_BUILD_PR)
+          _TARGET_BRANCH_TO_CHECK: ${{parameters.GitHubPyTorchPRTrigger.TARGET_BRANCH_TO_CHECK_AZ_DEVOPS_PR}}
+          _TARGET_PR_NUMBER: ${{parameters.GitHubPyTorchPRTrigger.PR_NUMBER}}
+          _TARGET_COMMIT: ${{parameters.GitHubPyTorchPRTrigger.TARGET_COMMIT}}

.azure_pipelines/verify-pipeline.yml

@@ -0,0 +1,224 @@
+# PyTorch Official Builds Pipeline on Azure DevOps
+#
+# This pipeline:
+#   1) builds PyTorch on all available configurations
+#   2) verifies PyTorch artifacts by installing them in a clean environment
+#      and checking torch.__version_
+#   3) publishes official PyTorch artifacts to Azure DevOps Artifacts for consumption
+
+stages:
+- stage: 'Build'
+  displayName: 'Build PyTorch'
+  jobs:
+  - template: job_templates/build-verify-publish-template-unix.yml
+    parameters:
+      name: ubuntu_1804_CPU_docker
+      pool: 'PyTorch-Linux-CPU'
+      container_endpoint: pytorchms.azurecr.io
+      build_stage: True
+      is_official_build: True
+      os: ubuntu
+      cuda: cpu
+      customMatrixes:
+        Py_38:
+          configuration: ubuntu_1804_py_38_cpu
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cpu_dev
+        Py_37:
+          configuration: ubuntu_1804_py_37_cpu
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cpu_dev
+
+  - template: job_templates/build-verify-publish-template-unix.yml
+    parameters:
+      name: ubuntu_1804_GPU_docker
+      pool: 'PyTorch-Linux-GPU'
+      container_endpoint: pytorchms.azurecr.io
+      build_stage: True
+      is_official_build: True
+      os: ubuntu
+      cuda: gpu
+      customMatrixes:
+        Py_39_CUDA_112_cuDNN_810:
+          configuration: ubuntu_1804_py_39_cuda_112_cudnn_810
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_39_cuda_112_cudnn_8_dev
+          CUDA_VERSION: 112
+        Py_38_CUDA_102_cuDNN_810:
+          configuration: ubuntu_1804_py_38_cuda_102_cudnn_810
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cuda_102_cudnn_8_dev
+          CUDA_VERSION: 102
+        Py_37_CUDA_101_cuDNN_765:
+          configuration: ubuntu_1804_py_37_cuda_101_cudnn_765
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cuda_101_cudnn_7_dev
+          CUDA_VERSION: 101
+
+  - template: job_templates/build-verify-publish-template-win.yml
+    parameters:
+      name: windows_2019_CPU
+      pool: 'PyTorch-Win-CPU'
+      build_stage: True
+      is_official_build: True
+      os: windows
+      cuda: cpu
+      customMatrixes:
+        Py_38:
+          configuration: windows_2019_py_38_cpu
+        Py_37:
+          configuration: windows_2019_py_37_cpu
+
+  - template: job_templates/build-verify-publish-template-win.yml
+    parameters:
+      name: windows_2019_GPU
+      pool: 'PyTorch-Win-GPU'
+      build_stage: True
+      is_official_build: True
+      os: windows
+      cuda: gpu
+      customMatrixes:
+        Py_39_CUDA_112_cuDNN_810:
+          configuration: windows_2019_py_39_cuda_112_cudnn_810
+          CUDA_VERSION: 112
+        Py_38_CUDA_102_cuDNN_765:
+          configuration: windows_2019_py_38_cuda_102_cudnn_765
+          CUDA_VERSION: 102
+        Py_37_CUDA_101_cuDNN_764:
+          configuration: windows_2019_py_37_cuda_101_cudnn_764
+          CUDA_VERSION: 101
+
+- stage: 'Verify'
+  displayName: 'Verify PyTorch wheels'
+  dependsOn: Build
+  condition: succeeded()
+  jobs:
+  - template: job_templates/build-verify-publish-template-unix.yml
+    parameters:
+      name: ubuntu_1804_CPU_docker
+      pool: 'PyTorch-Linux-CPU'
+      container_endpoint: pytorchms.azurecr.io
+      verify_stage: True
+      is_official_build: True
+      customMatrixes:
+        Py_38:
+          configuration: ubuntu_1804_py_38_cpu
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cpu_dev
+        Py_37:
+          configuration: ubuntu_1804_py_37_cpu
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cpu_dev
+
+  - template: job_templates/build-verify-publish-template-unix.yml
+    parameters:
+      name: ubuntu_1804_GPU_docker
+      pool: 'PyTorch-Linux-GPU'
+      container_endpoint: pytorchms.azurecr.io
+      verify_stage: True
+      is_official_build: True
+      customMatrixes:
+        Py_39_CUDA_112_cuDNN_810:
+          configuration: ubuntu_1804_py_39_cuda_112_cudnn_810
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_39_cuda_112_cudnn_8_dev
+          CUDA_VERSION: 112
+        Py_38_CUDA_102_cuDNN_810:
+          configuration: ubuntu_1804_py_38_cuda_102_cudnn_810
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cuda_102_cudnn_8_dev
+          CUDA_VERSION: 102
+        Py_37_CUDA_101_cuDNN_765:
+          configuration: ubuntu_1804_py_37_cuda_101_cudnn_765
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cuda_101_cudnn_7_dev
+          CUDA_VERSION: 101
+
+  - template: job_templates/build-verify-publish-template-win.yml
+    parameters:
+      name: windows_2019_CPU
+      pool: 'PyTorch-Win-CPU'
+      verify_stage: True
+      is_official_build: True
+      customMatrixes:
+        Py_38:
+          configuration: windows_2019_py_38_cpu
+        Py_37:
+          configuration: windows_2019_py_37_cpu
+
+  - template: job_templates/build-verify-publish-template-win.yml
+    parameters:
+      name: windows_2019_GPU
+      pool: 'PyTorch-Win-GPU'
+      verify_stage: True
+      is_official_build: True
+      customMatrixes:
+        Py_39_CUDA_112_cuDNN_810:
+          configuration: windows_2019_py_39_cuda_112_cudnn_810
+          CUDA_VERSION: 112
+        Py_38_CUDA_102_cuDNN_765:
+          configuration: windows_2019_py_38_cuda_102_cudnn_765
+          CUDA_VERSION: 102
+        Py_37_CUDA_101_cuDNN_764:
+          configuration: windows_2019_py_37_cuda_101_cudnn_764
+          CUDA_VERSION: 101
+
+- stage: 'Publish'
+  displayName: 'Publish PyTorch wheels'
+  dependsOn: Verify
+  condition: succeeded()
+  jobs:
+  - template: job_templates/build-verify-publish-template-unix.yml
+    parameters:
+      name: ubuntu_1804_CPU_docker
+      pool: 'PyTorch-Linux-CPU'
+      container_endpoint: pytorchms.azurecr.io
+      publish_stage: True
+      is_official_build: True
+      customMatrixes:
+        Py_38:
+          configuration: ubuntu_1804_py_38_cpu
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cpu_dev
+        Py_37:
+          configuration: ubuntu_1804_py_37_cpu
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cpu_dev
+
+  - template: job_templates/build-verify-publish-template-unix.yml
+    parameters:
+      name: ubuntu_1804_GPU_docker
+      pool: 'PyTorch-Linux-GPU'
+      container_endpoint: pytorchms.azurecr.io
+      publish_stage: True
+      is_official_build: True
+      customMatrixes:
+        Py_39_CUDA_112_cuDNN_810:
+          configuration: ubuntu_1804_py_39_cuda_112_cudnn_810
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_39_cuda_112_cudnn_8_dev
+          CUDA_VERSION: 112
+        Py_38_CUDA_102_cuDNN_810:
+          configuration: ubuntu_1804_py_38_cuda_102_cudnn_810
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cuda_102_cudnn_8_dev
+          CUDA_VERSION: 102
+        Py_37_CUDA_101_cuDNN_765:
+          configuration: ubuntu_1804_py_37_cuda_101_cudnn_765
+          container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cuda_101_cudnn_7_dev
+          CUDA_VERSION: 101
+
+  - template: job_templates/build-verify-publish-template-win.yml
+    parameters:
+      name: windows_2019_CPU
+      pool: 'PyTorch-Win-CPU'
+      publish_stage: True
+      is_official_build: True
+      customMatrixes:
+        Py_38:
+          configuration: windows_2019_py_38_cpu
+        Py_37:
+          configuration: windows_2019_py_37_cpu
+
+  - template: job_templates/build-verify-publish-template-win.yml
+    parameters:
+      name: windows_2019_GPU
+      pool: 'PyTorch-Win-GPU'
+      publish_stage: True
+      is_official_build: True
+      customMatrixes:
+        Py_39_CUDA_112_cuDNN_810:
+          configuration: windows_2019_py_39_cuda_112_cudnn_810
+          CUDA_VERSION: 112
+        Py_38_CUDA_102_cuDNN_765:
+          configuration: windows_2019_py_38_cuda_102_cudnn_765
+          CUDA_VERSION: 102
+        Py_37_CUDA_101_cuDNN_764:
+          configuration: windows_2019_py_37_cuda_101_cudnn_764
+          CUDA_VERSION: 101

.bazelrc

@@ -1,115 +1,13 @@
-build --cxxopt=--std=c++17
+build --copt=--std=c++14
 build --copt=-I.
-# Bazel does not support including its cc_library targets as system
-# headers. We work around this for generated code
-# (e.g. c10/macros/cmake_macros.h) by making the generated directory a
-# system include path.
 build --copt=-isystem --copt bazel-out/k8-fastbuild/bin
-build --copt=-isystem --copt bazel-out/darwin-fastbuild/bin
-build --experimental_ui_max_stdouterr_bytes=2048576
 
 # Configuration to disable tty features for environments like CI
 build:no-tty --curses no
 build:no-tty --progress_report_interval 10
 build:no-tty --show_progress_rate_limit 10
 
-# Build with GPU support by default.
-build --define=cuda=true
-# rules_cuda configuration
-build --@rules_cuda//cuda:enable_cuda
-build --@rules_cuda//cuda:cuda_targets=sm_52
-build --@rules_cuda//cuda:compiler=nvcc
-build --repo_env=CUDA_PATH=/usr/local/cuda
-
-# Configuration to build without GPU support
-build:cpu-only --define=cuda=false
+# Configuration to build with GPU support
+build:gpu --define=cuda=true
 # define a separate build folder for faster switching between configs
-build:cpu-only --platform_suffix=-cpu-only
-# See the note on the config-less build for details about why we are
-# doing this. We must also do it for the "-cpu-only" platform suffix.
-build --copt=-isystem --copt=bazel-out/k8-fastbuild-cpu-only/bin
-# rules_cuda configuration
-build:cpu-only --@rules_cuda//cuda:enable_cuda=False
-
-# Definition of --config=shell
-# interactive shell immediately before execution
-build:shell --run_under="//tools/bazel_tools:shellwrap"
-
-# Disable all warnings for external repositories. We don't care about
-# their warnings.
-build --per_file_copt=^external/@-w
-
-# Set additional warnings to error level.
-#
-# Implementation notes:
-#  * we use file extensions to determine if we are using the C++
-#    compiler or the cuda compiler
-#  * we use ^// at the start of the regex to only permit matching
-#    PyTorch files. This excludes external repos.
-#
-# Note that because this is logically a command-line flag, it is
-# considered the word on what warnings are enabled. This has the
-# unfortunate consequence of preventing us from disabling an error at
-# the target level because those flags will come before these flags in
-# the action invocation. Instead we provide per-file exceptions after
-# this.
-#
-# On the bright side, this means we don't have to more broadly apply
-# the exceptions to an entire target.
-#
-# Looking for CUDA flags? We have a cu_library macro that we can edit
-# directly. Look in //tools/rules:cu.bzl for details. Editing the
-# macro over this has the following advantages:
-#  * making changes does not require discarding the Bazel analysis
-#    cache
-#  * it allows for selective overrides on individual targets since the
-#    macro-level opts will come earlier than target level overrides
-
-build --per_file_copt='^//.*\.(cpp|cc)$'@-Werror=all
-# The following warnings come from -Wall. We downgrade them from error
-# to warnings here.
-#
-# sign-compare has a tremendous amount of violations in the
-# codebase. It will be a lot of work to fix them, just disable it for
-# now.
-build --per_file_copt='^//.*\.(cpp|cc)$'@-Wno-sign-compare
-# We intentionally use #pragma unroll, which is compiler specific.
-build --per_file_copt='^//.*\.(cpp|cc)$'@-Wno-error=unknown-pragmas
-
-build --per_file_copt='^//.*\.(cpp|cc)$'@-Werror=extra
-# The following warnings come from -Wextra. We downgrade them from error
-# to warnings here.
-#
-# unused-parameter-compare has a tremendous amount of violations in the
-# codebase. It will be a lot of work to fix them, just disable it for
-# now.
-build --per_file_copt='^//.*\.(cpp|cc)$'@-Wno-unused-parameter
-# missing-field-parameters has both a large number of violations in
-# the codebase, but it also is used pervasively in the Python C
-# API. There are a couple of catches though:
-# * we use multiple versions of the Python API and hence have
-#   potentially multiple different versions of each relevant
-#   struct. They may have different numbers of fields. It will be
-#   unwieldy to support multiple versions in the same source file.
-# * Python itself for many of these structs recommends only
-#   initializing a subset of the fields. We should respect the API
-#   usage conventions of our dependencies.
-#
-# Hence, we just disable this warning altogether. We may want to clean
-# up some of the clear-cut cases that could be risky, but we still
-# likely want to have this disabled for the most part.
-build --per_file_copt='^//.*\.(cpp|cc)$'@-Wno-missing-field-initializers
-
-build --per_file_copt='//:aten/src/ATen/RegisterCompositeExplicitAutograd\.cpp$'@-Wno-error=unused-function
-build --per_file_copt='//:aten/src/ATen/RegisterCompositeImplicitAutograd\.cpp$'@-Wno-error=unused-function
-build --per_file_copt='//:aten/src/ATen/RegisterMkldnnCPU\.cpp$'@-Wno-error=unused-function
-build --per_file_copt='//:aten/src/ATen/RegisterNestedTensorCPU\.cpp$'@-Wno-error=unused-function
-build --per_file_copt='//:aten/src/ATen/RegisterQuantizedCPU\.cpp$'@-Wno-error=unused-function
-build --per_file_copt='//:aten/src/ATen/RegisterSparseCPU\.cpp$'@-Wno-error=unused-function
-build --per_file_copt='//:aten/src/ATen/RegisterSparseCsrCPU\.cpp$'@-Wno-error=unused-function
-build --per_file_copt='//:aten/src/ATen/RegisterNestedTensorMeta\.cpp$'@-Wno-error=unused-function
-build --per_file_copt='//:aten/src/ATen/RegisterSparseMeta\.cpp$'@-Wno-error=unused-function
-build --per_file_copt='//:aten/src/ATen/RegisterQuantizedMeta\.cpp$'@-Wno-error=unused-function
-build --per_file_copt='//:aten/src/ATen/RegisterZeroTensor\.cpp$'@-Wno-error=unused-function
-build --per_file_copt='//:torch/csrc/lazy/generated/RegisterAutogradLazy\.cpp$'@-Wno-error=unused-function
-build --per_file_copt='//:torch/csrc/lazy/generated/RegisterLazy\.cpp$'@-Wno-error=unused-function
+build:gpu --platform_suffix=-gpu

.buckconfig.oss

@@ -1,25 +0,0 @@
-[pt]
-  is_oss=1
-
-[buildfile]
-  name = BUCK.oss
-  includes = //tools/build_defs/select.bzl
-
-[repositories]
-  bazel_skylib = third_party/bazel-skylib/
-  ovr_config = .
-
-[download]
-  in_build = true
-
-[cxx]
-  cxxflags = -std=c++17
-  should_remap_host_platform = true
-  cpp = /usr/bin/clang
-  cc = /usr/bin/clang
-  cxx = /usr/bin/clang++
-  cxxpp = /usr/bin/clang++
-  ld = /usr/bin/clang++
-
-[project]
-  default_flavors_mode=all

.circleci/README.md

@@ -1,8 +1,3 @@
-Warning
-=======
-
-Contents may be out of date. Our CircleCI workflows are gradually being migrated to Github actions.
-
 Structure of CI
 ===============
 
@@ -21,6 +16,8 @@ setup job:
    not, even if there isn't a Git checkout.
 
 
+
+
 CircleCI configuration generator
 ================================
 
@@ -59,6 +56,7 @@ See comment [here](https://github.com/pytorch/pytorch/pull/17323#pullrequestrevi
 
 In contrast with a full recursive tree traversal of configuration dimensions,
 > in the future I think we actually want to decrease our matrix somewhat and have only a few mostly-orthogonal builds that taste as many different features as possible on PRs, plus a more complete suite on every PR and maybe an almost full suite nightly/weekly (we don't have this yet). Specifying PR jobs in the future might be easier to read with an explicit list when we come to this.
+
 ----------------
 ----------------
 
@@ -73,9 +71,9 @@ A **binary configuration** is a collection of
 * release or nightly
     * releases are stable, nightlies are beta and built every night
 * python version
-    * linux: 3.7m (mu is wide unicode or something like that. It usually doesn't matter but you should know that it exists)
-    * macos: 3.7, 3.8
-    * windows: 3.7, 3.8
+    * linux: 3.5m, 3.6m 3.7m (mu is wide unicode or something like that. It usually doesn't matter but you should know that it exists)
+    * macos: 3.6, 3.7, 3.8
+    * windows: 3.6, 3.7, 3.8
 * cpu version
     * cpu, cuda 9.0, cuda 10.0
     * The supported cuda versions occasionally change
@@ -190,6 +188,18 @@ binary_run_in_docker.sh is a way to share the docker start-up code between the b
 
 We want all the nightly binary jobs to run on the exact same git commit, so we wrote our own checkout logic to ensure that the same commit was always picked. Later circleci changed that to use a single pytorch checkout and persist it through the workspace (they did this because our config file was too big, so they wanted to take a lot of the setup code into scripts, but the scripts needed the code repo to exist to be called, so they added a prereq step called 'setup' to checkout the code and persist the needed scripts to the workspace). The changes to the binary jobs were not properly tested, so they all broke from missing pytorch code no longer existing. We hotfixed the problem by adding the pytorch checkout back to binary_checkout, so now there's two checkouts of pytorch on the binary jobs. This problem still needs to be fixed, but it takes careful tracing of which code is being called where.
 
+# Azure Pipelines structure of the binaries
+
+TODO: fill in stuff
+
+## How are the workflows structured?
+
+TODO: fill in stuff
+
+## How are the jobs structured?
+
+TODO: fill in stuff
+
 # Code structure of the binaries (circleci agnostic)
 
 ## Overview
@@ -205,22 +215,28 @@ pytorch/pytorch
   - config.yml              # GENERATED file that actually controls all circleci behavior
   - verbatim-sources        # Used to generate job/workflow sections in ^
   - scripts/                # Code needed to prepare circleci environments for binary build scripts
+
 - setup.py                  # Builds pytorch. This is wrapped in pytorch/builder
 - cmake files               # used in normal building of pytorch
+
 # All code needed to prepare a binary build, given an environment
 # with all the right variables/packages/paths.
 pytorch/builder
+
 # Given an installed binary and a proper python env, runs some checks
 # to make sure the binary was built the proper way. Checks things like
 # the library dependencies, symbols present, etc.
 - check_binary.sh
+
 # Given an installed binary, runs python tests to make sure everything
 # is in order. These should be de-duped. Right now they both run smoke
 # tests, but are called from different places. Usually just call some
 # import statements, but also has overlap with check_binary.sh above
 - run_tests.sh
 - smoke_test.sh
+
 # Folders that govern how packages are built. See paragraphs below
+
 - conda/
   - build_pytorch.sh          # Entrypoint. Delegates to proper conda build folder
   - switch_cuda_version.sh    # Switches activate CUDA installation in Docker
@@ -349,28 +365,36 @@ Writing PRs that test the binaries is annoying, since the default circleci jobs
 ```sh
 # Make your changes
 touch .circleci/verbatim-sources/nightly-binary-build-defaults.yml
+
 # Regenerate the yaml, has to be in python 3.7
 .circleci/regenerate.sh
+
 # Make a commit
 git add .circleci *
 git commit -m "My real changes"
 git push origin my_branch
+
 # Now hardcode the jobs that you want in the .circleci/config.yml workflows section
 # Also eliminate ensure-consistency and should_run_job checks
 # e.g. https://github.com/pytorch/pytorch/commit/2b3344bfed8772fe86e5210cc4ee915dee42b32d
+
 # Make a commit you won't keep
 git add .circleci
 git commit -m "[DO NOT LAND] testing binaries for above changes"
 git push origin my_branch
+
 # Now you need to make some changes to the first commit.
 git rebase -i HEAD~2 # mark the first commit as 'edit'
+
 # Make the changes
 touch .circleci/verbatim-sources/nightly-binary-build-defaults.yml
 .circleci/regenerate.sh
+
 # Ammend the commit and recontinue
 git add .circleci
 git commit --amend
 git rebase --continue
+
 # Update the PR, need to force since the commits are different now
 git push origin my_branch --force
 ```
@@ -399,12 +423,14 @@ docker run \
     -v your/builder/repo:/builder \
     -v where/you/want/packages/to/appear:/final_pkgs \
     -it pytorch/conda-cuda /bin/bash
+
 # Export whatever variables are important to you. All variables that you'd
 # possibly need are in .circleci/scripts/binary_populate_env.sh
 # You should probably always export at least these 3 variables
 export PACKAGE_TYPE=conda
-export DESIRED_PYTHON=3.7
+export DESIRED_PYTHON=3.6
 export DESIRED_CUDA=cpu
+
 # Call the entrypoint
 # `|& tee foo.log` just copies all stdout and stderr output to foo.log
 # The builds generate lots of output so you probably need this when
@@ -428,6 +454,7 @@ But if you want to try, then I’d recommend
 # Create a new terminal
 # Clear your LD_LIBRARY_PATH and trim as much out of your PATH as you
 # know how to do
+
 # Install a new miniconda
 # First remove any other python or conda installation from your PATH
 # Always install miniconda 3, even if building for Python <3
@@ -438,17 +465,20 @@ chmod +x "$conda_sh"
 "$conda_sh" -b -p "$MINICONDA_ROOT"
 rm -f "$conda_sh"
 export PATH="~/my_new_conda/bin:$PATH"
+
 # Create a clean python env
 # All MacOS builds use conda to manage the python env and dependencies
 # that are built with, even the pip packages
 conda create -yn binary python=2.7
 conda activate binary
+
 # Export whatever variables are important to you. All variables that you'd
 # possibly need are in .circleci/scripts/binary_populate_env.sh
 # You should probably always export at least these 3 variables
 export PACKAGE_TYPE=conda
-export DESIRED_PYTHON=3.7
+export DESIRED_PYTHON=3.6
 export DESIRED_CUDA=cpu
+
 # Call the entrypoint you want
 path/to/builder/wheel/build_wheel.sh
 ```

.circleci/cimodel/data/binary_build_data.py

@@ -30,7 +30,48 @@ def get_processor_arch_name(gpu_version):
         "cu" + gpu_version.strip("cuda") if gpu_version.startswith("cuda") else gpu_version
     )
 
+LINUX_PACKAGE_VARIANTS = OrderedDict(
+    manywheel=[
+        "3.6m",
+        "3.7m",
+        "3.8m",
+        "3.9m"
+    ],
+    conda=dimensions.STANDARD_PYTHON_VERSIONS,
+    libtorch=[
+        "3.7m",
+    ],
+)
+
 CONFIG_TREE_DATA = OrderedDict(
+    linux=(dimensions.GPU_VERSIONS, LINUX_PACKAGE_VARIANTS),
+    macos=([None], OrderedDict(
+        wheel=dimensions.STANDARD_PYTHON_VERSIONS,
+        conda=dimensions.STANDARD_PYTHON_VERSIONS,
+        libtorch=[
+            "3.7",
+        ],
+    )),
+    macos_arm64=([None], OrderedDict(
+        wheel=[
+            "3.8",
+            "3.9",
+        ],
+        conda=[
+            "3.8",
+            "3.9",
+        ],
+    )),
+    windows=(
+        [v for v in dimensions.GPU_VERSIONS if v not in dimensions.ROCM_VERSION_LABELS],
+        OrderedDict(
+            wheel=dimensions.STANDARD_PYTHON_VERSIONS,
+            conda=dimensions.STANDARD_PYTHON_VERSIONS,
+            libtorch=[
+                "3.7",
+            ],
+        )
+    ),
 )
 
 # GCC config variants:

.circleci/cimodel/data/dimensions.py

@@ -2,14 +2,14 @@ PHASES = ["build", "test"]
 
 CUDA_VERSIONS = [
     "102",
+    "111",
     "113",
-    "116",
-    "117",
 ]
 
 ROCM_VERSIONS = [
-    "4.3.1",
-    "4.5.2",
+    "4.0.1",
+    "4.1",
+    "4.2",
 ]
 
 ROCM_VERSION_LABELS = ["rocm" + v for v in ROCM_VERSIONS]
@@ -17,8 +17,8 @@ ROCM_VERSION_LABELS = ["rocm" + v for v in ROCM_VERSIONS]
 GPU_VERSIONS = [None] + ["cuda" + v for v in CUDA_VERSIONS] + ROCM_VERSION_LABELS
 
 STANDARD_PYTHON_VERSIONS = [
+    "3.6",
     "3.7",
     "3.8",
-    "3.9",
-    "3.10"
+    "3.9"
 ]

.circleci/cimodel/data/pytorch_build_data.py

@@ -1,7 +1,70 @@
-from cimodel.lib.conf_tree import ConfigNode
+from cimodel.lib.conf_tree import ConfigNode, X, XImportant
 
 
 CONFIG_TREE_DATA = [
+    ("xenial", [
+        ("gcc", [
+            ("5.4", [  # All this subtree rebases to master and then build
+                ("3.6", [
+                    ("important", [X(True)]),
+                ]),
+            ]),
+            # TODO: bring back libtorch test
+            ("7", [X("3.6")]),
+        ]),
+        ("clang", [
+            ("7", [
+                ("3.6", [
+                    ("asan", [
+                        (True, [
+                            ("shard_test", [XImportant(True)]),
+                        ]),
+                    ]),
+                    ("onnx", [XImportant(True)]),
+                ]),
+            ]),
+        ]),
+        ("cuda", [
+            ("10.2", [
+                ("3.6", [
+                    # Build are needed for slow_gradcheck
+                    ('build_only', [X(True)]),
+                    ("slow_gradcheck", [
+                        # If you update this slow gradcheck, you should
+                        # also update docker_definitions.py to make sure
+                        # the docker image match the config used here
+                        (True, [
+                            ('shard_test', [XImportant(True)]),
+                        ]),
+                    ]),
+                    # UNCOMMENT THE BELOW TO REENABLE LIBTORCH
+                    # ("libtorch", [
+                    #     (True, [
+                    #         ('build_only', [X(True)]),
+                    #     ]),
+                    # ]),
+                ]),
+            ]),
+        ]),
+    ]),
+    ("bionic", [
+        ("clang", [
+            ("9", [
+                ("3.6", [
+                    ("xla", [XImportant(True)]),
+                    ("vulkan", [XImportant(True)]),
+                ]),
+            ]),
+        ]),
+        # @jithunnair-amd believes Jenkins builds are sufficient
+        # ("rocm", [
+        #     ("3.9", [
+        #         ("3.6", [
+        #             ('build_only', [XImportant(True)]),
+        #         ]),
+        #     ]),
+        # ]),
+    ]),
 ]
 
 
@@ -71,11 +134,10 @@ class ExperimentalFeatureConfigNode(TreeConfigNode):
         next_nodes = {
             "asan": AsanConfigNode,
             "xla": XlaConfigNode,
-            "mps": MPSConfigNode,
+            "mlc": MLCConfigNode,
             "vulkan": VulkanConfigNode,
             "parallel_tbb": ParallelTBBConfigNode,
-            "crossref": CrossRefConfigNode,
-            "dynamo": DynamoConfigNode,
+            "noarch": NoarchConfigNode,
             "parallel_native": ParallelNativeConfigNode,
             "onnx": ONNXConfigNode,
             "libtorch": LibTorchConfigNode,
@@ -83,6 +145,7 @@ class ExperimentalFeatureConfigNode(TreeConfigNode):
             "build_only": BuildOnlyConfigNode,
             "shard_test": ShardTestConfigNode,
             "cuda_gcc_override": CudaGccOverrideConfigNode,
+            "coverage": CoverageConfigNode,
             "pure_torch": PureTorchConfigNode,
             "slow_gradcheck": SlowGradcheckConfigNode,
         }
@@ -117,12 +180,12 @@ class XlaConfigNode(TreeConfigNode):
     def child_constructor(self):
         return ImportantConfigNode
 
-class MPSConfigNode(TreeConfigNode):
+class MLCConfigNode(TreeConfigNode):
     def modify_label(self, label):
-        return "MPS=" + str(label)
+        return "MLC=" + str(label)
 
     def init2(self, node_name):
-        self.props["is_mps"] = node_name
+        self.props["is_mlc"] = node_name
 
     def child_constructor(self):
         return ImportantConfigNode
@@ -172,17 +235,9 @@ class ParallelTBBConfigNode(TreeConfigNode):
         return ImportantConfigNode
 
 
-class CrossRefConfigNode(TreeConfigNode):
+class NoarchConfigNode(TreeConfigNode):
     def init2(self, node_name):
-        self.props["is_crossref"] = node_name
-
-    def child_constructor(self):
-        return ImportantConfigNode
-
-
-class DynamoConfigNode(TreeConfigNode):
-    def init2(self, node_name):
-        self.props["is_dynamo"] = node_name
+        self.props["is_noarch"] = node_name
 
     def child_constructor(self):
         return ImportantConfigNode
@@ -234,6 +289,14 @@ class ShardTestConfigNode(TreeConfigNode):
         return ImportantConfigNode
 
 
+class CoverageConfigNode(TreeConfigNode):
+    def init2(self, node_name):
+        self.props["is_coverage"] = node_name
+
+    def child_constructor(self):
+        return ExperimentalFeatureConfigNode
+
+
 class ImportantConfigNode(TreeConfigNode):
     def modify_label(self, label):
         return "IMPORTANT=" + str(label)

.circleci/cimodel/data/pytorch_build_definitions.py

@@ -185,7 +185,7 @@ def gen_docs_configs(xenial_parent_config):
         HiddenConf(
             "pytorch_python_doc_build",
             parent_build=xenial_parent_config,
-            filters=gen_filter_dict(branches_list=["master", "main", "nightly"],
+            filters=gen_filter_dict(branches_list=["master", "nightly"],
                                     tags_list=RC_PATTERN),
         )
     )
@@ -201,7 +201,7 @@ def gen_docs_configs(xenial_parent_config):
         HiddenConf(
             "pytorch_cpp_doc_build",
             parent_build=xenial_parent_config,
-            filters=gen_filter_dict(branches_list=["master", "main", "nightly"],
+            filters=gen_filter_dict(branches_list=["master", "nightly"],
                                     tags_list=RC_PATTERN),
         )
     )
@@ -239,8 +239,8 @@ def instantiate_configs(only_slow_gradcheck):
         compiler_version = fc.find_prop("compiler_version")
         is_xla = fc.find_prop("is_xla") or False
         is_asan = fc.find_prop("is_asan") or False
-        is_crossref = fc.find_prop("is_crossref") or False
-        is_dynamo = fc.find_prop("is_dynamo") or False
+        is_coverage = fc.find_prop("is_coverage") or False
+        is_noarch = fc.find_prop("is_noarch") or False
         is_onnx = fc.find_prop("is_onnx") or False
         is_pure_torch = fc.find_prop("is_pure_torch") or False
         is_vulkan = fc.find_prop("is_vulkan") or False
@@ -284,11 +284,12 @@ def instantiate_configs(only_slow_gradcheck):
             python_version = fc.find_prop("pyver")
             parms_list[0] = fc.find_prop("abbreviated_pyver")
 
-        if is_crossref:
-            parms_list_ignored_for_docker_image.append("crossref")
+        if is_coverage:
+            parms_list_ignored_for_docker_image.append("coverage")
+            python_version = fc.find_prop("pyver")
 
-        if is_dynamo:
-            parms_list_ignored_for_docker_image.append("dynamo")
+        if is_noarch:
+            parms_list_ignored_for_docker_image.append("noarch")
 
         if is_onnx:
             parms_list.append("onnx")
@@ -338,12 +339,13 @@ def instantiate_configs(only_slow_gradcheck):
             build_only=build_only,
         )
 
-        # run docs builds on "pytorch-linux-xenial-py3.7-gcc5.4". Docs builds
+        # run docs builds on "pytorch-linux-xenial-py3.6-gcc5.4". Docs builds
         # should run on a CPU-only build that runs on all PRs.
-        # XXX should this be updated to a more modern build?
+        # XXX should this be updated to a more modern build? Projects are
+        #     beginning to drop python3.6
         if (
             distro_name == "xenial"
-            and fc.find_prop("pyver") == "3.7"
+            and fc.find_prop("pyver") == "3.6"
             and cuda_version is None
             and parallel_backend is None
             and not is_vulkan
@@ -355,6 +357,28 @@ def instantiate_configs(only_slow_gradcheck):
                                         tags_list=RC_PATTERN)
             c.dependent_tests = gen_docs_configs(c)
 
+        if (
+            compiler_name != "clang"
+            and not rocm_version
+            and not is_libtorch
+            and not is_vulkan
+            and not is_pure_torch
+            and not is_noarch
+            and not is_slow_gradcheck
+            and not only_slow_gradcheck
+            and not build_only
+        ):
+            distributed_test = Conf(
+                c.gen_build_name("") + "distributed",
+                [],
+                is_xla=False,
+                restrict_phases=["test"],
+                is_libtorch=False,
+                is_important=True,
+                parent_build=c,
+            )
+            c.dependent_tests.append(distributed_test)
+
         config_list.append(c)
 
     return config_list

.circleci/cimodel/data/simple/android_definitions.py

@@ -0,0 +1,119 @@
+import cimodel.data.simple.util.branch_filters as branch_filters
+from cimodel.data.simple.util.docker_constants import (
+    DOCKER_IMAGE_NDK, DOCKER_REQUIREMENT_NDK
+)
+import cimodel.lib.miniutils as miniutils
+
+
+class AndroidJob:
+    def __init__(self,
+                 variant,
+                 template_name,
+                 is_master_only=True):
+
+        self.variant = variant
+        self.template_name = template_name
+        self.is_master_only = is_master_only
+
+    def gen_tree(self):
+
+        base_name_parts = [
+            "pytorch",
+            "linux",
+            "xenial",
+            "py3",
+            "clang5",
+            "android",
+            "ndk",
+            "r19c",
+        ] + self.variant + [
+            "build",
+        ]
+
+        full_job_name = "_".join(base_name_parts)
+        build_env_name = "-".join(base_name_parts)
+
+        props_dict = {
+            "name": full_job_name,
+            "build_environment": "\"{}\"".format(build_env_name),
+            "docker_image": "\"{}\"".format(DOCKER_IMAGE_NDK),
+            "requires": [DOCKER_REQUIREMENT_NDK]
+        }
+
+        if self.is_master_only:
+            props_dict["filters"] = branch_filters.gen_filter_dict(branch_filters.NON_PR_BRANCH_LIST)
+
+        return [{self.template_name: props_dict}]
+
+
+class AndroidGradleJob:
+    def __init__(self,
+                 job_name,
+                 template_name,
+                 dependencies,
+                 is_master_only=True,
+                 is_pr_only=False,
+                 extra_props=tuple()):
+
+        self.job_name = job_name
+        self.template_name = template_name
+        self.dependencies = dependencies
+        self.is_master_only = is_master_only
+        self.is_pr_only = is_pr_only
+        self.extra_props = dict(extra_props)
+
+    def gen_tree(self):
+
+        props_dict = {
+            "name": self.job_name,
+            "requires": self.dependencies,
+        }
+
+        if self.is_master_only:
+            props_dict["filters"] = branch_filters.gen_filter_dict(branch_filters.NON_PR_BRANCH_LIST)
+        elif self.is_pr_only:
+            props_dict["filters"] = branch_filters.gen_filter_dict(branch_filters.PR_BRANCH_LIST)
+        if self.extra_props:
+            props_dict.update(self.extra_props)
+
+        return [{self.template_name: props_dict}]
+
+
+WORKFLOW_DATA = [
+    AndroidJob(["x86_32"], "pytorch_linux_build", is_master_only=False),
+    AndroidJob(["x86_64"], "pytorch_linux_build"),
+    AndroidJob(["arm", "v7a"], "pytorch_linux_build"),
+    AndroidJob(["arm", "v8a"], "pytorch_linux_build"),
+    AndroidGradleJob(
+        "pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-build-x86_32",
+        "pytorch_android_gradle_build-x86_32",
+        ["pytorch_linux_xenial_py3_clang5_android_ndk_r19c_x86_32_build"],
+        is_master_only=False,
+        is_pr_only=True),
+    AndroidGradleJob(
+        "pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-custom-build-single",
+        "pytorch_android_gradle_custom_build_single",
+        [DOCKER_REQUIREMENT_NDK],
+        is_master_only=False,
+        is_pr_only=True),
+    AndroidGradleJob(
+        "pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-custom-build-single-full-jit",
+        "pytorch_android_gradle_custom_build_single",
+        [DOCKER_REQUIREMENT_NDK],
+        is_master_only=False,
+        is_pr_only=True,
+        extra_props=tuple({
+            "lite_interpreter": miniutils.quote(str(int(False)))
+        }.items())),
+    AndroidGradleJob(
+        "pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-build",
+        "pytorch_android_gradle_build",
+        ["pytorch_linux_xenial_py3_clang5_android_ndk_r19c_x86_32_build",
+         "pytorch_linux_xenial_py3_clang5_android_ndk_r19c_x86_64_build",
+         "pytorch_linux_xenial_py3_clang5_android_ndk_r19c_arm_v7a_build",
+         "pytorch_linux_xenial_py3_clang5_android_ndk_r19c_arm_v8a_build"]),
+]
+
+
+def get_workflow_jobs():
+    return [item.gen_tree() for item in WORKFLOW_DATA]

.circleci/cimodel/data/simple/bazel_definitions.py

@@ -0,0 +1,69 @@
+from cimodel.data.simple.util.docker_constants import (
+    DOCKER_IMAGE_GCC7,
+    DOCKER_REQUIREMENT_GCC7
+)
+
+
+def gen_job_name(phase):
+    job_name_parts = [
+        "pytorch",
+        "bazel",
+        phase,
+    ]
+
+    return "_".join(job_name_parts)
+
+
+class BazelJob:
+    def __init__(self, phase, extra_props=None):
+        self.phase = phase
+        self.extra_props = extra_props or {}
+
+    def gen_tree(self):
+
+        template_parts = [
+            "pytorch",
+            "linux",
+            "bazel",
+            self.phase,
+        ]
+
+        build_env_parts = [
+            "pytorch",
+            "linux",
+            "xenial",
+            "py3.6",
+            "gcc7",
+            "bazel",
+            self.phase,
+        ]
+
+        full_job_name = gen_job_name(self.phase)
+        build_env_name = "-".join(build_env_parts)
+
+        extra_requires = (
+            [gen_job_name("build")] if self.phase == "test" else
+            [DOCKER_REQUIREMENT_GCC7]
+        )
+
+        props_dict = {
+            "build_environment": build_env_name,
+            "docker_image": DOCKER_IMAGE_GCC7,
+            "name": full_job_name,
+            "requires": extra_requires,
+        }
+
+        props_dict.update(self.extra_props)
+
+        template_name = "_".join(template_parts)
+        return [{template_name: props_dict}]
+
+
+WORKFLOW_DATA = [
+    BazelJob("build", {"resource_class": "large"}),
+    BazelJob("test"),
+]
+
+
+def get_workflow_jobs():
+    return [item.gen_tree() for item in WORKFLOW_DATA]

.circleci/cimodel/data/simple/binary_smoketest.py

@@ -0,0 +1,193 @@
+"""
+TODO: Refactor circleci/cimodel/data/binary_build_data.py to generate this file
+       instead of doing one offs here
+ Binary builds (subset, to smoke test that they'll work)
+
+ NB: If you modify this file, you need to also modify
+ the binary_and_smoke_tests_on_pr variable in
+ pytorch-ci-hud to adjust the allowed build list
+ at https://github.com/ezyang/pytorch-ci-hud/blob/master/src/BuildHistoryDisplay.js
+
+ Note:
+ This binary build is currently broken, see https://github_com/pytorch/pytorch/issues/16710
+ - binary_linux_conda_3_6_cu90_devtoolset7_build
+ - binary_linux_conda_3_6_cu90_devtoolset7_test
+
+ TODO
+ we should test a libtorch cuda build, but they take too long
+ - binary_linux_libtorch_3_6m_cu90_devtoolset7_static-without-deps_build
+"""
+
+import cimodel.lib.miniutils as miniutils
+import cimodel.data.simple.util.branch_filters
+
+
+class SmoketestJob:
+    def __init__(self,
+                 template_name,
+                 build_env_parts,
+                 docker_image,
+                 job_name,
+                 is_master_only=False,
+                 requires=None,
+                 has_libtorch_variant=False,
+                 extra_props=None):
+
+        self.template_name = template_name
+        self.build_env_parts = build_env_parts
+        self.docker_image = docker_image
+        self.job_name = job_name
+        self.is_master_only = is_master_only
+        self.requires = requires or []
+        self.has_libtorch_variant = has_libtorch_variant
+        self.extra_props = extra_props or {}
+
+    def gen_tree(self):
+
+        props_dict = {
+            "build_environment": " ".join(self.build_env_parts),
+            "name": self.job_name,
+            "requires": self.requires,
+        }
+
+        if self.docker_image:
+            props_dict["docker_image"] = self.docker_image
+
+        if self.is_master_only:
+            props_dict["filters"] = cimodel.data.simple.util.branch_filters.gen_filter_dict()
+
+        if self.has_libtorch_variant:
+            props_dict["libtorch_variant"] = "shared-with-deps"
+
+        props_dict.update(self.extra_props)
+
+        return [{self.template_name: props_dict}]
+
+
+WORKFLOW_DATA = [
+    SmoketestJob(
+        "binary_linux_build",
+        ["manywheel", "3.7m", "cu102", "devtoolset7"],
+        "pytorch/manylinux-cuda102",
+        "binary_linux_manywheel_3_7m_cu102_devtoolset7_build",
+        is_master_only=True,
+    ),
+    SmoketestJob(
+        "binary_linux_build",
+        ["libtorch", "3.7m", "cpu", "devtoolset7"],
+        "pytorch/manylinux-cuda102",
+        "binary_linux_libtorch_3_7m_cpu_devtoolset7_shared-with-deps_build",
+        is_master_only=True,
+        has_libtorch_variant=True,
+    ),
+    SmoketestJob(
+        "binary_linux_build",
+        ["libtorch", "3.7m", "cpu", "gcc5.4_cxx11-abi"],
+        "pytorch/pytorch-binary-docker-image-ubuntu16.04:latest",
+        "binary_linux_libtorch_3_7m_cpu_gcc5_4_cxx11-abi_shared-with-deps_build",
+        is_master_only=False,
+        has_libtorch_variant=True,
+    ),
+    SmoketestJob(
+        "binary_mac_build",
+        ["wheel", "3.7", "cpu"],
+        None,
+        "binary_macos_wheel_3_7_cpu_build",
+        is_master_only=True,
+    ),
+    # This job has an average run time of 3 hours o.O
+    # Now only running this on master to reduce overhead
+    SmoketestJob(
+        "binary_mac_build",
+        ["libtorch", "3.7", "cpu"],
+        None,
+        "binary_macos_libtorch_3_7_cpu_build",
+        is_master_only=True,
+    ),
+    SmoketestJob(
+        "binary_windows_build",
+        ["libtorch", "3.7", "cpu", "debug"],
+        None,
+        "binary_windows_libtorch_3_7_cpu_debug_build",
+        is_master_only=True,
+    ),
+    SmoketestJob(
+        "binary_windows_build",
+        ["libtorch", "3.7", "cpu", "release"],
+        None,
+        "binary_windows_libtorch_3_7_cpu_release_build",
+        is_master_only=True,
+    ),
+    SmoketestJob(
+        "binary_windows_build",
+        ["wheel", "3.7", "cu102"],
+        None,
+        "binary_windows_wheel_3_7_cu102_build",
+        is_master_only=True,
+    ),
+
+    SmoketestJob(
+        "binary_windows_test",
+        ["libtorch", "3.7", "cpu", "debug"],
+        None,
+        "binary_windows_libtorch_3_7_cpu_debug_test",
+        is_master_only=True,
+        requires=["binary_windows_libtorch_3_7_cpu_debug_build"],
+    ),
+    SmoketestJob(
+        "binary_windows_test",
+        ["libtorch", "3.7", "cpu", "release"],
+        None,
+        "binary_windows_libtorch_3_7_cpu_release_test",
+        is_master_only=False,
+        requires=["binary_windows_libtorch_3_7_cpu_release_build"],
+    ),
+    SmoketestJob(
+        "binary_windows_test",
+        ["wheel", "3.7", "cu102"],
+        None,
+        "binary_windows_wheel_3_7_cu102_test",
+        is_master_only=True,
+        requires=["binary_windows_wheel_3_7_cu102_build"],
+        extra_props={
+            "executor": "windows-with-nvidia-gpu",
+        },
+    ),
+
+
+
+    SmoketestJob(
+        "binary_linux_test",
+        ["manywheel", "3.7m", "cu102", "devtoolset7"],
+        "pytorch/manylinux-cuda102",
+        "binary_linux_manywheel_3_7m_cu102_devtoolset7_test",
+        is_master_only=True,
+        requires=["binary_linux_manywheel_3_7m_cu102_devtoolset7_build"],
+        extra_props={
+            "resource_class": "gpu.medium",
+            "use_cuda_docker_runtime": miniutils.quote((str(1))),
+        },
+    ),
+    SmoketestJob(
+        "binary_linux_test",
+        ["libtorch", "3.7m", "cpu", "devtoolset7"],
+        "pytorch/manylinux-cuda102",
+        "binary_linux_libtorch_3_7m_cpu_devtoolset7_shared-with-deps_test",
+        is_master_only=True,
+        requires=["binary_linux_libtorch_3_7m_cpu_devtoolset7_shared-with-deps_build"],
+        has_libtorch_variant=True,
+    ),
+    SmoketestJob(
+        "binary_linux_test",
+        ["libtorch", "3.7m", "cpu", "gcc5.4_cxx11-abi"],
+        "pytorch/pytorch-binary-docker-image-ubuntu16.04:latest",
+        "binary_linux_libtorch_3_7m_cpu_gcc5_4_cxx11-abi_shared-with-deps_test",
+        is_master_only=True,
+        requires=["binary_linux_libtorch_3_7m_cpu_gcc5_4_cxx11-abi_shared-with-deps_build"],
+        has_libtorch_variant=True,
+    ),
+]
+
+
+def get_workflow_jobs():
+    return [item.gen_tree() for item in WORKFLOW_DATA]

.circleci/cimodel/data/simple/docker_definitions.py

@@ -4,8 +4,27 @@ from cimodel.lib.miniutils import quote
 from cimodel.data.simple.util.branch_filters import gen_filter_dict, RC_PATTERN
 
 
-# NOTE: All hardcoded docker image builds have been migrated to GHA
+# TODO: make this generated from a matrix rather than just a static list
 IMAGE_NAMES = [
+    "pytorch-linux-bionic-cuda10.2-cudnn7-py3.9-gcc7",
+    "pytorch-linux-bionic-py3.6-clang9",
+    "pytorch-linux-bionic-cuda10.2-cudnn7-py3.6-clang9",
+    "pytorch-linux-bionic-py3.8-gcc9",
+    "pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7",
+    "pytorch-linux-xenial-cuda11.1-cudnn8-py3-gcc7",
+    "pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7",
+    "pytorch-linux-xenial-py3-clang5-android-ndk-r19c",
+    "pytorch-linux-xenial-py3-clang5-asan",
+    "pytorch-linux-xenial-py3-clang7-asan",
+    "pytorch-linux-xenial-py3-clang7-onnx",
+    "pytorch-linux-xenial-py3.8",
+    "pytorch-linux-xenial-py3.6-clang7",
+    "pytorch-linux-xenial-py3.6-gcc5.4",  # this one is used in doc builds
+    "pytorch-linux-xenial-py3.6-gcc7.2",
+    "pytorch-linux-xenial-py3.6-gcc7",
+    "pytorch-linux-bionic-rocm4.1-py3.6",
+    "pytorch-linux-bionic-rocm4.2-py3.6",
+    "pytorch-linux-bionic-rocm4.3.1-py3.6",
 ]
 
 # This entry should be an element from the list above
@@ -13,12 +32,10 @@ IMAGE_NAMES = [
 # pytorch_build_data.py
 SLOW_GRADCHECK_IMAGE_NAME = "pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7"
 
-def get_workflow_jobs(images=IMAGE_NAMES, only_slow_gradcheck=False):
+def get_workflow_jobs(only_slow_gradcheck=False):
     """Generates a list of docker image build definitions"""
     ret = []
-    for image_name in images:
-        if image_name.startswith('docker-'):
-            image_name = image_name.lstrip('docker-')
+    for image_name in IMAGE_NAMES:
         if only_slow_gradcheck and image_name is not SLOW_GRADCHECK_IMAGE_NAME:
             continue
 
@@ -26,7 +43,7 @@ def get_workflow_jobs(images=IMAGE_NAMES, only_slow_gradcheck=False):
             "name": quote(f"docker-{image_name}"),
             "image_name": quote(image_name),
         })
-        if image_name == "pytorch-linux-xenial-py3.7-gcc5.4":
+        if image_name == "pytorch-linux-xenial-py3.6-gcc5.4":
             # pushing documentation on tags requires CircleCI to also
             # build all the dependencies on tags, including this docker image
             parameters['filters'] = gen_filter_dict(branches_list=r"/.*/",

.circleci/cimodel/data/simple/ios_definitions.py

@@ -1,5 +1,4 @@
 from cimodel.data.simple.util.versions import MultiPartVersion
-from cimodel.data.simple.util.branch_filters import gen_filter_dict_exclude
 import cimodel.lib.miniutils as miniutils
 
 XCODE_VERSION = MultiPartVersion([12, 5, 1])
@@ -12,7 +11,7 @@ class ArchVariant:
 
     def render(self):
         extra_parts = [self.custom_build_name] if len(self.custom_build_name) > 0 else []
-        return "-".join([self.name] + extra_parts).replace("_", "-")
+        return "_".join([self.name] + extra_parts)
 
 
 def get_platform(arch_variant_name):
@@ -26,25 +25,30 @@ class IOSJob:
         self.is_org_member_context = is_org_member_context
         self.extra_props = extra_props
 
-    def gen_name_parts(self):
-        version_parts = self.xcode_version.render_dots_or_parts("-")
-        build_variant_suffix = self.arch_variant.render()
+    def gen_name_parts(self, with_version_dots):
+
+        version_parts = self.xcode_version.render_dots_or_parts(with_version_dots)
+        build_variant_suffix = "_".join([self.arch_variant.render(), "build"])
+
         return [
+            "pytorch",
             "ios",
         ] + version_parts + [
             build_variant_suffix,
         ]
 
     def gen_job_name(self):
-        return "-".join(self.gen_name_parts())
+        return "_".join(self.gen_name_parts(False))
 
     def gen_tree(self):
+
         platform_name = get_platform(self.arch_variant.name)
+
         props_dict = {
-            "name": self.gen_job_name(),
-            "build_environment": self.gen_job_name(),
+            "build_environment": "-".join(self.gen_name_parts(True)),
             "ios_arch": self.arch_variant.name,
             "ios_platform": platform_name,
+            "name": self.gen_job_name(),
         }
 
         if self.is_org_member_context:
@@ -53,28 +57,24 @@ class IOSJob:
         if self.extra_props:
             props_dict.update(self.extra_props)
 
-        props_dict["filters"] = gen_filter_dict_exclude()
-
         return [{"pytorch_ios_build": props_dict}]
 
 
 WORKFLOW_DATA = [
     IOSJob(XCODE_VERSION, ArchVariant("x86_64"), is_org_member_context=False, extra_props={
         "lite_interpreter": miniutils.quote(str(int(True)))}),
-    # IOSJob(XCODE_VERSION, ArchVariant("arm64"), extra_props={
-    #     "lite_interpreter": miniutils.quote(str(int(True)))}),
-    # IOSJob(XCODE_VERSION, ArchVariant("arm64", "metal"), extra_props={
-    #     "use_metal": miniutils.quote(str(int(True))),
-    #     "lite_interpreter": miniutils.quote(str(int(True)))}),
-    # IOSJob(XCODE_VERSION, ArchVariant("arm64", "custom-ops"), extra_props={
-    #     "op_list": "mobilenetv2.yaml",
-    #     "lite_interpreter": miniutils.quote(str(int(True)))}),
-    IOSJob(XCODE_VERSION, ArchVariant("x86_64", "coreml"), is_org_member_context=False, extra_props={
-        "use_coreml": miniutils.quote(str(int(True))),
+    IOSJob(XCODE_VERSION, ArchVariant("x86_64", "full_jit"), is_org_member_context=False, extra_props={
+        "lite_interpreter": miniutils.quote(str(int(False)))}),
+    IOSJob(XCODE_VERSION, ArchVariant("arm64"), extra_props={
+        "lite_interpreter": miniutils.quote(str(int(True)))}),
+    IOSJob(XCODE_VERSION, ArchVariant("arm64", "metal"), extra_props={
+        "use_metal": miniutils.quote(str(int(True))),
+        "lite_interpreter": miniutils.quote(str(int(True)))}),
+    IOSJob(XCODE_VERSION, ArchVariant("arm64", "full_jit"), extra_props={
+        "lite_interpreter": miniutils.quote(str(int(False)))}),
+    IOSJob(XCODE_VERSION, ArchVariant("arm64", "custom"), extra_props={
+        "op_list": "mobilenetv2.yaml",
         "lite_interpreter": miniutils.quote(str(int(True)))}),
-    # IOSJob(XCODE_VERSION, ArchVariant("arm64", "coreml"), extra_props={
-    #     "use_coreml": miniutils.quote(str(int(True))),
-    #     "lite_interpreter": miniutils.quote(str(int(True)))}),
 ]
 
 

.circleci/cimodel/data/simple/macos_definitions.py

@@ -11,14 +11,10 @@ class MacOsJob:
         non_phase_parts = ["pytorch", "macos", self.os_version, "py3"]
 
         extra_name_list = [name for name, exist in self.extra_props.items() if exist]
-        full_job_name_list = (
-            non_phase_parts
-            + extra_name_list
-            + [
-                "build" if self.is_build else None,
-                "test" if self.is_test else None,
-            ]
-        )
+        full_job_name_list = non_phase_parts + extra_name_list + [
+            'build' if self.is_build else None,
+            'test' if self.is_test else None,
+        ]
 
         full_job_name = "_".join(list(filter(None, full_job_name_list)))
 
@@ -45,8 +41,10 @@ WORKFLOW_DATA = [
         "10_13",
         is_build=True,
         is_test=True,
-        extra_props=tuple({"lite_interpreter": True}.items()),
-    ),
+        extra_props=tuple({
+            "lite_interpreter": True
+        }.items()),
+    )
 ]
 
 

.circleci/cimodel/data/simple/mobile_definitions.py

@@ -4,6 +4,12 @@ PyTorch Mobile PR builds (use linux host toolchain + mobile build options)
 
 import cimodel.lib.miniutils as miniutils
 import cimodel.data.simple.util.branch_filters
+from cimodel.data.simple.util.docker_constants import (
+    DOCKER_IMAGE_ASAN,
+    DOCKER_REQUIREMENT_ASAN,
+    DOCKER_IMAGE_NDK,
+    DOCKER_REQUIREMENT_NDK
+)
 
 
 class MobileJob:
@@ -46,6 +52,33 @@ class MobileJob:
 
 
 WORKFLOW_DATA = [
+    MobileJob(
+        DOCKER_IMAGE_ASAN,
+        [DOCKER_REQUIREMENT_ASAN],
+        ["build"]
+    ),
+
+    # Use LLVM-DEV toolchain in android-ndk-r19c docker image
+    MobileJob(
+        DOCKER_IMAGE_NDK,
+        [DOCKER_REQUIREMENT_NDK],
+        ["custom", "build", "dynamic"]
+    ),
+
+    MobileJob(
+        DOCKER_IMAGE_NDK,
+        [DOCKER_REQUIREMENT_NDK],
+        ["custom", "build", "static"]
+    ),
+
+    # Use LLVM-DEV toolchain in android-ndk-r19c docker image
+    # Most of this CI is already covered by "mobile-custom-build-dynamic" job
+    MobileJob(
+        DOCKER_IMAGE_NDK,
+        [DOCKER_REQUIREMENT_NDK],
+        ["code", "analysis"],
+        True
+    ),
 ]
 
 

.circleci/cimodel/data/simple/nightly_android.py

@@ -0,0 +1,77 @@
+from cimodel.data.simple.util.docker_constants import (
+    DOCKER_IMAGE_NDK,
+    DOCKER_REQUIREMENT_NDK
+)
+
+
+class AndroidNightlyJob:
+    def __init__(self,
+                 variant,
+                 template_name,
+                 extra_props=None,
+                 with_docker=True,
+                 requires=None,
+                 no_build_suffix=False):
+
+        self.variant = variant
+        self.template_name = template_name
+        self.extra_props = extra_props or {}
+        self.with_docker = with_docker
+        self.requires = requires
+        self.no_build_suffix = no_build_suffix
+
+    def gen_tree(self):
+
+        base_name_parts = [
+            "pytorch",
+            "linux",
+            "xenial",
+            "py3",
+            "clang5",
+            "android",
+            "ndk",
+            "r19c",
+        ] + self.variant
+
+        build_suffix = [] if self.no_build_suffix else ["build"]
+        full_job_name = "_".join(["nightly"] + base_name_parts + build_suffix)
+        build_env_name = "-".join(base_name_parts)
+
+        props_dict = {
+            "name": full_job_name,
+            "requires": self.requires,
+            "filters": {"branches": {"only": "nightly"}},
+        }
+
+        props_dict.update(self.extra_props)
+
+        if self.with_docker:
+            props_dict["docker_image"] = DOCKER_IMAGE_NDK
+            props_dict["build_environment"] = build_env_name
+
+        return [{self.template_name: props_dict}]
+
+BASE_REQUIRES = [DOCKER_REQUIREMENT_NDK]
+
+WORKFLOW_DATA = [
+    AndroidNightlyJob(["x86_32"], "pytorch_linux_build", requires=BASE_REQUIRES),
+    AndroidNightlyJob(["x86_64"], "pytorch_linux_build", requires=BASE_REQUIRES),
+    AndroidNightlyJob(["arm", "v7a"], "pytorch_linux_build", requires=BASE_REQUIRES),
+    AndroidNightlyJob(["arm", "v8a"], "pytorch_linux_build", requires=BASE_REQUIRES),
+    AndroidNightlyJob(["android_gradle"], "pytorch_android_gradle_build",
+                      with_docker=False,
+                      requires=[
+                          "nightly_pytorch_linux_xenial_py3_clang5_android_ndk_r19c_x86_32_build",
+                          "nightly_pytorch_linux_xenial_py3_clang5_android_ndk_r19c_x86_64_build",
+                          "nightly_pytorch_linux_xenial_py3_clang5_android_ndk_r19c_arm_v7a_build",
+                          "nightly_pytorch_linux_xenial_py3_clang5_android_ndk_r19c_arm_v8a_build"]),
+    AndroidNightlyJob(["x86_32_android_publish_snapshot"], "pytorch_android_publish_snapshot",
+                      extra_props={"context": "org-member"},
+                      with_docker=False,
+                      requires=["nightly_pytorch_linux_xenial_py3_clang5_android_ndk_r19c_android_gradle_build"],
+                      no_build_suffix=True),
+]
+
+
+def get_workflow_jobs():
+    return [item.gen_tree() for item in WORKFLOW_DATA]

.circleci/cimodel/data/simple/nightly_ios.py

@@ -5,26 +5,21 @@ import cimodel.lib.miniutils as miniutils
 class IOSNightlyJob:
     def __init__(self,
                  variant,
-                 is_full_jit=False,
                  is_upload=False):
 
         self.variant = variant
-        self.is_full_jit = is_full_jit
         self.is_upload = is_upload
 
     def get_phase_name(self):
         return "upload" if self.is_upload else "build"
 
-    def get_common_name_pieces(self, sep):
+    def get_common_name_pieces(self, with_version_dots):
 
         extra_name_suffix = [self.get_phase_name()] if self.is_upload else []
 
-        extra_name = ["full_jit"] if self.is_full_jit else []
-
         common_name_pieces = [
             "ios",
-        ] + extra_name + [
-        ] + ios_definitions.XCODE_VERSION.render_dots_or_parts(sep) + [
+        ] + ios_definitions.XCODE_VERSION.render_dots_or_parts(with_version_dots) + [
             "nightly",
             self.variant,
             "build",
@@ -33,14 +28,13 @@ class IOSNightlyJob:
         return common_name_pieces
 
     def gen_job_name(self):
-        return "_".join(["pytorch"] + self.get_common_name_pieces(None))
+        return "_".join(["pytorch"] + self.get_common_name_pieces(False))
 
     def gen_tree(self):
-        build_configs = BUILD_CONFIGS_FULL_JIT if self.is_full_jit else BUILD_CONFIGS
-        extra_requires = [x.gen_job_name() for x in build_configs] if self.is_upload else []
+        extra_requires = [x.gen_job_name() for x in BUILD_CONFIGS] if self.is_upload else []
 
         props_dict = {
-            "build_environment": "-".join(["libtorch"] + self.get_common_name_pieces(".")),
+            "build_environment": "-".join(["libtorch"] + self.get_common_name_pieces(True)),
             "requires": extra_requires,
             "context": "org-member",
             "filters": {"branches": {"only": "nightly"}},
@@ -53,9 +47,6 @@ class IOSNightlyJob:
             props_dict["use_metal"] = miniutils.quote(str(int(True)))
             props_dict["use_coreml"] = miniutils.quote(str(int(True)))
 
-        if self.is_full_jit:
-            props_dict["lite_interpreter"] = miniutils.quote(str(int(False)))
-
         template_name = "_".join([
             "binary",
             "ios",
@@ -70,14 +61,9 @@ BUILD_CONFIGS = [
     IOSNightlyJob("arm64"),
 ]
 
-BUILD_CONFIGS_FULL_JIT = [
-    IOSNightlyJob("x86_64", is_full_jit=True),
-    IOSNightlyJob("arm64", is_full_jit=True),
-]
 
-WORKFLOW_DATA = BUILD_CONFIGS + BUILD_CONFIGS_FULL_JIT + [
-    IOSNightlyJob("binary", is_full_jit=False, is_upload=True),
-    IOSNightlyJob("binary", is_full_jit=True, is_upload=True),
+WORKFLOW_DATA = BUILD_CONFIGS + [
+    IOSNightlyJob("binary", is_upload=True),
 ]
 
 

.circleci/cimodel/data/simple/util/branch_filters.py

@@ -1,5 +1,4 @@
 NON_PR_BRANCH_LIST = [
-    "main",
     "master",
     r"/ci-all\/.*/",
     r"/release\/.*/",
@@ -12,9 +11,6 @@ PR_BRANCH_LIST = [
 
 RC_PATTERN = r"/v[0-9]+(\.[0-9]+)*-rc[0-9]+/"
 
-MAC_IOS_EXCLUSION_LIST = ["nightly", "postnightly"]
-
-
 def gen_filter_dict(
         branches_list=NON_PR_BRANCH_LIST,
         tags_list=None
@@ -29,11 +25,3 @@ def gen_filter_dict(
     if tags_list is not None:
         filter_dict["tags"] = {"only": tags_list}
     return filter_dict
-
-
-def gen_filter_dict_exclude(branches_list=MAC_IOS_EXCLUSION_LIST):
-    return {
-        "branches": {
-            "ignore": branches_list,
-        },
-    }

.circleci/cimodel/data/simple/util/docker_constants.py

@@ -11,7 +11,7 @@ def gen_docker_image_requires(image_name):
 
 
 DOCKER_IMAGE_BASIC, DOCKER_REQUIREMENT_BASE = gen_docker_image(
-    "pytorch-linux-xenial-py3.7-gcc5.4"
+    "pytorch-linux-xenial-py3.6-gcc5.4"
 )
 
 DOCKER_IMAGE_CUDA_10_2, DOCKER_REQUIREMENT_CUDA_10_2 = gen_docker_image(
@@ -19,7 +19,7 @@ DOCKER_IMAGE_CUDA_10_2, DOCKER_REQUIREMENT_CUDA_10_2 = gen_docker_image(
 )
 
 DOCKER_IMAGE_GCC7, DOCKER_REQUIREMENT_GCC7 = gen_docker_image(
-    "pytorch-linux-xenial-py3.7-gcc7"
+    "pytorch-linux-xenial-py3.6-gcc7"
 )
 
 

.circleci/cimodel/data/simple/util/versions.py

@@ -1,6 +1,3 @@
-from typing import Optional
-
-
 class MultiPartVersion:
     def __init__(self, parts, prefix=""):
         self.parts = parts
@@ -16,11 +13,14 @@ class MultiPartVersion:
         else:
             return [self.prefix]
 
-    def render_dots_or_parts(self, sep: Optional[str] = None):
-        if sep is None:
-            return self.prefixed_parts()
+    def render_dots(self):
+        return ".".join(self.prefixed_parts())
+
+    def render_dots_or_parts(self, with_dots):
+        if with_dots:
+            return [self.render_dots()]
         else:
-            return [sep.join(self.prefixed_parts())]
+            return self.prefixed_parts()
 
 
 class CudaVersion(MultiPartVersion):

.circleci/cimodel/data/windows_build_definitions.py

@@ -0,0 +1,160 @@
+import cimodel.lib.miniutils as miniutils
+from cimodel.data.simple.util.branch_filters import gen_filter_dict, RC_PATTERN, NON_PR_BRANCH_LIST
+from cimodel.data.simple.util.versions import CudaVersion
+
+
+class WindowsJob:
+    def __init__(
+        self,
+        test_index,
+        vscode_spec,
+        cuda_version,
+        force_on_cpu=False,
+        multi_gpu=False,
+        master_only=False,
+        nightly_only=False,
+        master_and_nightly=False
+    ):
+        self.test_index = test_index
+        self.vscode_spec = vscode_spec
+        self.cuda_version = cuda_version
+        self.force_on_cpu = force_on_cpu
+        self.multi_gpu = multi_gpu
+        self.master_only = master_only
+        self.nightly_only = nightly_only
+        self.master_and_nightly = master_and_nightly
+
+    def gen_tree(self):
+
+        base_phase = "build" if self.test_index is None else "test"
+        numbered_phase = (
+            base_phase if self.test_index is None else base_phase + str(self.test_index)
+        )
+
+        key_parts = ["pytorch", "windows", base_phase]
+        if self.multi_gpu:
+            key_parts.append('multigpu')
+        key_name = "_".join(key_parts)
+
+        cpu_forcing_name_parts = ["on", "cpu"] if self.force_on_cpu else []
+
+        target_arch = self.cuda_version.render_dots() if self.cuda_version else "cpu"
+
+        python_version = "3.8"
+
+        base_name_parts = [
+            "pytorch",
+            "windows",
+            self.vscode_spec.render(),
+            "py" + python_version.replace(".", ""),
+            target_arch,
+        ]
+
+        prerequisite_jobs = []
+        if base_phase == "test":
+            prerequisite_jobs.append("_".join(base_name_parts + ["build"]))
+
+        if self.cuda_version:
+            self.cudnn_version = 8 if self.cuda_version.major == 11 else 7
+
+        arch_env_elements = (
+            ["cuda" + str(self.cuda_version.major) + "." + str(self.cuda_version.minor)]
+            if self.cuda_version
+            else ["cpu"]
+        )
+
+        build_environment_string = "-".join(
+            ["pytorch", "win"]
+            + self.vscode_spec.get_elements()
+            + arch_env_elements
+            + ["py" + python_version.split(".")[0]]
+        )
+
+        is_running_on_cuda = bool(self.cuda_version) and not self.force_on_cpu
+
+        if self.multi_gpu:
+            props_dict = {"requires": prerequisite_jobs}
+        else:
+            props_dict = {
+                "build_environment": build_environment_string,
+                "python_version": miniutils.quote(python_version),
+                "vs_version": miniutils.quote("16.8.6"),
+                "vc_version": miniutils.quote(self.vscode_spec.dotted_version()),
+                "vc_year": miniutils.quote(str(self.vscode_spec.year)),
+                "vc_product": self.vscode_spec.get_product(),
+                "use_cuda": miniutils.quote(str(int(is_running_on_cuda))),
+                "requires": prerequisite_jobs,
+            }
+
+        if self.master_only:
+            props_dict[
+                "filters"
+            ] = gen_filter_dict()
+        elif self.nightly_only:
+            props_dict[
+                "filters"
+            ] = gen_filter_dict(branches_list=["nightly"], tags_list=RC_PATTERN)
+        elif self.master_and_nightly:
+            props_dict[
+                "filters"
+            ] = gen_filter_dict(branches_list=NON_PR_BRANCH_LIST + ["nightly"], tags_list=RC_PATTERN)
+
+        name_parts = base_name_parts + cpu_forcing_name_parts + [numbered_phase]
+
+        if not self.multi_gpu:
+            if base_phase == "test":
+                test_name = "-".join(["pytorch", "windows", numbered_phase])
+                props_dict["test_name"] = test_name
+
+                if is_running_on_cuda:
+                    props_dict["executor"] = "windows-with-nvidia-gpu"
+
+            props_dict["cuda_version"] = (
+                miniutils.quote(str(self.cuda_version))
+                if self.cuda_version
+                else "cpu"
+            )
+
+        props_dict["name"] = "_".join(name_parts)
+
+        return [{key_name: props_dict}]
+
+
+class VcSpec:
+    def __init__(self, year, version_elements=None, hide_version=False):
+        self.year = year
+        self.version_elements = version_elements or []
+        self.hide_version = hide_version
+
+    def get_elements(self):
+        if self.hide_version:
+            return [self.prefixed_year()]
+        return [self.prefixed_year()] + self.version_elements
+
+    def get_product(self):
+        return "BuildTools"
+
+    def dotted_version(self):
+        return ".".join(self.version_elements)
+
+    def prefixed_year(self):
+        return "vs" + str(self.year)
+
+    def render(self):
+        return "_".join(self.get_elements())
+
+_VC2019 = VcSpec(2019)
+
+WORKFLOW_DATA = [
+    # VS2019 CUDA-10.2
+    WindowsJob(None, _VC2019, CudaVersion(10, 2), master_only=True),
+    # VS2019 CUDA-10.2 force on cpu
+    WindowsJob(1, _VC2019, CudaVersion(10, 2), force_on_cpu=True, master_only=True),
+
+    # TODO: This test is disabled due to https://github.com/pytorch/pytorch/issues/59724
+    # WindowsJob('_azure_multi_gpu', _VC2019, CudaVersion(11, 1), multi_gpu=True, master_and_nightly=True),
+]
+
+
+def get_windows_workflows():
+    return [item.gen_tree() for item in WORKFLOW_DATA]

.circleci/docker/android/build.gradle

@@ -51,9 +51,9 @@ android {
 dependencies {
     implementation 'com.android.support:appcompat-v7:28.0.0'
     implementation 'androidx.appcompat:appcompat:1.0.0'
-    implementation 'com.facebook.fbjni:fbjni-java-only:0.2.2'
+    implementation 'com.facebook.fbjni:fbjni-java-only:0.0.3'
     implementation 'com.google.code.findbugs:jsr305:3.0.1'
-    implementation 'com.facebook.soloader:nativeloader:0.10.4'
+    implementation 'com.facebook.soloader:nativeloader:0.8.0'
 
     implementation 'junit:junit:' + rootProject.junitVersion
     implementation 'androidx.test:core:' + rootProject.coreVersion

.circleci/docker/build.sh

@@ -33,25 +33,21 @@ function extract_all_from_image_name() {
     if [ "x${name}" = xpy ]; then
       vername=ANACONDA_PYTHON_VERSION
     fi
-    # skip non-conforming fields such as "pytorch", "linux" or "bionic" without version string
+    # skip non-conforming fields such as "pytorch", "linux" or "xenial" without version string
     if [ -n "${name}" ]; then
       extract_version_from_image_name "${name}" "${vername}"
     fi
   done
 }
 
-# Use the same pre-built XLA test image from PyTorch/XLA
-if [[ "$image" == *xla* ]]; then
-  echo "Using pre-built XLA test image..."
-  exit 0
-fi
-
-if [[ "$image" == *-bionic* ]]; then
+if [[ "$image" == *-xenial* ]]; then
+  UBUNTU_VERSION=16.04
+elif [[ "$image" == *-artful* ]]; then
+  UBUNTU_VERSION=17.10
+elif [[ "$image" == *-bionic* ]]; then
   UBUNTU_VERSION=18.04
 elif [[ "$image" == *-focal* ]]; then
   UBUNTU_VERSION=20.04
-elif [[ "$image" == *-jammy* ]]; then
-  UBUNTU_VERSION=22.04
 elif [[ "$image" == *ubuntu* ]]; then
   extract_version_from_image_name ubuntu UBUNTU_VERSION
 elif [[ "$image" == *centos* ]]; then
@@ -68,81 +64,108 @@ else
 fi
 
 DOCKERFILE="${OS}/Dockerfile"
-# When using ubuntu - 22.04, start from Ubuntu docker image, instead of nvidia/cuda docker image.
-if [[ "$image" == *cuda* && "$UBUNTU_VERSION" != "22.04" ]]; then
+if [[ "$image" == *cuda* ]]; then
   DOCKERFILE="${OS}-cuda/Dockerfile"
 elif [[ "$image" == *rocm* ]]; then
   DOCKERFILE="${OS}-rocm/Dockerfile"
 fi
 
-# CMake 3.18 is needed to support CUDA17 language variant
-CMAKE_VERSION=3.18.5
-
 TRAVIS_DL_URL_PREFIX="https://s3.amazonaws.com/travis-python-archives/binaries/ubuntu/14.04/x86_64"
-_UCX_COMMIT=31e74cac7bee0ef66bef2af72e7d86d9c282e5ab
-_UCC_COMMIT=1c7a7127186e7836f73aafbd7697bbc274a77eee
 
 # It's annoying to rename jobs every time you want to rewrite a
 # configuration, so we hardcode everything here rather than do it
 # from scratch
 case "$image" in
-  pytorch-linux-bionic-cuda11.3-cudnn8-py3-clang9)
+  pytorch-linux-xenial-py3.8)
+    ANACONDA_PYTHON_VERSION=3.8
+    CMAKE_VERSION=3.10.3
+    GCC_VERSION=7
+    # Do not install PROTOBUF, DB, and VISION as a test
+    ;;
+  pytorch-linux-xenial-py3.6-gcc5.4)
+    ANACONDA_PYTHON_VERSION=3.6
+    CMAKE_VERSION=3.10.3
+    GCC_VERSION=5
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    KATEX=yes
+    ;;
+  pytorch-linux-xenial-py3.6-gcc7.2)
+    ANACONDA_PYTHON_VERSION=3.6
+    CMAKE_VERSION=3.10.3
+    GCC_VERSION=7
+    # Do not install PROTOBUF, DB, and VISION as a test
+    ;;
+  pytorch-linux-xenial-py3.6-gcc7)
+    ANACONDA_PYTHON_VERSION=3.6
+    CMAKE_VERSION=3.10.3
+    GCC_VERSION=7
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    ;;
+  pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7)
+    CUDA_VERSION=10.2
+    CUDNN_VERSION=7
+    ANACONDA_PYTHON_VERSION=3.6
+    CMAKE_VERSION=3.10.3
+    GCC_VERSION=7
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    KATEX=yes
+    ;;
+  pytorch-linux-xenial-cuda11.1-cudnn8-py3-gcc7)
+    CUDA_VERSION=11.1
+    CUDNN_VERSION=8
+    ANACONDA_PYTHON_VERSION=3.6
+    CMAKE_VERSION=3.10.3
+    GCC_VERSION=7
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    KATEX=yes
+    ;;
+  pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7)
     CUDA_VERSION=11.3.0 # Deviating from major.minor to conform to nvidia's Docker image names
     CUDNN_VERSION=8
-    TENSORRT_VERSION=8.0.1.6
-    ANACONDA_PYTHON_VERSION=3.7
-    CLANG_VERSION=9
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    KATEX=yes
-    CONDA_CMAKE=yes
-    ;;
-  pytorch-linux-bionic-cuda11.6-cudnn8-py3-gcc7)
-    CUDA_VERSION=11.6.2
-    CUDNN_VERSION=8
-    ANACONDA_PYTHON_VERSION=3.10
+    ANACONDA_PYTHON_VERSION=3.6
+    CMAKE_VERSION=3.10.3
     GCC_VERSION=7
     PROTOBUF=yes
     DB=yes
     VISION=yes
     KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
     ;;
-  pytorch-linux-bionic-cuda11.7-cudnn8-py3-gcc7)
-    CUDA_VERSION=11.7.0
-    CUDNN_VERSION=8
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=7
+  pytorch-linux-xenial-py3-clang5-asan)
+    ANACONDA_PYTHON_VERSION=3.6
+    CLANG_VERSION=5.0
+    CMAKE_VERSION=3.10.3
     PROTOBUF=yes
     DB=yes
     VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
     ;;
-  pytorch-linux-focal-py3-clang7-asan)
-    ANACONDA_PYTHON_VERSION=3.7
+  pytorch-linux-xenial-py3-clang7-asan)
+    ANACONDA_PYTHON_VERSION=3.6
     CLANG_VERSION=7
+    CMAKE_VERSION=3.10.3
     PROTOBUF=yes
     DB=yes
     VISION=yes
-    CONDA_CMAKE=yes
     ;;
-  pytorch-linux-focal-py3-clang10-onnx)
-    ANACONDA_PYTHON_VERSION=3.7
-    CLANG_VERSION=10
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    CONDA_CMAKE=yes
-    ;;
-  pytorch-linux-focal-py3-clang7-android-ndk-r19c)
-    ANACONDA_PYTHON_VERSION=3.7
+  pytorch-linux-xenial-py3-clang7-onnx)
+    ANACONDA_PYTHON_VERSION=3.6
     CLANG_VERSION=7
+    CMAKE_VERSION=3.10.3
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    ;;
+  pytorch-linux-xenial-py3-clang5-android-ndk-r19c)
+    ANACONDA_PYTHON_VERSION=3.6
+    CLANG_VERSION=5.0
+    CMAKE_VERSION=3.10.3
     LLVMDEV=yes
     PROTOBUF=yes
     ANDROID=yes
@@ -150,15 +173,22 @@ case "$image" in
     GRADLE_VERSION=6.8.3
     NINJA_VERSION=1.9.0
     ;;
-  pytorch-linux-bionic-py3.7-clang9)
-    ANACONDA_PYTHON_VERSION=3.7
+  pytorch-linux-xenial-py3.6-clang7)
+    ANACONDA_PYTHON_VERSION=3.6
+    CMAKE_VERSION=3.10.3
+    CLANG_VERSION=7
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    ;;
+  pytorch-linux-bionic-py3.6-clang9)
+    ANACONDA_PYTHON_VERSION=3.6
     CLANG_VERSION=9
     PROTOBUF=yes
     DB=yes
     VISION=yes
     VULKAN_SDK_VERSION=1.2.162.1
     SWIFTSHADER=yes
-    CONDA_CMAKE=yes
     ;;
   pytorch-linux-bionic-py3.8-gcc9)
     ANACONDA_PYTHON_VERSION=3.8
@@ -166,17 +196,15 @@ case "$image" in
     PROTOBUF=yes
     DB=yes
     VISION=yes
-    CONDA_CMAKE=yes
     ;;
-  pytorch-linux-bionic-cuda10.2-cudnn7-py3.7-clang9)
+  pytorch-linux-bionic-cuda10.2-cudnn7-py3.6-clang9)
     CUDA_VERSION=10.2
     CUDNN_VERSION=7
-    ANACONDA_PYTHON_VERSION=3.7
+    ANACONDA_PYTHON_VERSION=3.6
     CLANG_VERSION=9
     PROTOBUF=yes
     DB=yes
     VISION=yes
-    CONDA_CMAKE=yes
     ;;
   pytorch-linux-bionic-cuda10.2-cudnn7-py3.9-gcc7)
     CUDA_VERSION=10.2
@@ -186,52 +214,40 @@ case "$image" in
     PROTOBUF=yes
     DB=yes
     VISION=yes
-    CONDA_CMAKE=yes
     ;;
-  pytorch-linux-focal-rocm5.1-py3.8)
-    ANACONDA_PYTHON_VERSION=3.8
+  pytorch-linux-bionic-cuda11.0-cudnn8-py3.6-gcc9)
+    CUDA_VERSION=11.0
+    CUDNN_VERSION=8
+    ANACONDA_PYTHON_VERSION=3.6
     GCC_VERSION=9
     PROTOBUF=yes
     DB=yes
     VISION=yes
-    ROCM_VERSION=5.1.1
-    CONDA_CMAKE=yes
+    ROCM_VERSION=3.9
     ;;
-  pytorch-linux-focal-rocm5.2-py3.8)
-    ANACONDA_PYTHON_VERSION=3.8
+  pytorch-linux-bionic-rocm4.1-py3.6)
+    ANACONDA_PYTHON_VERSION=3.6
     GCC_VERSION=9
     PROTOBUF=yes
     DB=yes
     VISION=yes
-    ROCM_VERSION=5.2
-    CONDA_CMAKE=yes
+    ROCM_VERSION=4.1
     ;;
-  pytorch-linux-focal-py3.7-gcc7)
-    ANACONDA_PYTHON_VERSION=3.7
-    GCC_VERSION=7
+  pytorch-linux-bionic-rocm4.2-py3.6)
+    ANACONDA_PYTHON_VERSION=3.6
+    GCC_VERSION=9
     PROTOBUF=yes
     DB=yes
     VISION=yes
-    KATEX=yes
-    CONDA_CMAKE=yes
+    ROCM_VERSION=4.2
     ;;
-  pytorch-linux-jammy-cuda11.6-cudnn8-py3.8-clang12)
-    ANACONDA_PYTHON_VERSION=3.8
-    CUDA_VERSION=11.6
-    CUDNN_VERSION=8
-    CLANG_VERSION=12
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    ;;
-  pytorch-linux-jammy-cuda11.7-cudnn8-py3.8-clang12)
-    ANACONDA_PYTHON_VERSION=3.8
-    CUDA_VERSION=11.7
-    CUDNN_VERSION=8
-    CLANG_VERSION=12
+  pytorch-linux-bionic-rocm4.3.1-py3.6)
+    ANACONDA_PYTHON_VERSION=3.6
+    GCC_VERSION=9
     PROTOBUF=yes
     DB=yes
     VISION=yes
+    ROCM_VERSION=4.3.1
     ;;
   *)
     # Catch-all for builds that are not hardcoded.
@@ -239,6 +255,9 @@ case "$image" in
     DB=yes
     VISION=yes
     echo "image '$image' did not match an existing build configuration"
+    if [[ "$image" == *xenial* ]]; then
+      CMAKE_VERSION=3.10.3
+    fi
     if [[ "$image" == *py* ]]; then
       extract_version_from_image_name py ANACONDA_PYTHON_VERSION
     fi
@@ -248,10 +267,6 @@ case "$image" in
     fi
     if [[ "$image" == *rocm* ]]; then
       extract_version_from_image_name rocm ROCM_VERSION
-      NINJA_VERSION=1.9.0
-    fi
-    if [[ "$image" == *centos7* ]]; then
-      NINJA_VERSION=1.10.2
     fi
     if [[ "$image" == *gcc* ]]; then
       extract_version_from_image_name gcc GCC_VERSION
@@ -279,14 +294,6 @@ fi
 
 tmp_tag=$(basename "$(mktemp -u)" | tr '[:upper:]' '[:lower:]')
 
-#when using cudnn version 8 install it separately from cuda
-if [[ "$image" == *cuda*  && ${OS} == "ubuntu" ]]; then
-  IMAGE_NAME="nvidia/cuda:${CUDA_VERSION}-cudnn${CUDNN_VERSION}-devel-ubuntu${UBUNTU_VERSION}"
-  if [[ ${CUDNN_VERSION} == 8 ]]; then
-    IMAGE_NAME="nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}"
-  fi
-fi
-
 # Build image
 # TODO: build-arg THRIFT is not turned on for any image, remove it once we confirm
 # it's no longer needed.
@@ -313,7 +320,6 @@ docker build \
        --build-arg "GCC_VERSION=${GCC_VERSION}" \
        --build-arg "CUDA_VERSION=${CUDA_VERSION}" \
        --build-arg "CUDNN_VERSION=${CUDNN_VERSION}" \
-       --build-arg "TENSORRT_VERSION=${TENSORRT_VERSION}" \
        --build-arg "ANDROID=${ANDROID}" \
        --build-arg "ANDROID_NDK=${ANDROID_NDK_VERSION}" \
        --build-arg "GRADLE_VERSION=${GRADLE_VERSION}" \
@@ -323,11 +329,6 @@ docker build \
        --build-arg "NINJA_VERSION=${NINJA_VERSION:-}" \
        --build-arg "KATEX=${KATEX:-}" \
        --build-arg "ROCM_VERSION=${ROCM_VERSION:-}" \
-       --build-arg "PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH:-gfx906}" \
-       --build-arg "IMAGE_NAME=${IMAGE_NAME}" \
-       --build-arg "UCX_COMMIT=${UCX_COMMIT}" \
-       --build-arg "UCC_COMMIT=${UCC_COMMIT}" \
-       --build-arg "CONDA_CMAKE=${CONDA_CMAKE}" \
        -f $(dirname ${DOCKERFILE})/Dockerfile \
        -t "$tmp_tag" \
        "$@" \
@@ -346,7 +347,6 @@ function drun() {
 }
 
 if [[ "$OS" == "ubuntu" ]]; then
-
   if !(drun lsb_release -a 2>&1 | grep -qF Ubuntu); then
     echo "OS=ubuntu, but:"
     drun lsb_release -a

.circleci/docker/build_docker.sh

@@ -18,7 +18,6 @@ tag="${DOCKER_TAG}"
 
 registry="308535385114.dkr.ecr.us-east-1.amazonaws.com"
 image="${registry}/pytorch/${IMAGE_NAME}"
-ghcr_image="ghcr.io/pytorch/ci-image"
 
 login() {
   aws ecr get-authorization-token --region us-east-1 --output text --query 'authorizationData[].authorizationToken' |
@@ -27,14 +26,11 @@ login() {
     docker login -u AWS --password-stdin "$1"
 }
 
+# Retry on timeouts (can happen on job stampede).
+retry login "${registry}"
 
-# Only run these steps if not on github actions
-if [[ -z "${GITHUB_ACTIONS}" ]]; then
-  # Retry on timeouts (can happen on job stampede).
-  retry login "${registry}"
-  # Logout on exit
-  trap "docker logout ${registry}" EXIT
-fi
+# Logout on exit
+trap "docker logout ${registry}" EXIT
 
 # export EC2=1
 # export JENKINS=1
@@ -47,25 +43,10 @@ fi
 # Build new image
 ./build.sh ${IMAGE_NAME} -t "${image}:${tag}"
 
-# Only push if `DOCKER_SKIP_PUSH` = false
-if [ "${DOCKER_SKIP_PUSH:-true}" = "false" ]; then
-  # Only push if docker image doesn't exist already.
-  # ECR image tags are immutable so this will avoid pushing if only just testing if the docker jobs work
-  # NOTE: The only workflow that should push these images should be the docker-builds.yml workflow
-  if ! docker manifest inspect "${image}:${tag}" >/dev/null 2>/dev/null; then
-    docker push "${image}:${tag}"
-  fi
+docker push "${image}:${tag}"
 
-  if [ "${PUSH_GHCR_IMAGE:-}" = "true" ]; then
-    # Push docker image to the ghcr.io
-    echo $GHCR_PAT | docker login ghcr.io -u pytorch --password-stdin
-    docker tag "${image}:${tag}" "${ghcr_image}:${IMAGE_NAME}-${tag}"
-    docker push "${ghcr_image}:${IMAGE_NAME}-${tag}"
-  fi
-fi
+docker save -o "${IMAGE_NAME}:${tag}.tar" "${image}:${tag}"
 
 if [ -z "${DOCKER_SKIP_S3_UPLOAD:-}" ]; then
-  trap "rm -rf ${IMAGE_NAME}:${tag}.tar" EXIT
-  docker save -o "${IMAGE_NAME}:${tag}.tar" "${image}:${tag}"
   aws s3 cp "${IMAGE_NAME}:${tag}.tar" "s3://ossci-linux-build/pytorch/base/${IMAGE_NAME}:${tag}.tar" --acl public-read
 fi

.circleci/docker/centos-rocm/Dockerfile

@@ -4,77 +4,61 @@ FROM centos:${CENTOS_VERSION}
 
 ARG CENTOS_VERSION
 
-# Set AMD gpu targets to build for
-ARG PYTORCH_ROCM_ARCH
-ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
-
 # Install required packages to build Caffe2
 
 # Install common dependencies (so that this step can be cached separately)
 ARG EC2
-COPY ./common/install_base.sh install_base.sh
+ADD ./common/install_base.sh install_base.sh
 RUN bash ./install_base.sh && rm install_base.sh
 
-# Update CentOS git version
-RUN yum -y remove git
-RUN yum -y remove git-*
-RUN yum -y install https://packages.endpoint.com/rhel/7/os/x86_64/endpoint-repo-1.9-1.x86_64.rpm
-RUN yum install -y git
-
 # Install devtoolset
 ARG DEVTOOLSET_VERSION
-COPY ./common/install_devtoolset.sh install_devtoolset.sh
+ADD ./common/install_devtoolset.sh install_devtoolset.sh
 RUN bash ./install_devtoolset.sh && rm install_devtoolset.sh
 ENV BASH_ENV "/etc/profile"
 
 # (optional) Install non-default glibc version
 ARG GLIBC_VERSION
-COPY ./common/install_glibc.sh install_glibc.sh
+ADD ./common/install_glibc.sh install_glibc.sh
 RUN if [ -n "${GLIBC_VERSION}" ]; then bash ./install_glibc.sh; fi
 RUN rm install_glibc.sh
 
 # Install user
-COPY ./common/install_user.sh install_user.sh
+ADD ./common/install_user.sh install_user.sh
 RUN bash ./install_user.sh && rm install_user.sh
 
-# Install conda and other packages (e.g., numpy, pytest)
+# Install conda and other packages (e.g., numpy, coverage, pytest)
 ENV PATH /opt/conda/bin:$PATH
 ARG ANACONDA_PYTHON_VERSION
-ARG CONDA_CMAKE
-COPY requirements-ci.txt /opt/conda/requirements-ci.txt
-COPY ./common/install_conda.sh install_conda.sh
+ADD ./common/install_conda.sh install_conda.sh
 RUN bash ./install_conda.sh && rm install_conda.sh
-RUN rm /opt/conda/requirements-ci.txt
 
 # (optional) Install protobuf for ONNX
 ARG PROTOBUF
-COPY ./common/install_protobuf.sh install_protobuf.sh
+ADD ./common/install_protobuf.sh install_protobuf.sh
 RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
 RUN rm install_protobuf.sh
 ENV INSTALLED_PROTOBUF ${PROTOBUF}
 
 # (optional) Install database packages like LMDB and LevelDB
 ARG DB
-COPY ./common/install_db.sh install_db.sh
+ADD ./common/install_db.sh install_db.sh
 RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
 RUN rm install_db.sh
 ENV INSTALLED_DB ${DB}
 
 # (optional) Install vision packages like OpenCV and ffmpeg
 ARG VISION
-COPY ./common/install_vision.sh install_vision.sh
+ADD ./common/install_vision.sh install_vision.sh
 RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
 RUN rm install_vision.sh
 ENV INSTALLED_VISION ${VISION}
 
 # Install rocm
 ARG ROCM_VERSION
-COPY ./common/install_rocm.sh install_rocm.sh
+ADD ./common/install_rocm.sh install_rocm.sh
 RUN bash ./install_rocm.sh
 RUN rm install_rocm.sh
-COPY ./common/install_rocm_magma.sh install_rocm_magma.sh
-RUN bash ./install_rocm_magma.sh
-RUN rm install_rocm_magma.sh
 ENV PATH /opt/rocm/bin:$PATH
 ENV PATH /opt/rocm/hcc/bin:$PATH
 ENV PATH /opt/rocm/hip/bin:$PATH
@@ -86,18 +70,18 @@ ENV LC_ALL en_US.utf8
 
 # (optional) Install non-default CMake version
 ARG CMAKE_VERSION
-COPY ./common/install_cmake.sh install_cmake.sh
+ADD ./common/install_cmake.sh install_cmake.sh
 RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
 RUN rm install_cmake.sh
 
 # (optional) Install non-default Ninja version
 ARG NINJA_VERSION
-COPY ./common/install_ninja.sh install_ninja.sh
+ADD ./common/install_ninja.sh install_ninja.sh
 RUN if [ -n "${NINJA_VERSION}" ]; then bash ./install_ninja.sh; fi
 RUN rm install_ninja.sh
 
 # Install ccache/sccache (do this last, so we get priority in PATH)
-COPY ./common/install_cache.sh install_cache.sh
+ADD ./common/install_cache.sh install_cache.sh
 ENV PATH /opt/cache/bin:$PATH
 RUN bash ./install_cache.sh && rm install_cache.sh
 

.circleci/docker/common/install_base.sh

@@ -11,41 +11,18 @@ install_ubuntu() {
   #   "$UBUNTU_VERSION" == "18.04"
   if [[ "$UBUNTU_VERSION" == "18.04"* ]]; then
     cmake3="cmake=3.10*"
-    maybe_libiomp_dev="libiomp-dev"
-  elif [[ "$UBUNTU_VERSION" == "20.04"* ]]; then
-    cmake3="cmake=3.16*"
-    maybe_libiomp_dev=""
-  elif [[ "$UBUNTU_VERSION" == "22.04"* ]]; then
-    cmake3="cmake=3.22*"
-    maybe_libiomp_dev=""
   else
     cmake3="cmake=3.5*"
-    maybe_libiomp_dev="libiomp-dev"
   fi
 
-  if [[ "$CLANG_VERSION" == 12 ]]; then
-    maybe_libomp_dev="libomp-12-dev"
-  elif [[ "$CLANG_VERSION" == 10 ]]; then
-    maybe_libomp_dev="libomp-10-dev"
-  else
-    maybe_libomp_dev=""
-  fi
-
-  # TODO: Remove this once nvidia package repos are back online
-  # Comment out nvidia repositories to prevent them from getting apt-get updated, see https://github.com/pytorch/pytorch/issues/74968
-  # shellcheck disable=SC2046
-  sed -i 's/.*nvidia.*/# &/' $(find /etc/apt/ -type f -name "*.list")
-
   # Install common dependencies
   apt-get update
   # TODO: Some of these may not be necessary
   ccache_deps="asciidoc docbook-xml docbook-xsl xsltproc"
-  deploy_deps="libffi-dev libbz2-dev libreadline-dev libncurses5-dev libncursesw5-dev libgdbm-dev libsqlite3-dev uuid-dev tk-dev"
   numpy_deps="gfortran"
   apt-get install -y --no-install-recommends \
     $ccache_deps \
     $numpy_deps \
-    ${deploy_deps} \
     ${cmake3} \
     apt-transport-https \
     autoconf \
@@ -56,40 +33,16 @@ install_ubuntu() {
     git \
     libatlas-base-dev \
     libc6-dbg \
-    ${maybe_libiomp_dev} \
+    libiomp-dev \
     libyaml-dev \
     libz-dev \
     libjpeg-dev \
     libasound2-dev \
     libsndfile-dev \
-    ${maybe_libomp_dev} \
     software-properties-common \
-    wget \
     sudo \
-    vim \
-    jq \
-    libtool \
-    vim \
-    unzip \
-    gdb
-
-  # Should resolve issues related to various apt package repository cert issues
-  # see: https://github.com/pytorch/pytorch/issues/65931
-  apt-get install -y libgnutls30
-
-  # cuda-toolkit does not work with gcc-11.2.0 which is default in Ubunutu 22.04
-  # see: https://github.com/NVlabs/instant-ngp/issues/119
-  if [[ "$UBUNTU_VERSION" == "22.04"* ]]; then
-    apt-get install -y g++-10
-    update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-10 30
-    update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-10 30
-    update-alternatives --install /usr/bin/gcov gcov /usr/bin/gcov-10 30
-
-    # https://www.spinics.net/lists/libreoffice/msg07549.html
-    sudo rm -rf /usr/lib/gcc/x86_64-linux-gnu/11
-    wget https://github.com/gcc-mirror/gcc/commit/2b2d97fc545635a0f6aa9c9ee3b017394bc494bf.patch -O noexecpt.patch
-    sudo patch  /usr/include/c++/10/bits/range_access.h noexecpt.patch
-  fi
+    wget \
+    vim
 
   # Cleanup package manager
   apt-get autoclean && apt-get clean
@@ -129,9 +82,7 @@ install_centos() {
     opencv-devel \
     sudo \
     wget \
-    vim \
-    unzip \
-    gdb
+    vim
 
   # Cleanup
   yum clean all
@@ -158,11 +109,14 @@ esac
 # Install Valgrind separately since the apt-get version is too old.
 mkdir valgrind_build && cd valgrind_build
 VALGRIND_VERSION=3.16.1
-wget https://ossci-linux.s3.amazonaws.com/valgrind-${VALGRIND_VERSION}.tar.bz2
+if ! wget http://valgrind.org/downloads/valgrind-${VALGRIND_VERSION}.tar.bz2
+then
+  wget https://sourceware.org/ftp/valgrind/valgrind-${VALGRIND_VERSION}.tar.bz2
+fi
 tar -xjf valgrind-${VALGRIND_VERSION}.tar.bz2
 cd valgrind-${VALGRIND_VERSION}
 ./configure --prefix=/usr/local
-make -j6
+make -j 4
 sudo make install
 cd ../../
 rm -rf valgrind_build

.circleci/docker/common/install_cache.sh

@@ -5,9 +5,7 @@ set -ex
 install_ubuntu() {
   echo "Preparing to build sccache from source"
   apt-get update
-  # libssl-dev will not work as it is upgraded to libssl3 in Ubuntu-22.04.
-  # Instead use lib and headers from OpenSSL1.1 installed in `install_openssl.sh``
-  apt-get install -y cargo
+  apt-get install -y cargo pkg-config libssl-dev
   echo "Checking out sccache repo"
   git clone https://github.com/pytorch/sccache
   cd sccache
@@ -48,9 +46,7 @@ fi
 chmod a+x /opt/cache/bin/sccache
 
 function write_sccache_stub() {
-  # Unset LD_PRELOAD for ps because of asan + ps issues
-  # https://gcc.gnu.org/bugzilla/show_bug.cgi?id=90589
-  printf "#!/bin/sh\nif [ \$(env -u LD_PRELOAD ps -p \$PPID -o comm=) != sccache ]; then\n  exec sccache $(which $1) \"\$@\"\nelse\n  exec $(which $1) \"\$@\"\nfi" > "/opt/cache/bin/$1"
+  printf "#!/bin/sh\nif [ \$(ps -p \$PPID -o comm=) != sccache ]; then\n  exec sccache $(which $1) \"\$@\"\nelse\n  exec $(which $1) \"\$@\"\nfi" > "/opt/cache/bin/$1"
   chmod a+x "/opt/cache/bin/$1"
 }
 

.circleci/docker/common/install_clang.sh

@@ -13,9 +13,6 @@ if [ -n "$CLANG_VERSION" ]; then
     sudo apt-get install  -y --no-install-recommends gpg-agent
     wget --no-check-certificate -O - https://apt.llvm.org/llvm-snapshot.gpg.key | sudo apt-key add  -
     apt-add-repository "deb http://apt.llvm.org/bionic/ llvm-toolchain-bionic-${CLANG_VERSION} main"
-  elif [[ $UBUNTU_VERSION == 22.04 ]]; then
-    # work around ubuntu apt-get conflicts
-    sudo apt-get -y -f install
   fi
 
   sudo apt-get update

.circleci/docker/common/install_conda.sh

@@ -21,7 +21,7 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
       ;;
   esac
 
-  mkdir -p /opt/conda
+  mkdir /opt/conda
   chown jenkins:jenkins /opt/conda
 
   # Work around bug where devtoolset replaces sudo and breaks it.
@@ -55,10 +55,8 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
   # Ensure we run conda in a directory that jenkins has write access to
   pushd /opt/conda
 
-  # Prevent conda from updating to 4.14.0, which causes docker build failures
-  # See https://hud.pytorch.org/pytorch/pytorch/commit/754d7f05b6841e555cea5a4b2c505dd9e0baec1d
-  # Uncomment the below when resolved to track the latest conda update
-  # as_jenkins conda update -y -n base conda
+  # Track latest conda update
+  as_jenkins conda update -y -n base conda
 
   # Install correct Python version
   as_jenkins conda install -y python="$ANACONDA_PYTHON_VERSION"
@@ -70,49 +68,68 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
     as_jenkins conda install -q -y python="$ANACONDA_PYTHON_VERSION" $*
   }
 
-  pip_install() {
-    as_jenkins pip install --progress-bar off $*
-  }
-
   # Install PyTorch conda deps, as per https://github.com/pytorch/pytorch README
-  CONDA_COMMON_DEPS="astunparse pyyaml mkl=2022.0.1 mkl-include=2022.0.1 setuptools cffi future six"
-  if [ "$ANACONDA_PYTHON_VERSION" = "3.10" ]; then
+  # DO NOT install cmake here as it would install a version newer than 3.10, but
+  # we want to pin to version 3.10.
+  SCIPY_VERSION=1.1.0
+  if [ "$ANACONDA_PYTHON_VERSION" = "3.9" ]; then
     # Install llvm-8 as it is required to compile llvmlite-0.30.0 from source
-    conda_install numpy=1.21.2 ${CONDA_COMMON_DEPS} llvmdev=8.0.0
-  elif [ "$ANACONDA_PYTHON_VERSION" = "3.9" ]; then
-    # Install llvm-8 as it is required to compile llvmlite-0.30.0 from source
-    conda_install numpy=1.19.2 ${CONDA_COMMON_DEPS} llvmdev=8.0.0
+    conda_install numpy=1.19.2 astunparse pyyaml mkl mkl-include setuptools cffi future six llvmdev=8.0.0 -c conda-forge
+    SCIPY_VERSION=1.6.0
   elif [ "$ANACONDA_PYTHON_VERSION" = "3.8" ]; then
     # Install llvm-8 as it is required to compile llvmlite-0.30.0 from source
-    conda_install numpy=1.18.5 ${CONDA_COMMON_DEPS} llvmdev=8.0.0
+    conda_install numpy=1.18.5 astunparse pyyaml mkl mkl-include setuptools cffi future six llvmdev=8.0.0
+  elif [ "$ANACONDA_PYTHON_VERSION" = "3.7" ]; then
+    # DO NOT install dataclasses if installing python-3.7, since its part of python-3.7 core packages
+    conda_install numpy=1.18.5 astunparse pyyaml mkl mkl-include setuptools cffi future six typing_extensions
   else
-    # Install `typing_extensions` for 3.7
-    conda_install numpy=1.18.5 ${CONDA_COMMON_DEPS} typing_extensions
+    conda_install numpy=1.18.5 astunparse pyyaml mkl mkl-include setuptools cffi future six dataclasses typing_extensions
   fi
 
-  # Use conda cmake in some cases. Conda cmake will be newer than our supported
-  # min version (3.5 for xenial and 3.10 for bionic), so we only do it in those
-  # following builds that we know should use conda. Specifically, Ubuntu bionic
-  # and focal cannot find conda mkl with stock cmake, so we need a cmake from conda
-  if [ -n "${CONDA_CMAKE}" ]; then
-    conda_install cmake
+  if [[ "$CUDA_VERSION" == 10.2* ]]; then
+    conda_install magma-cuda102 -c pytorch
+  elif [[ "$CUDA_VERSION" == 11.0* ]]; then
+    conda_install magma-cuda110 -c pytorch
+  elif [[ "$CUDA_VERSION" == 11.1* ]]; then
+    conda_install magma-cuda111 -c pytorch
+  elif [[ "$CUDA_VERSION" == 11.3* ]]; then
+    conda_install magma-cuda113 -c pytorch
   fi
 
-  # Magma package names are concatenation of CUDA major and minor ignoring revision
-  # I.e. magma-cuda102 package corresponds to CUDA_VERSION=10.2 and CUDA_VERSION=10.2.89
-  if [ -n "$CUDA_VERSION" ]; then
-    conda_install magma-cuda$(TMP=${CUDA_VERSION/./};echo ${TMP%.*[0-9]}) -c pytorch
-  fi
+  # TODO: This isn't working atm
+  conda_install nnpack -c killeent
 
   # Install some other packages, including those needed for Python test reporting
-  pip_install -r /opt/conda/requirements-ci.txt
+  # TODO: Why is scipy pinned
+  # Pin MyPy version because new errors are likely to appear with each release
+  # Pin hypothesis to avoid flakiness: https://github.com/pytorch/pytorch/issues/31136
+  # Pin coverage so we can use COVERAGE_RCFILE
+  as_jenkins pip install --progress-bar off pytest \
+    scipy==$SCIPY_VERSION \
+    scikit-image \
+    psutil \
+    unittest-xml-reporting \
+    boto3==1.16.34 \
+    coverage==5.5 \
+    hypothesis==4.53.2 \
+    expecttest==0.1.3 \
+    mypy==0.812 \
+    tb-nightly
+
+  # Install numba only on python-3.8 or below
+  # For numba issue see https://github.com/pytorch/pytorch/issues/51511
+  if [[ $(python -c "import sys; print(int(sys.version_info < (3, 9)))") == "1" ]]; then
+    as_jenkins pip install --progress-bar off numba librosa>=0.6.2
+  else
+    as_jenkins pip install --progress-bar off numba==0.49.0 librosa>=0.6.2
+  fi
 
   # Update scikit-learn to a python-3.8 compatible version
   if [[ $(python -c "import sys; print(int(sys.version_info >= (3, 8)))") == "1" ]]; then
-    pip_install -U scikit-learn
+    as_jenkins pip install --progress-bar off -U scikit-learn
   else
     # Pinned scikit-learn due to https://github.com/scikit-learn/scikit-learn/issues/14485 (affects gcc 5.5 only)
-    pip_install scikit-learn==0.20.3
+    as_jenkins pip install --progress-bar off scikit-learn==0.20.3
   fi
 
   popd

.circleci/docker/common/install_cudnn.sh

@@ -1,24 +0,0 @@
-#!/bin/bash
-
-if [[ ${CUDNN_VERSION} == 8 ]]; then
-    # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
-    mkdir tmp_cudnn && cd tmp_cudnn
-    CUDNN_NAME="cudnn-linux-x86_64-8.3.2.44_cuda11.5-archive"
-    if [[ ${CUDA_VERSION:0:4} == "11.7" ]]; then
-        CUDNN_NAME="cudnn-linux-x86_64-8.5.0.96_cuda11-archive"
-        curl --retry 3 -OLs https://ossci-linux.s3.amazonaws.com/${CUDNN_NAME}.tar.xz
-    else
-        curl --retry 3 -OLs  https://developer.download.nvidia.com/compute/redist/cudnn/v8.3.2/local_installers/11.5/${CUDNN_NAME}.tar.xz
-    fi
-
-    tar xf ${CUDNN_NAME}.tar.xz
-    cp -a ${CUDNN_NAME}/include/* /usr/include/
-    cp -a ${CUDNN_NAME}/include/* /usr/local/cuda/include/
-    cp -a ${CUDNN_NAME}/include/* /usr/include/x86_64-linux-gnu/
-
-    cp -a ${CUDNN_NAME}/lib/* /usr/local/cuda/lib64/
-    cp -a ${CUDNN_NAME}/lib/* /usr/lib/x86_64-linux-gnu/
-    cd ..
-    rm -rf tmp_cudnn
-    ldconfig
-fi

.circleci/docker/common/install_docs_reqs.sh

@@ -1,25 +0,0 @@
-#!/bin/bash
-
-set -ex
-
-if [ -n "$KATEX" ]; then
-  apt-get update
-  # Ignore error if gpg-agent doesn't exist (for Ubuntu 16.04)
-  apt-get install -y gpg-agent || :
-
-  curl --retry 3 -sL https://deb.nodesource.com/setup_12.x | sudo -E bash -
-  sudo apt-get install -y nodejs
-
-  curl --retry 3 -sS https://dl.yarnpkg.com/debian/pubkey.gpg | sudo apt-key add -
-  echo "deb https://dl.yarnpkg.com/debian/ stable main" | sudo tee /etc/apt/sources.list.d/yarn.list
-
-  apt-get update
-  apt-get install -y --no-install-recommends yarn
-  yarn global add katex --prefix /usr/local
-
-  sudo apt-get -y install doxygen
-
-  apt-get autoclean && apt-get clean
-  rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
-
-fi

.circleci/docker/common/install_gcc.sh

@@ -7,18 +7,15 @@ if [ -n "$GCC_VERSION" ]; then
   # Need the official toolchain repo to get alternate packages
   add-apt-repository ppa:ubuntu-toolchain-r/test
   apt-get update
-  if [[ "$UBUNTU_VERSION" == "16.04" && "${GCC_VERSION:0:1}" == "5" ]]; then
+  if [ "$UBUNTU_VERSION" = "16.04" -a "$GCC_VERSION" = "5" ]; then
     apt-get install -y g++-5=5.4.0-6ubuntu1~16.04.12
-    update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-5 50
-    update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-5 50
-    update-alternatives --install /usr/bin/gcov gcov /usr/bin/gcov-5 50
   else
     apt-get install -y g++-$GCC_VERSION
-    update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-"$GCC_VERSION" 50
-    update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-"$GCC_VERSION" 50
-    update-alternatives --install /usr/bin/gcov gcov /usr/bin/gcov-"$GCC_VERSION" 50
   fi
 
+  update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-"$GCC_VERSION" 50
+  update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-"$GCC_VERSION" 50
+  update-alternatives --install /usr/bin/gcov gcov /usr/bin/gcov-"$GCC_VERSION" 50
 
   # Cleanup package manager
   apt-get autoclean && apt-get clean

.circleci/docker/common/install_katex.sh

@@ -0,0 +1,20 @@
+#!/bin/bash
+
+set -ex
+
+if [ -n "$KATEX" ]; then
+
+  curl -sL https://deb.nodesource.com/setup_12.x | sudo -E bash -
+  sudo apt-get install -y nodejs
+
+  curl -sS https://dl.yarnpkg.com/debian/pubkey.gpg | sudo apt-key add -
+  echo "deb https://dl.yarnpkg.com/debian/ stable main" | sudo tee /etc/apt/sources.list.d/yarn.list
+
+  apt-get update
+  apt-get install -y --no-install-recommends yarn
+  yarn global add katex --prefix /usr/local
+
+  apt-get autoclean && apt-get clean
+  rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
+
+fi

.circleci/docker/common/install_openssl.sh

@@ -4,13 +4,11 @@ set -ex
 
 OPENSSL=openssl-1.1.1k
 
-wget -q -O "${OPENSSL}.tar.gz" "https://ossci-linux.s3.amazonaws.com/${OPENSSL}.tar.gz"
+wget -q -O "${OPENSSL}.tar.gz" "https://www.openssl.org/source/${OPENSSL}.tar.gz"
 tar xf "${OPENSSL}.tar.gz"
 cd "${OPENSSL}"
 ./config --prefix=/opt/openssl -d '-Wl,--enable-new-dtags,-rpath,$(LIBRPATH)'
-# NOTE: openssl install errors out when built with the -j option
-make -j6; make install_sw
-# Link the ssl libraries to the /usr/lib folder.
-sudo ln -s /opt/openssl/lib/lib* /usr/lib
+# NOTE: opensl errors out when built with the -j option
+make install_sw
 cd ..
 rm -rf "${OPENSSL}"

.circleci/docker/common/install_protobuf.sh

@@ -12,11 +12,11 @@ install_protobuf_317() {
   #   g++: error: ./../lib64/crti.o: No such file or directory
   ln -s /usr/lib64 "$pb_dir/lib64"
 
-  curl -LO "https://github.com/protocolbuffers/protobuf/releases/download/v3.17.3/protobuf-all-3.17.3.tar.gz" --retry 3
+  curl -LO "https://github.com/protocolbuffers/protobuf/releases/download/v3.17.3/protobuf-all-3.17.3.tar.gz"
   tar -xvz -C "$pb_dir" --strip-components 1 -f protobuf-all-3.17.3.tar.gz
-  # -j6 to balance memory usage and speed.
+  # -j2 to balance memory usage and speed.
   # naked `-j` seems to use too much memory.
-  pushd "$pb_dir" && ./configure && make -j6 && make -j6 check && sudo make -j6 install && sudo ldconfig
+  pushd "$pb_dir" && ./configure && make -j2 && make -j2 check && sudo make -j2 install && sudo ldconfig
   popd
   rm -rf $pb_dir
 }

.circleci/docker/common/install_rocm.sh

@@ -2,23 +2,39 @@
 
 set -ex
 
+install_magma() {
+    # "install" hipMAGMA into /opt/rocm/magma by copying after build
+    git clone https://bitbucket.org/icl/magma.git -b magma_ctrl_launch_bounds
+    pushd magma
+    # The branch "magma_ctrl_launch_bounds" is having a fix over the below commit, so keeping the below comment for reference.
+    #git checkout 878b1ce02e9cfe4a829be22c8f911e9c0b6bd88f
+    # Work around non-asii characters in certain magma sources; remove this after upstream magma fixes this.
+    perl -i.bak -pe 's/[^[:ascii:]]//g' sparse/control/magma_zfree.cpp
+    perl -i.bak -pe 's/[^[:ascii:]]//g' sparse/control/magma_zsolverinfo.cpp
+    cp make.inc-examples/make.inc.hip-gcc-mkl make.inc
+    echo 'LIBDIR += -L$(MKLROOT)/lib' >> make.inc
+    echo 'LIB += -Wl,--enable-new-dtags -Wl,--rpath,/opt/rocm/lib -Wl,--rpath,$(MKLROOT)/lib -Wl,--rpath,/opt/rocm/magma/lib' >> make.inc
+    echo 'DEVCCFLAGS += --amdgpu-target=gfx803 --amdgpu-target=gfx900 --amdgpu-target=gfx906 --amdgpu-target=gfx908 --gpu-max-threads-per-block=256' >> make.inc
+    # hipcc with openmp flag may cause isnan() on __device__ not to be found; depending on context, compiler may attempt to match with host definition
+    sed -i 's/^FOPENMP/#FOPENMP/g' make.inc
+    export PATH="${PATH}:/opt/rocm/bin"
+    make -f make.gen.hipMAGMA -j $(nproc)
+    make lib/libmagma.so -j $(nproc) MKLROOT=/opt/conda
+    make testing/testing_dgemm -j $(nproc) MKLROOT=/opt/conda
+    popd
+    mv magma /opt/rocm
+}
+
 ver() {
     printf "%3d%03d%03d%03d" $(echo "$1" | tr '.' ' ');
 }
 
-# Map ROCm version to AMDGPU version
-declare -A AMDGPU_VERSIONS=( ["5.0"]="21.50" ["5.1.1"]="22.10.1" ["5.2"]="22.20" )
-
 install_ubuntu() {
     apt-get update
     if [[ $UBUNTU_VERSION == 18.04 ]]; then
       # gpg-agent is not available by default on 18.04
       apt-get install -y --no-install-recommends gpg-agent
     fi
-    if [[ $UBUNTU_VERSION == 20.04 ]]; then
-      # gpg-agent is not available by default on 20.04
-      apt-get install -y --no-install-recommends gpg-agent
-    fi
     apt-get install -y kmod
     apt-get install -y wget
 
@@ -26,31 +42,14 @@ install_ubuntu() {
     apt-get install -y libc++1
     apt-get install -y libc++abi1
 
-    if [[ $(ver $ROCM_VERSION) -ge $(ver 4.5) ]]; then
-        # Add amdgpu repository
-        UBUNTU_VERSION_NAME=`cat /etc/os-release | grep UBUNTU_CODENAME | awk -F= '{print $2}'`
-        local amdgpu_baseurl
-        if [[ $(ver $ROCM_VERSION) -ge $(ver 5.3) ]]; then
-          amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/ubuntu"
-        else
-          amdgpu_baseurl="https://repo.radeon.com/amdgpu/${AMDGPU_VERSIONS[$ROCM_VERSION]}/ubuntu"
-        fi
-        echo "deb [arch=amd64] ${amdgpu_baseurl} ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/amdgpu.list
-    fi
-
     ROCM_REPO="ubuntu"
     if [[ $(ver $ROCM_VERSION) -lt $(ver 4.2) ]]; then
         ROCM_REPO="xenial"
     fi
 
-    if [[ $(ver $ROCM_VERSION) -ge $(ver 5.3) ]]; then
-        ROCM_REPO="${UBUNTU_VERSION_NAME}"
-    fi
-
     # Add rocm repository
     wget -qO - http://repo.radeon.com/rocm/rocm.gpg.key | apt-key add -
-    local rocm_baseurl="http://repo.radeon.com/rocm/apt/${ROCM_VERSION}"
-    echo "deb [arch=amd64] ${rocm_baseurl} ${ROCM_REPO} main" > /etc/apt/sources.list.d/rocm.list
+    echo "deb [arch=amd64] http://repo.radeon.com/rocm/apt/${ROCM_VERSION} ${ROCM_REPO} main" > /etc/apt/sources.list.d/rocm.list
     apt-get update --allow-insecure-repositories
 
     DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated \
@@ -70,6 +69,8 @@ install_ubuntu() {
       DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ${MIOPENKERNELS}
     fi
 
+    install_magma
+
     # Cleanup
     apt-get autoclean && apt-get clean
     rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
@@ -85,33 +86,11 @@ install_centos() {
   yum install -y epel-release
   yum install -y dkms kernel-headers-`uname -r` kernel-devel-`uname -r`
 
-  if [[ $(ver $ROCM_VERSION) -ge $(ver 4.5) ]]; then
-      # Add amdgpu repository
-      local amdgpu_baseurl
-      if [[ $OS_VERSION == 9 ]]; then
-          amdgpu_baseurl="https://repo.radeon.com/amdgpu/${AMDGPU_VERSIONS[$ROCM_VERSION]}/rhel/9.0/main/x86_64"
-      else
-        if [[ $(ver $ROCM_VERSION) -ge $(ver 5.3) ]]; then
-          amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/rhel/7.9/main/x86_64"
-        else
-          amdgpu_baseurl="https://repo.radeon.com/amdgpu/${AMDGPU_VERSIONS[$ROCM_VERSION]}/rhel/7.9/main/x86_64"
-        fi
-      fi
-      echo "[AMDGPU]" > /etc/yum.repos.d/amdgpu.repo
-      echo "name=AMDGPU" >> /etc/yum.repos.d/amdgpu.repo
-      echo "baseurl=${amdgpu_baseurl}" >> /etc/yum.repos.d/amdgpu.repo
-      echo "enabled=1" >> /etc/yum.repos.d/amdgpu.repo
-      echo "gpgcheck=1" >> /etc/yum.repos.d/amdgpu.repo
-      echo "gpgkey=http://repo.radeon.com/rocm/rocm.gpg.key" >> /etc/yum.repos.d/amdgpu.repo
-  fi
-
-  local rocm_baseurl="http://repo.radeon.com/rocm/yum/${ROCM_VERSION}"
   echo "[ROCm]" > /etc/yum.repos.d/rocm.repo
   echo "name=ROCm" >> /etc/yum.repos.d/rocm.repo
-  echo "baseurl=${rocm_baseurl}" >> /etc/yum.repos.d/rocm.repo
+  echo "baseurl=http://repo.radeon.com/rocm/yum/${ROCM_VERSION}" >> /etc/yum.repos.d/rocm.repo
   echo "enabled=1" >> /etc/yum.repos.d/rocm.repo
-  echo "gpgcheck=1" >> /etc/yum.repos.d/rocm.repo
-  echo "gpgkey=http://repo.radeon.com/rocm/rocm.gpg.key" >> /etc/yum.repos.d/rocm.repo
+  echo "gpgcheck=0" >> /etc/yum.repos.d/rocm.repo
 
   yum update -y
 
@@ -123,6 +102,8 @@ install_centos() {
                    rocprofiler-dev \
                    roctracer-dev
 
+  install_magma
+
   # Cleanup
   yum clean all
   rm -rf /var/cache/yum

.circleci/docker/common/install_rocm_magma.sh

@@ -1,29 +0,0 @@
-#!/bin/bash
-
-set -ex
-
-# "install" hipMAGMA into /opt/rocm/magma by copying after build
-git clone https://bitbucket.org/icl/magma.git
-pushd magma
-# Fixes memory leaks of magma found while executing linalg UTs
-git checkout 5959b8783e45f1809812ed96ae762f38ee701972
-cp make.inc-examples/make.inc.hip-gcc-mkl make.inc
-echo 'LIBDIR += -L$(MKLROOT)/lib' >> make.inc
-echo 'LIB += -Wl,--enable-new-dtags -Wl,--rpath,/opt/rocm/lib -Wl,--rpath,$(MKLROOT)/lib -Wl,--rpath,/opt/rocm/magma/lib' >> make.inc
-echo 'DEVCCFLAGS += --gpu-max-threads-per-block=256' >> make.inc
-export PATH="${PATH}:/opt/rocm/bin"
-if [[ -n "$PYTORCH_ROCM_ARCH" ]]; then
-  amdgpu_targets=`echo $PYTORCH_ROCM_ARCH | sed 's/;/ /g'`
-else
-  amdgpu_targets=`rocm_agent_enumerator | grep -v gfx000 | sort -u | xargs`
-fi
-for arch in $amdgpu_targets; do
-  echo "DEVCCFLAGS += --amdgpu-target=$arch" >> make.inc
-done
-# hipcc with openmp flag may cause isnan() on __device__ not to be found; depending on context, compiler may attempt to match with host definition
-sed -i 's/^FOPENMP/#FOPENMP/g' make.inc
-make -f make.gen.hipMAGMA -j $(nproc)
-LANG=C.UTF-8 make lib/libmagma.so -j $(nproc) MKLROOT=/opt/conda
-make testing/testing_dgemm -j $(nproc) MKLROOT=/opt/conda
-popd
-mv magma /opt/rocm

.circleci/docker/common/install_ucc.sh

@@ -1,48 +0,0 @@
-#!/bin/bash
-
-set -ex
-
-if [[ -d "/usr/local/cuda/" ]];  then
-  with_cuda=/usr/local/cuda/
-else
-  with_cuda=no
-fi
-
-function install_ucx() {
-  set -ex
-  git clone --recursive https://github.com/openucx/ucx.git
-  pushd ucx
-  git checkout ${UCX_COMMIT}
-  git submodule update --init --recursive
-
-  ./autogen.sh
-  ./configure --prefix=$UCX_HOME      \
-      --enable-mt                     \
-      --with-cuda=$with_cuda          \
-      --enable-profiling              \
-      --enable-stats
-  time make -j
-  sudo make install
-
-  popd
-  rm -rf ucx
-}
-
-function install_ucc() {
-  set -ex
-  git clone --recursive https://github.com/openucx/ucc.git
-  pushd ucc
-  git checkout ${UCC_COMMIT}
-  git submodule update --init --recursive
-
-  ./autogen.sh
-  ./configure --prefix=$UCC_HOME --with-ucx=$UCX_HOME --with-cuda=$with_cuda
-  time make -j
-  sudo make install
-
-  popd
-  rm -rf ucc
-}
-
-install_ucx
-install_ucc

.circleci/docker/common/install_user.sh

@@ -3,11 +3,8 @@
 set -ex
 
 # Mirror jenkins user in container
-# jenkins user as ec2-user should have the same user-id
-echo "jenkins:x:1000:1000::/var/lib/jenkins:" >> /etc/passwd
-echo "jenkins:x:1000:" >> /etc/group
-# Needed on focal or newer
-echo "jenkins:*:19110:0:99999:7:::" >>/etc/shadow
+echo "jenkins:x:1014:1014::/var/lib/jenkins:" >> /etc/passwd
+echo "jenkins:x:1014:" >> /etc/group
 
 # Create $HOME
 mkdir -p /var/lib/jenkins
@@ -21,6 +18,3 @@ chown jenkins:jenkins /usr/local
 # Allow sudo
 # TODO: Maybe we shouldn't
 echo 'jenkins ALL=(ALL) NOPASSWD:ALL' > /etc/sudoers.d/jenkins
-
-# Test that sudo works
-sudo -u jenkins sudo -v

.circleci/docker/requirements-ci.txt

@@ -1,249 +0,0 @@
-# Python dependencies required for unit tests
-
-#awscli==1.6 #this breaks some platforms
-#Description: AWS command line interface
-#Pinned versions: 1.6
-#test that import:
-
-boto3==1.19.12
-#Description: AWS SDK for python
-#Pinned versions: 1.19.12, 1.16.34
-#test that import:
-
-click
-#Description: Command Line Interface Creation Kit
-#Pinned versions:
-#test that import:
-
-coremltools==5.0b5
-#Description: Apple framework for ML integration
-#Pinned versions: 5.0b5
-#test that import:
-
-#dataclasses #this breaks some platforms
-#Description: Provides decorators for auto adding special methods to user classes
-#Pinned versions:
-#test that import:
-
-expecttest==0.1.3
-#Description: method for writing tests where test framework auto populates
-# the expected output based on previous runs
-#Pinned versions: 0.1.3
-#test that import:
-
-flatbuffers==2.0
-#Description: cross platform serialization library
-#Pinned versions: 2.0
-#test that import:
-
-#future #this breaks linux-bionic-rocm4.5-py3.7
-#Description: compatibility layer between python 2 and python 3
-#Pinned versions:
-#test that import:
-
-hypothesis==5.35.1
-# Pin hypothesis to avoid flakiness: https://github.com/pytorch/pytorch/issues/31136
-#Description: advanced library for generating parametrized tests
-#Pinned versions: 3.44.6, 4.53.2
-#test that import: test_xnnpack_integration.py, test_pruning_op.py, test_nn.py
-
-junitparser==2.1.1
-#Description: unitparser handles JUnit/xUnit Result XML files
-#Pinned versions: 2.1.1
-#test that import:
-
-librosa>=0.6.2
-#Description: A python package for music and audio analysis
-#Pinned versions: >=0.6.2
-#test that import: test_spectral_ops.py
-
-#mkl #this breaks linux-bionic-rocm4.5-py3.7
-#Description: Intel oneAPI Math Kernel Library
-#Pinned versions:
-#test that import: test_profiler.py, test_public_bindings.py, test_testing.py,
-#test_nn.py, test_mkldnn.py, test_jit.py, test_fx_experimental.py,
-#test_autograd.py
-
-#mkl-devel
-# see mkl
-
-#mock # breaks ci/circleci: docker-pytorch-linux-xenial-py3-clang5-android-ndk-r19c
-#Description: A testing library that allows you to replace parts of your
-#system under test with mock objects
-#Pinned versions:
-#test that import: test_module_init.py, test_modules.py, test_nn.py,
-#test_testing.py
-
-#MonkeyType # breaks pytorch-xla-linux-bionic-py3.7-clang8
-#Description: collects runtime types of function arguments and return
-#values, and can automatically generate stub files
-#Pinned versions:
-#test that import:
-
-mypy==0.960
-# Pin MyPy version because new errors are likely to appear with each release
-#Description: linter
-#Pinned versions: 0.960
-#test that import: test_typing.py, test_type_hints.py
-
-networkx==2.6.3
-#Description: creation, manipulation, and study of
-#the structure, dynamics, and functions of complex networks
-#Pinned versions: 2.6.3 (latest version that works with Python 3.7+)
-#test that import: functorch
-
-#ninja
-#Description: build system.  Note that it install from
-#here breaks things so it is commented out
-#Pinned versions: 1.10.0.post1
-#test that import: run_test.py, test_cpp_extensions_aot.py,test_determination.py
-
-numba==0.49.0 ; python_version < "3.9"
-numba==0.54.1 ; python_version == "3.9"
-numba==0.55.2 ; python_version == "3.10"
-#Description: Just-In-Time Compiler for Numerical Functions
-#Pinned versions: 0.54.1, 0.49.0, <=0.49.1
-#test that import: test_numba_integration.py
-#For numba issue see https://github.com/pytorch/pytorch/issues/51511
-
-#numpy
-#Description: Provides N-dimensional arrays and linear algebra
-#Pinned versions: 1.20
-#test that import: test_view_ops.py, test_unary_ufuncs.py, test_type_promotion.py,
-#test_type_info.py, test_torch.py, test_tensorexpr_pybind.py, test_tensorexpr.py,
-#test_tensorboard.py, test_tensor_creation_ops.py, test_static_runtime.py,
-#test_spectral_ops.py, test_sort_and_select.py, test_shape_ops.py,
-#test_segment_reductions.py, test_reductions.py, test_pruning_op.py,
-#test_overrides.py, test_numpy_interop.py, test_numba_integration.py
-#test_nn.py, test_namedtensor.py, test_linalg.py, test_jit_cuda_fuser.py,
-#test_jit.py, test_indexing.py, test_datapipe.py, test_dataloader.py,
-#test_binary_ufuncs.py
-
-#onnxruntime
-#Description: scoring engine for Open Neural Network Exchange (ONNX) models
-#Pinned versions: 1.9.0
-#test that import:
-
-opt-einsum==3.3
-#Description: Python library to optimize tensor contraction order, used in einsum
-#Pinned versions: 3.3
-#test that import: test_linalg.py
-
-#pillow
-#Description:  Python Imaging Library fork
-#Pinned versions:
-#test that import:
-
-protobuf==3.20.2
-#Description:  Google’s data interchange format
-#Pinned versions: 3.20.1
-#test that import: test_tensorboard.py
-
-psutil
-#Description: information on running processes and system utilization
-#Pinned versions:
-#test that import: test_profiler.py, test_openmp.py, test_dataloader.py
-
-pytest
-#Description: testing framework
-#Pinned versions:
-#test that import: test_typing.py, test_cpp_extensions_aot.py, run_test.py
-
-pytest-xdist
-#Description: plugin for running pytest in parallel
-#Pinned versions:
-#test that import:
-
-pytest-shard
-#Description: plugin spliting up tests in pytest
-#Pinned versions:
-#test that import:
-
-pytest-flakefinder==1.1.0
-#Description: plugin for rerunning tests a fixed number of times in pytest
-#Pinned versions: 1.1.0
-#test that import:
-
-pytest-rerunfailures
-#Description: plugin for rerunning failure tests in pytest
-#Pinned versions:
-#test that import:
-
-#pytest-benchmark
-#Description: fixture for benchmarking code
-#Pinned versions: 3.2.3
-#test that import:
-
-#pytest-sugar
-#Description: shows failures and errors instantly
-#Pinned versions:
-#test that import:
-
-xdoctest==1.0.2
-#Description: runs doctests in pytest
-#Pinned versions: 1.0.2
-#test that import:
-
-pygments==2.12.0
-#Description: support doctest highlighting
-#Pinned versions: 2.12.0
-#test that import: the doctests
-
-#PyYAML
-#Description: data serialization format
-#Pinned versions:
-#test that import:
-
-#requests
-#Description: HTTP library
-#Pinned versions:
-#test that import: test_type_promotion.py
-
-#rich
-#Description: rich text and beautiful formatting in the terminal
-#Pinned versions: 10.9.0
-#test that import:
-
-scikit-image
-#Description: image processing routines
-#Pinned versions:
-#test that import: test_nn.py
-
-#scikit-learn
-#Description: machine learning package
-#Pinned versions: 0.20.3
-#test that import:
-
-scipy==1.6.3 ; python_version < "3.10"
-scipy==1.8.1 ; python_version == "3.10"
-# Pin SciPy because of failing distribution tests (see #60347)
-#Description: scientific python
-#Pinned versions: 1.6.3
-#test that import: test_unary_ufuncs.py, test_torch.py,test_tensor_creation_ops.py
-#test_spectral_ops.py, test_sparse_csr.py, test_reductions.py,test_nn.py
-#test_linalg.py, test_binary_ufuncs.py
-
-#tabulate
-#Description: Pretty-print tabular data
-#Pinned versions:
-#test that import:
-
-tb-nightly
-#Description: TensorBoard
-#Pinned versions:
-#test that import:
-
-#typing-extensions
-#Description: type hints for python
-#Pinned versions:
-#test that import:
-
-#virtualenv
-#Description: virtual environment for python
-#Pinned versions:
-#test that import:
-
-unittest-xml-reporting<=3.2.0,>=2.0.0
-#Description: saves unit test results to xml
-#Pinned versions:
-#test that import:

.circleci/docker/ubuntu-cuda/Dockerfile

@@ -1,107 +1,89 @@
 ARG UBUNTU_VERSION
 ARG CUDA_VERSION
-ARG IMAGE_NAME
+ARG CUDNN_VERSION
 
-FROM ${IMAGE_NAME}
+FROM nvidia/cuda:${CUDA_VERSION}-cudnn${CUDNN_VERSION}-devel-ubuntu${UBUNTU_VERSION}
 
 ARG UBUNTU_VERSION
 ARG CUDA_VERSION
+ARG CUDNN_VERSION
 
 ENV DEBIAN_FRONTEND noninteractive
 
 # Install common dependencies (so that this step can be cached separately)
 ARG EC2
-COPY ./common/install_base.sh install_base.sh
+ADD ./common/install_base.sh install_base.sh
 RUN bash ./install_base.sh && rm install_base.sh
 
 # Install user
-COPY ./common/install_user.sh install_user.sh
+ADD ./common/install_user.sh install_user.sh
 RUN bash ./install_user.sh && rm install_user.sh
 
 # Install katex
 ARG KATEX
-COPY ./common/install_docs_reqs.sh install_docs_reqs.sh
-RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
+ADD ./common/install_katex.sh install_katex.sh
+RUN bash ./install_katex.sh && rm install_katex.sh
 
-# Install conda and other packages (e.g., numpy, pytest)
+# Install conda and other packages (e.g., numpy, coverage, pytest)
 ENV PATH /opt/conda/bin:$PATH
 ARG ANACONDA_PYTHON_VERSION
-ARG CONDA_CMAKE
-COPY requirements-ci.txt /opt/conda/requirements-ci.txt
-COPY ./common/install_conda.sh install_conda.sh
+ADD ./common/install_conda.sh install_conda.sh
 RUN bash ./install_conda.sh && rm install_conda.sh
-RUN rm /opt/conda/requirements-ci.txt
 
 # Install gcc
 ARG GCC_VERSION
-COPY ./common/install_gcc.sh install_gcc.sh
+ADD ./common/install_gcc.sh install_gcc.sh
 RUN bash ./install_gcc.sh && rm install_gcc.sh
 
 # Install clang
 ARG CLANG_VERSION
-COPY ./common/install_clang.sh install_clang.sh
+ADD ./common/install_clang.sh install_clang.sh
 RUN bash ./install_clang.sh && rm install_clang.sh
 
 # (optional) Install protobuf for ONNX
 ARG PROTOBUF
-COPY ./common/install_protobuf.sh install_protobuf.sh
+ADD ./common/install_protobuf.sh install_protobuf.sh
 RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
 RUN rm install_protobuf.sh
 ENV INSTALLED_PROTOBUF ${PROTOBUF}
 
 # (optional) Install database packages like LMDB and LevelDB
 ARG DB
-COPY ./common/install_db.sh install_db.sh
+ADD ./common/install_db.sh install_db.sh
 RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
 RUN rm install_db.sh
 ENV INSTALLED_DB ${DB}
 
 # (optional) Install vision packages like OpenCV and ffmpeg
 ARG VISION
-COPY ./common/install_vision.sh install_vision.sh
+ADD ./common/install_vision.sh install_vision.sh
 RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
 RUN rm install_vision.sh
 ENV INSTALLED_VISION ${VISION}
 
-# (optional) Install UCC
-ARG UCX_COMMIT
-ARG UCC_COMMIT
-ENV UCX_COMMIT $UCX_COMMIT
-ENV UCC_COMMIT $UCC_COMMIT
-ENV UCX_HOME /usr
-ENV UCC_HOME /usr
-ADD ./common/install_ucc.sh install_ucc.sh
-RUN if [ -n "${UCX_COMMIT}" ] && [ -n "${UCC_COMMIT}" ]; then bash ./install_ucc.sh; fi
-RUN rm install_ucc.sh
-
-COPY ./common/install_openssl.sh install_openssl.sh
+ADD ./common/install_openssl.sh install_openssl.sh
 ENV OPENSSL_ROOT_DIR /opt/openssl
 RUN bash ./install_openssl.sh
-ENV OPENSSL_DIR /opt/openssl
 
 # (optional) Install non-default CMake version
 ARG CMAKE_VERSION
-COPY ./common/install_cmake.sh install_cmake.sh
+ADD ./common/install_cmake.sh install_cmake.sh
 RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
 RUN rm install_cmake.sh
 
 # Install ccache/sccache (do this last, so we get priority in PATH)
-COPY ./common/install_cache.sh install_cache.sh
+ADD ./common/install_cache.sh install_cache.sh
 ENV PATH /opt/cache/bin:$PATH
-# See https://github.com/pytorch/pytorch/issues/82174
-# TODO(sdym@fb.com):
-# check if this is needed after full off Xenial migration
-ENV CARGO_NET_GIT_FETCH_WITH_CLI true
 RUN bash ./install_cache.sh && rm install_cache.sh
-ENV CMAKE_CUDA_COMPILER_LAUNCHER=/opt/cache/bin/sccache
+ENV CUDA_NVCC_EXECUTABLE=/opt/cache/lib/nvcc
 
 # Add jni.h for java host build
-COPY ./common/install_jni.sh install_jni.sh
-COPY ./java/jni.h jni.h
+ADD ./common/install_jni.sh install_jni.sh
+ADD ./java/jni.h jni.h
 RUN bash ./install_jni.sh && rm install_jni.sh
 
 # Install Open MPI for CUDA
-COPY ./common/install_openmpi.sh install_openmpi.sh
+ADD ./common/install_openmpi.sh install_openmpi.sh
 RUN if [ -n "${CUDA_VERSION}" ]; then bash install_openmpi.sh; fi
 RUN rm install_openmpi.sh
 
@@ -112,21 +94,9 @@ ENV BUILD_ENVIRONMENT ${BUILD_ENVIRONMENT}
 # AWS specific CUDA build guidance
 ENV TORCH_CUDA_ARCH_LIST Maxwell
 ENV TORCH_NVCC_FLAGS "-Xfatbin -compress-all"
-ENV CUDA_PATH /usr/local/cuda
 
 # Install LLVM dev version (Defined in the pytorch/builder github repository)
 COPY --from=pytorch/llvm:9.0.1 /opt/llvm /opt/llvm
 
-# Install CUDNN
-ARG CUDNN_VERSION
-ARG CUDA_VERSION
-COPY ./common/install_cudnn.sh install_cudnn.sh
-RUN if [ "${CUDNN_VERSION}" -eq 8 ]; then bash install_cudnn.sh; fi
-RUN rm install_cudnn.sh
-
-# Delete /usr/local/cuda-11.X/cuda-11.X symlinks
-RUN if [ -h /usr/local/cuda-11.6/cuda-11.6 ]; then rm /usr/local/cuda-11.6/cuda-11.6; fi
-RUN if [ -h /usr/local/cuda-11.7/cuda-11.7 ]; then rm /usr/local/cuda-11.7/cuda-11.7; fi
-
 USER jenkins
 CMD ["bash"]

.circleci/docker/ubuntu-rocm/Dockerfile

@@ -6,68 +6,58 @@ ARG UBUNTU_VERSION
 
 ENV DEBIAN_FRONTEND noninteractive
 
-# Set AMD gpu targets to build for
-ARG PYTORCH_ROCM_ARCH
-ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
-
 # Install common dependencies (so that this step can be cached separately)
 ARG EC2
-COPY ./common/install_base.sh install_base.sh
+ADD ./common/install_base.sh install_base.sh
 RUN bash ./install_base.sh && rm install_base.sh
 
 # Install clang
 ARG LLVMDEV
 ARG CLANG_VERSION
-COPY ./common/install_clang.sh install_clang.sh
+ADD ./common/install_clang.sh install_clang.sh
 RUN bash ./install_clang.sh && rm install_clang.sh
 
 # Install user
-COPY ./common/install_user.sh install_user.sh
+ADD ./common/install_user.sh install_user.sh
 RUN bash ./install_user.sh && rm install_user.sh
 
-# Install conda and other packages (e.g., numpy, pytest)
+# Install conda and other packages (e.g., numpy, coverage, pytest)
 ENV PATH /opt/conda/bin:$PATH
 ARG ANACONDA_PYTHON_VERSION
-ARG CONDA_CMAKE
-COPY requirements-ci.txt /opt/conda/requirements-ci.txt
-COPY ./common/install_conda.sh install_conda.sh
+ADD ./common/install_conda.sh install_conda.sh
 RUN bash ./install_conda.sh && rm install_conda.sh
-RUN rm /opt/conda/requirements-ci.txt
 
 # Install gcc
 ARG GCC_VERSION
-COPY ./common/install_gcc.sh install_gcc.sh
+ADD ./common/install_gcc.sh install_gcc.sh
 RUN bash ./install_gcc.sh && rm install_gcc.sh
 
 # (optional) Install protobuf for ONNX
 ARG PROTOBUF
-COPY ./common/install_protobuf.sh install_protobuf.sh
+ADD ./common/install_protobuf.sh install_protobuf.sh
 RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
 RUN rm install_protobuf.sh
 ENV INSTALLED_PROTOBUF ${PROTOBUF}
 
 # (optional) Install database packages like LMDB and LevelDB
 ARG DB
-COPY ./common/install_db.sh install_db.sh
+ADD ./common/install_db.sh install_db.sh
 RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
 RUN rm install_db.sh
 ENV INSTALLED_DB ${DB}
 
 # (optional) Install vision packages like OpenCV and ffmpeg
 ARG VISION
-COPY ./common/install_vision.sh install_vision.sh
+ADD ./common/install_vision.sh install_vision.sh
 RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
 RUN rm install_vision.sh
 ENV INSTALLED_VISION ${VISION}
 
 # Install rocm
 ARG ROCM_VERSION
-COPY ./common/install_rocm.sh install_rocm.sh
+ADD ./common/install_rocm.sh install_rocm.sh
 RUN bash ./install_rocm.sh
 RUN rm install_rocm.sh
-COPY ./common/install_rocm_magma.sh install_rocm_magma.sh
-RUN bash ./install_rocm_magma.sh
-RUN rm install_rocm_magma.sh
 ENV PATH /opt/rocm/bin:$PATH
 ENV PATH /opt/rocm/hcc/bin:$PATH
 ENV PATH /opt/rocm/hip/bin:$PATH
@@ -79,18 +69,18 @@ ENV LC_ALL C.UTF-8
 
 # (optional) Install non-default CMake version
 ARG CMAKE_VERSION
-COPY ./common/install_cmake.sh install_cmake.sh
+ADD ./common/install_cmake.sh install_cmake.sh
 RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
 RUN rm install_cmake.sh
 
 # (optional) Install non-default Ninja version
 ARG NINJA_VERSION
-COPY ./common/install_ninja.sh install_ninja.sh
+ADD ./common/install_ninja.sh install_ninja.sh
 RUN if [ -n "${NINJA_VERSION}" ]; then bash ./install_ninja.sh; fi
 RUN rm install_ninja.sh
 
 # Install ccache/sccache (do this last, so we get priority in PATH)
-COPY ./common/install_cache.sh install_cache.sh
+ADD ./common/install_cache.sh install_cache.sh
 ENV PATH /opt/cache/bin:$PATH
 RUN bash ./install_cache.sh && rm install_cache.sh
 

.circleci/docker/ubuntu/Dockerfile

@@ -6,87 +6,65 @@ ARG UBUNTU_VERSION
 
 ENV DEBIAN_FRONTEND noninteractive
 
-ARG CLANG_VERSION
-
 # Install common dependencies (so that this step can be cached separately)
 ARG EC2
-COPY ./common/install_base.sh install_base.sh
+ADD ./common/install_base.sh install_base.sh
 RUN bash ./install_base.sh && rm install_base.sh
 
 # Install clang
 ARG LLVMDEV
-COPY ./common/install_clang.sh install_clang.sh
+ARG CLANG_VERSION
+ADD ./common/install_clang.sh install_clang.sh
 RUN bash ./install_clang.sh && rm install_clang.sh
 
 # (optional) Install thrift.
 ARG THRIFT
-COPY ./common/install_thrift.sh install_thrift.sh
+ADD ./common/install_thrift.sh install_thrift.sh
 RUN if [ -n "${THRIFT}" ]; then bash ./install_thrift.sh; fi
 RUN rm install_thrift.sh
 ENV INSTALLED_THRIFT ${THRIFT}
 
 # Install user
-COPY ./common/install_user.sh install_user.sh
+ADD ./common/install_user.sh install_user.sh
 RUN bash ./install_user.sh && rm install_user.sh
 
 # Install katex
 ARG KATEX
-COPY ./common/install_docs_reqs.sh install_docs_reqs.sh
-RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
+ADD ./common/install_katex.sh install_katex.sh
+RUN bash ./install_katex.sh && rm install_katex.sh
 
-# Install conda and other packages (e.g., numpy, pytest)
+# Install conda and other packages (e.g., numpy, coverage, pytest)
 ENV PATH /opt/conda/bin:$PATH
 ARG ANACONDA_PYTHON_VERSION
-ARG CONDA_CMAKE
-COPY requirements-ci.txt /opt/conda/requirements-ci.txt
-COPY ./common/install_conda.sh install_conda.sh
+ADD ./common/install_conda.sh install_conda.sh
 RUN bash ./install_conda.sh && rm install_conda.sh
-RUN rm /opt/conda/requirements-ci.txt
 
 # Install gcc
 ARG GCC_VERSION
-COPY ./common/install_gcc.sh install_gcc.sh
+ADD ./common/install_gcc.sh install_gcc.sh
 RUN bash ./install_gcc.sh && rm install_gcc.sh
 
 # Install lcov for C++ code coverage
-COPY ./common/install_lcov.sh install_lcov.sh
+ADD ./common/install_lcov.sh install_lcov.sh
 RUN  bash ./install_lcov.sh && rm install_lcov.sh
 
-# Install cuda and cudnn
-ARG CUDA_VERSION
-RUN wget -q https://raw.githubusercontent.com/pytorch/builder/main/common/install_cuda.sh -O install_cuda.sh
-RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh
-ENV DESIRED_CUDA ${CUDA_VERSION}
-ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:$PATH
-
-# (optional) Install UCC
-ARG UCX_COMMIT
-ARG UCC_COMMIT
-ENV UCX_COMMIT $UCX_COMMIT
-ENV UCC_COMMIT $UCC_COMMIT
-ENV UCX_HOME /usr
-ENV UCC_HOME /usr
-ADD ./common/install_ucc.sh install_ucc.sh
-RUN if [ -n "${UCX_COMMIT}" ] && [ -n "${UCC_COMMIT}" ]; then bash ./install_ucc.sh; fi
-RUN rm install_ucc.sh
-
 # (optional) Install protobuf for ONNX
 ARG PROTOBUF
-COPY ./common/install_protobuf.sh install_protobuf.sh
+ADD ./common/install_protobuf.sh install_protobuf.sh
 RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
 RUN rm install_protobuf.sh
 ENV INSTALLED_PROTOBUF ${PROTOBUF}
 
 # (optional) Install database packages like LMDB and LevelDB
 ARG DB
-COPY ./common/install_db.sh install_db.sh
+ADD ./common/install_db.sh install_db.sh
 RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
 RUN rm install_db.sh
 ENV INSTALLED_DB ${DB}
 
 # (optional) Install vision packages like OpenCV and ffmpeg
 ARG VISION
-COPY ./common/install_vision.sh install_vision.sh
+ADD ./common/install_vision.sh install_vision.sh
 RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
 RUN rm install_vision.sh
 ENV INSTALLED_VISION ${VISION}
@@ -95,9 +73,9 @@ ENV INSTALLED_VISION ${VISION}
 ARG ANDROID
 ARG ANDROID_NDK
 ARG GRADLE_VERSION
-COPY ./common/install_android.sh install_android.sh
-COPY ./android/AndroidManifest.xml AndroidManifest.xml
-COPY ./android/build.gradle build.gradle
+ADD ./common/install_android.sh install_android.sh
+ADD ./android/AndroidManifest.xml AndroidManifest.xml
+ADD ./android/build.gradle build.gradle
 RUN if [ -n "${ANDROID}" ]; then bash ./install_android.sh; fi
 RUN rm install_android.sh
 RUN rm AndroidManifest.xml
@@ -106,53 +84,42 @@ ENV INSTALLED_ANDROID ${ANDROID}
 
 # (optional) Install Vulkan SDK
 ARG VULKAN_SDK_VERSION
-COPY ./common/install_vulkan_sdk.sh install_vulkan_sdk.sh
+ADD ./common/install_vulkan_sdk.sh install_vulkan_sdk.sh
 RUN if [ -n "${VULKAN_SDK_VERSION}" ]; then bash ./install_vulkan_sdk.sh; fi
 RUN rm install_vulkan_sdk.sh
 
 # (optional) Install swiftshader
 ARG SWIFTSHADER
-COPY ./common/install_swiftshader.sh install_swiftshader.sh
+ADD ./common/install_swiftshader.sh install_swiftshader.sh
 RUN if [ -n "${SWIFTSHADER}" ]; then bash ./install_swiftshader.sh; fi
 RUN rm install_swiftshader.sh
 
 # (optional) Install non-default CMake version
 ARG CMAKE_VERSION
-COPY ./common/install_cmake.sh install_cmake.sh
+ADD ./common/install_cmake.sh install_cmake.sh
 RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
 RUN rm install_cmake.sh
 
 # (optional) Install non-default Ninja version
 ARG NINJA_VERSION
-COPY ./common/install_ninja.sh install_ninja.sh
+ADD ./common/install_ninja.sh install_ninja.sh
 RUN if [ -n "${NINJA_VERSION}" ]; then bash ./install_ninja.sh; fi
 RUN rm install_ninja.sh
 
-COPY ./common/install_openssl.sh install_openssl.sh
+ADD ./common/install_openssl.sh install_openssl.sh
 RUN bash ./install_openssl.sh
 ENV OPENSSL_ROOT_DIR /opt/openssl
-ENV OPENSSL_DIR /opt/openssl
-RUN rm install_openssl.sh
 
 # Install ccache/sccache (do this last, so we get priority in PATH)
-COPY ./common/install_cache.sh install_cache.sh
+ADD ./common/install_cache.sh install_cache.sh
 ENV PATH /opt/cache/bin:$PATH
-# See https://github.com/pytorch/pytorch/issues/82174
-# TODO(sdym@fb.com):
-# check if this is needed after full off Xenial migration
-ENV CARGO_NET_GIT_FETCH_WITH_CLI true
 RUN bash ./install_cache.sh && rm install_cache.sh
 
 # Add jni.h for java host build
-COPY ./common/install_jni.sh install_jni.sh
-COPY ./java/jni.h jni.h
+ADD ./common/install_jni.sh install_jni.sh
+ADD ./java/jni.h jni.h
 RUN bash ./install_jni.sh && rm install_jni.sh
 
-# Install Open MPI for CUDA
-COPY ./common/install_openmpi.sh install_openmpi.sh
-RUN if [ -n "${CUDA_VERSION}" ]; then bash install_openmpi.sh; fi
-RUN rm install_openmpi.sh
-
 # Include BUILD_ENVIRONMENT environment variable in image
 ARG BUILD_ENVIRONMENT
 ENV BUILD_ENVIRONMENT ${BUILD_ENVIRONMENT}
@@ -160,10 +127,5 @@ ENV BUILD_ENVIRONMENT ${BUILD_ENVIRONMENT}
 # Install LLVM dev version (Defined in the pytorch/builder github repository)
 COPY --from=pytorch/llvm:9.0.1 /opt/llvm /opt/llvm
 
-# AWS specific CUDA build guidance
-ENV TORCH_CUDA_ARCH_LIST Maxwell
-ENV TORCH_NVCC_FLAGS "-Xfatbin -compress-all"
-ENV CUDA_PATH /usr/local/cuda
-
 USER jenkins
 CMD ["bash"]

.circleci/ecr_gc_docker/Dockerfile

@@ -0,0 +1,13 @@
+FROM ubuntu:18.04
+
+RUN apt-get update && apt-get install -y python3-pip git && rm -rf /var/lib/apt/lists/* /var/log/dpkg.log
+
+ADD requirements.txt /requirements.txt
+
+RUN pip3 install -r /requirements.txt
+
+ADD gc.py /usr/bin/gc.py
+
+ADD docker_hub.py /usr/bin/docker_hub.py
+
+ENTRYPOINT ["/usr/bin/gc.py"]

.circleci/ecr_gc_docker/docker_hub.py

@@ -0,0 +1,125 @@
+#!/usr/bin/env python3
+
+from collections import namedtuple
+
+import boto3
+import requests
+import os
+
+
+IMAGE_INFO = namedtuple(
+    "IMAGE_INFO", ("repo", "tag", "size", "last_updated_at", "last_updated_by")
+)
+
+
+def build_access_token(username, passwordtr):
+    r = requests.post(
+        "https://hub.docker.com/v2/users/login/",
+        data={"username": username, "password": password},
+    )
+    r.raise_for_status()
+    token = r.json().get("token")
+    return {"Authorization": "JWT " + token}
+
+
+def list_repos(user, token):
+    r = requests.get("https://hub.docker.com/v2/repositories/" + user, headers=token)
+    r.raise_for_status()
+    ret = sorted(
+        repo["user"] + "/" + repo["name"] for repo in r.json().get("results", [])
+    )
+    if ret:
+        print("repos found:")
+        print("".join("\n\t" + r for r in ret))
+    return ret
+
+
+def list_tags(repo, token):
+    r = requests.get(
+        "https://hub.docker.com/v2/repositories/" + repo + "/tags", headers=token
+    )
+    r.raise_for_status()
+    return [
+        IMAGE_INFO(
+            repo=repo,
+            tag=t["name"],
+            size=t["full_size"],
+            last_updated_at=t["last_updated"],
+            last_updated_by=t["last_updater_username"],
+        )
+        for t in r.json().get("results", [])
+    ]
+
+
+def save_to_s3(tags):
+    table_content = ""
+    client = boto3.client("s3")
+    for t in tags:
+        table_content += (
+            "<tr><td>{repo}</td><td>{tag}</td><td>{size}</td>"
+            "<td>{last_updated_at}</td><td>{last_updated_by}</td></tr>"
+        ).format(
+            repo=t.repo,
+            tag=t.tag,
+            size=t.size,
+            last_updated_at=t.last_updated_at,
+            last_updated_by=t.last_updated_by,
+        )
+    html_body = """
+    <html>
+        <head>
+            <link rel="stylesheet"
+                href="https://stackpath.bootstrapcdn.com/bootstrap/4.4.1/css/bootstrap.min.css"
+                integrity="sha384-Vkoo8x4CGsO3+Hhxv8T/Q5PaXtkKtu6ug5TOeNV6gBiFeWPGFN9MuhOf23Q9Ifjh"
+                crossorigin="anonymous">
+            <link rel="stylesheet" type="text/css"
+                href="https://cdn.datatables.net/1.10.20/css/jquery.dataTables.css">
+            <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js">
+            </script>
+            <script type="text/javascript" charset="utf8"
+                src="https://cdn.datatables.net/1.10.20/js/jquery.dataTables.js"></script>
+            <title> docker image info</title>
+        </head>
+        <body>
+            <table class="table table-striped table-hover" id="docker">
+            <caption>Docker images on docker hub</caption>
+            <thead class="thead-dark">
+                <tr>
+                <th scope="col">repo</th>
+                <th scope="col">tag</th>
+                <th scope="col">size</th>
+                <th scope="col">last_updated_at</th>
+                <th scope="col">last_updated_by</th>
+                </tr>
+            </thead>
+            <tbody>
+                {table_content}
+            </tbody>
+            </table>
+        </body>
+        <script>
+            $(document).ready( function () {{
+                $('#docker').DataTable({{paging: false}});
+            }} );py
+        </script>
+    </html>
+    """.format(
+        table_content=table_content
+    )
+    client.put_object(
+        Bucket="docker.pytorch.org",
+        ACL="public-read",
+        Key="docker_hub.html",
+        Body=html_body,
+        ContentType="text/html",
+    )
+
+
+if __name__ == "__main__":
+    username = os.environ.get("DOCKER_HUB_USERNAME")
+    password = os.environ.get("DOCKER_HUB_PASSWORD")
+    token = build_access_token(username, password)
+    tags = []
+    for repo in list_repos("pytorch", token):
+        tags.extend(list_tags(repo, token))
+    save_to_s3(tags)

.circleci/ecr_gc_docker/gc.py

@@ -0,0 +1,218 @@
+#!/usr/bin/env python3
+
+import argparse
+import boto3
+import datetime
+import pytz
+import re
+import sys
+
+
+def save_to_s3(project, data):
+    table_content = ""
+    client = boto3.client("s3")
+    for repo, tag, window, age, pushed in data:
+        table_content += "<tr><td>{repo}</td><td>{tag}</td><td>{window}</td><td>{age}</td><td>{pushed}</td></tr>".format(
+            repo=repo, tag=tag, window=window, age=age, pushed=pushed
+        )
+    html_body = """
+    <html>
+        <head>
+            <link rel="stylesheet"
+                href="https://stackpath.bootstrapcdn.com/bootstrap/4.4.1/css/bootstrap.min.css"
+                integrity="sha384-Vkoo8x4CGsO3+Hhxv8T/Q5PaXtkKtu6ug5TOeNV6gBiFeWPGFN9MuhOf23Q9Ifjh"
+                crossorigin="anonymous">
+            <link rel="stylesheet" type="text/css" href="https://cdn.datatables.net/1.10.20/css/jquery.dataTables.css">
+            <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
+            <script type="text/javascript" charset="utf8" src="https://cdn.datatables.net/1.10.20/js/jquery.dataTables.js"></script>
+            <title>{project} nightly and permanent docker image info</title>
+        </head>
+        <body>
+            <table class="table table-striped table-hover" id="docker">
+            <thead class="thead-dark">
+                <tr>
+                <th scope="col">repo</th>
+                <th scope="col">tag</th>
+                <th scope="col">keep window</th>
+                <th scope="col">age</th>
+                <th scope="col">pushed at</th>
+                </tr>
+            </thead>
+            <tbody>
+                {table_content}
+            </tbody>
+            </table>
+        </body>
+        <script>
+            $(document).ready( function () {{
+                $('#docker').DataTable({{paging: false}});
+            }} );
+        </script>
+    </html>
+    """.format(
+        project=project, table_content=table_content
+    )
+
+    # for pytorch, file can be found at
+    # http://ossci-docker.s3-website.us-east-1.amazonaws.com/pytorch.html
+    # and later one we can config docker.pytorch.org to point to the location
+
+    client.put_object(
+        Bucket="docker.pytorch.org",
+        ACL="public-read",
+        Key="{project}.html".format(project=project),
+        Body=html_body,
+        ContentType="text/html",
+    )
+
+
+def repos(client):
+    paginator = client.get_paginator("describe_repositories")
+    pages = paginator.paginate(registryId="308535385114")
+    for page in pages:
+        for repo in page["repositories"]:
+            yield repo
+
+
+def images(client, repository):
+    paginator = client.get_paginator("describe_images")
+    pages = paginator.paginate(
+        registryId="308535385114", repositoryName=repository["repositoryName"]
+    )
+    for page in pages:
+        for image in page["imageDetails"]:
+            yield image
+
+
+parser = argparse.ArgumentParser(description="Delete old Docker tags from registry")
+parser.add_argument(
+    "--dry-run", action="store_true", help="Dry run; print tags that would be deleted"
+)
+parser.add_argument(
+    "--debug", action="store_true", help="Debug, print ignored / saved tags"
+)
+parser.add_argument(
+    "--keep-stable-days",
+    type=int,
+    default=14,
+    help="Days of stable Docker tags to keep (non per-build images)",
+)
+parser.add_argument(
+    "--keep-unstable-days",
+    type=int,
+    default=1,
+    help="Days of unstable Docker tags to keep (per-build images)",
+)
+parser.add_argument(
+    "--filter-prefix",
+    type=str,
+    default="",
+    help="Only run cleanup for repositories with this prefix",
+)
+parser.add_argument(
+    "--ignore-tags",
+    type=str,
+    default="",
+    help="Never cleanup these tags (comma separated)",
+)
+args = parser.parse_args()
+
+if not args.ignore_tags or not args.filter_prefix:
+    print(
+        """
+Missing required arguments --ignore-tags and --filter-prefix
+
+You must specify --ignore-tags and --filter-prefix to avoid accidentally
+pruning a stable Docker tag which is being actively used.  This will
+make you VERY SAD.  So pay attention.
+
+First, which filter-prefix do you want?  The list of valid prefixes
+is in jobs/private.groovy under the 'docker-registry-cleanup' job.
+You probably want either pytorch or caffe2.
+
+Second, which ignore-tags do you want?  It should be whatever the most
+up-to-date DockerVersion for the repository in question is.  Follow
+the imports of jobs/pytorch.groovy to find them.
+"""
+    )
+    sys.exit(1)
+
+client = boto3.client("ecr", region_name="us-east-1")
+stable_window = datetime.timedelta(days=args.keep_stable_days)
+unstable_window = datetime.timedelta(days=args.keep_unstable_days)
+now = datetime.datetime.now(pytz.UTC)
+ignore_tags = args.ignore_tags.split(",")
+
+
+def chunks(chunkable, n):
+    """ Yield successive n-sized chunks from l.
+    """
+    for i in range(0, len(chunkable), n):
+        yield chunkable[i: i + n]
+
+
+SHA_PATTERN = re.compile(r'^[0-9a-f]{40}$')
+
+
+def looks_like_git_sha(tag):
+    """Returns a boolean to check if a tag looks like a git sha
+
+    For reference a sha1 is 40 characters with only 0-9a-f and contains no
+    "-" characters
+    """
+    return re.match(SHA_PATTERN, tag) is not None
+
+
+stable_window_tags = []
+for repo in repos(client):
+    repositoryName = repo["repositoryName"]
+    if not repositoryName.startswith(args.filter_prefix):
+        continue
+
+    # Keep list of image digests to delete for this repository
+    digest_to_delete = []
+
+    for image in images(client, repo):
+        tags = image.get("imageTags")
+        if not isinstance(tags, (list,)) or len(tags) == 0:
+            continue
+        created = image["imagePushedAt"]
+        age = now - created
+        for tag in tags:
+            if any([
+                    looks_like_git_sha(tag),
+                    tag.isdigit(),
+                    tag.count("-") == 4,  # TODO: Remove, this no longer applies as tags are now built using a SHA1
+                    tag in ignore_tags]):
+                window = stable_window
+                if tag in ignore_tags:
+                    stable_window_tags.append((repositoryName, tag, "", age, created))
+                elif age < window:
+                    stable_window_tags.append((repositoryName, tag, window, age, created))
+            else:
+                window = unstable_window
+
+            if tag in ignore_tags or age < window:
+                if args.debug:
+                    print("Ignoring {}:{} (age: {})".format(repositoryName, tag, age))
+                break
+        else:
+            for tag in tags:
+                print("{}Deleting {}:{} (age: {})".format("(dry run) " if args.dry_run else "", repositoryName, tag, age))
+            digest_to_delete.append(image["imageDigest"])
+    if args.dry_run:
+        if args.debug:
+            print("Skipping actual deletion, moving on...")
+    else:
+        # Issue batch delete for all images to delete for this repository
+        # Note that as of 2018-07-25, the maximum number of images you can
+        # delete in a single batch is 100, so chunk our list into batches of
+        # 100
+        for c in chunks(digest_to_delete, 100):
+            client.batch_delete_image(
+                registryId="308535385114",
+                repositoryName=repositoryName,
+                imageIds=[{"imageDigest": digest} for digest in c],
+            )
+
+        save_to_s3(args.filter_prefix, stable_window_tags)

.circleci/ecr_gc_docker/requirements.txt

@@ -0,0 +1,3 @@
+boto3
+pytz
+requests

.circleci/generate_config_yml.py

@@ -10,11 +10,18 @@ import shutil
 import sys
 from collections import namedtuple
 
+import cimodel.data.binary_build_definitions as binary_build_definitions
+import cimodel.data.pytorch_build_definitions as pytorch_build_definitions
+import cimodel.data.simple.android_definitions
+import cimodel.data.simple.binary_smoketest
 import cimodel.data.simple.docker_definitions
+import cimodel.data.simple.ios_definitions
+import cimodel.data.simple.macos_definitions
 import cimodel.data.simple.mobile_definitions
+import cimodel.data.simple.nightly_android
 import cimodel.data.simple.nightly_ios
 import cimodel.data.simple.anaconda_prune_defintions
-import cimodel.data.simple.ios_definitions
+import cimodel.data.windows_build_definitions as windows_build_definitions
 import cimodel.lib.miniutils as miniutils
 import cimodel.lib.miniyaml as miniyaml
 
@@ -71,22 +78,20 @@ class Header(object):
         for line in filter(None, lines):
             output_filehandle.write(line + "\n")
 
-
-def _for_all_items(items, functor) -> None:
-    if isinstance(items, list):
-        for item in items:
-            _for_all_items(item, functor)
-    if isinstance(items, dict) and len(items) == 1:
-        item_type, item = next(iter(items.items()))
-        functor(item_type, item)
-
-
 def filter_master_only_jobs(items):
-    def _is_main_or_master_item(item):
+    def _for_all_items(items, functor) -> None:
+        if isinstance(items, list):
+            for item in items:
+                _for_all_items(item, functor)
+        if isinstance(items, dict) and len(items) == 1:
+            item_type, item = next(iter(items.items()))
+            functor(item_type, item)
+
+    def _is_master_item(item):
         filters = item.get('filters', None)
         branches = filters.get('branches', None) if filters is not None else None
         branches_only = branches.get('only', None) if branches is not None else None
-        return ('main' in branches_only or 'master' in branches_only) if branches_only is not None else False
+        return 'master' in branches_only if branches_only is not None else False
 
     master_deps = set()
 
@@ -95,7 +100,7 @@ def filter_master_only_jobs(items):
         item_name = item.get("name", None)
         if not isinstance(requires, list):
             return
-        if _is_main_or_master_item(item) or item_name in master_deps:
+        if _is_master_item(item) or item_name in master_deps:
             master_deps.update([n.strip('"') for n in requires])
 
     def _do_filtering(items):
@@ -106,7 +111,7 @@ def filter_master_only_jobs(items):
         item_type, item = next(iter(items.items()))
         item_name = item.get("name", None)
         item_name = item_name.strip('"') if item_name is not None else None
-        if not _is_main_or_master_item(item) and item_name not in master_deps:
+        if not _is_master_item(item) and item_name not in master_deps:
             return None
         if 'filters' in item:
             item = item.copy()
@@ -114,58 +119,62 @@ def filter_master_only_jobs(items):
         return {item_type: item}
 
     # Scan of dependencies twice to pick up nested required jobs
-    # I.e. jobs depending on jobs that main-only job depend on
+    # I.e. jobs depending on jobs that master-only job depend on
     _for_all_items(items, _save_requires_if_master)
     _for_all_items(items, _save_requires_if_master)
     return _do_filtering(items)
 
 
-def generate_required_docker_images(items):
-    required_docker_images = set()
-
-    def _requires_docker_image(item_type, item):
-        requires = item.get('requires', None)
-        if not isinstance(requires, list):
-            return
-        for requirement in requires:
-            requirement = requirement.replace('"', '')
-            if requirement.startswith('docker-'):
-                required_docker_images.add(requirement)
-
-    _for_all_items(items, _requires_docker_image)
-    return required_docker_images
-
-
 def gen_build_workflows_tree():
     build_workflows_functions = [
-        cimodel.data.simple.mobile_definitions.get_workflow_jobs,
-        cimodel.data.simple.nightly_ios.get_workflow_jobs,
-        cimodel.data.simple.anaconda_prune_defintions.get_workflow_jobs,
+        cimodel.data.simple.docker_definitions.get_workflow_jobs,
+        pytorch_build_definitions.get_workflow_jobs,
+        cimodel.data.simple.macos_definitions.get_workflow_jobs,
+        cimodel.data.simple.android_definitions.get_workflow_jobs,
         cimodel.data.simple.ios_definitions.get_workflow_jobs,
+        cimodel.data.simple.mobile_definitions.get_workflow_jobs,
+        cimodel.data.simple.binary_smoketest.get_workflow_jobs,
+        cimodel.data.simple.nightly_ios.get_workflow_jobs,
+        cimodel.data.simple.nightly_android.get_workflow_jobs,
+        cimodel.data.simple.anaconda_prune_defintions.get_workflow_jobs,
+        windows_build_definitions.get_windows_workflows,
+        binary_build_definitions.get_post_upload_jobs,
+        binary_build_definitions.get_binary_smoke_test_jobs,
     ]
     build_jobs = [f() for f in build_workflows_functions]
-    build_jobs.extend(
-        cimodel.data.simple.docker_definitions.get_workflow_jobs(
-            # sort for consistency
-            sorted(generate_required_docker_images(build_jobs))
-        )
-    )
     master_build_jobs = filter_master_only_jobs(build_jobs)
 
-    rc = {
+    binary_build_functions = [
+        binary_build_definitions.get_binary_build_jobs,
+        binary_build_definitions.get_nightly_tests,
+        binary_build_definitions.get_nightly_uploads,
+    ]
+
+    slow_gradcheck_jobs = [
+        pytorch_build_definitions.get_workflow_jobs,
+        cimodel.data.simple.docker_definitions.get_workflow_jobs,
+    ]
+
+    return {
         "workflows": {
+            "binary_builds": {
+                "when": r"<< pipeline.parameters.run_binary_tests >>",
+                "jobs": [f() for f in binary_build_functions],
+            },
             "build": {
                 "when": r"<< pipeline.parameters.run_build >>",
                 "jobs": build_jobs,
             },
+            "master_build": {
+                "when": r"<< pipeline.parameters.run_master_build >>",
+                "jobs": master_build_jobs,
+            },
+            "slow_gradcheck_build": {
+                "when": r"<< pipeline.parameters.run_slow_gradcheck_build >>",
+                "jobs": [f(only_slow_gradcheck=True) for f in slow_gradcheck_jobs],
+            },
         }
     }
-    if len(master_build_jobs) > 0:
-        rc["workflows"]["master_build"] = {
-            "when": r"<< pipeline.parameters.run_master_build >>",
-            "jobs": master_build_jobs,
-        }
-    return rc
 
 
 # Order of this list matters to the generated config.yml.
@@ -176,14 +185,20 @@ YAML_SOURCES = [
     Header("Build parameters"),
     File("build-parameters/pytorch-build-params.yml"),
     File("build-parameters/binary-build-params.yml"),
+    File("build-parameters/promote-build-params.yml"),
     Header("Job specs"),
+    File("job-specs/pytorch-job-specs.yml"),
     File("job-specs/binary-job-specs.yml"),
     File("job-specs/job-specs-custom.yml"),
+    File("job-specs/job-specs-promote.yml"),
     File("job-specs/binary_update_htmls.yml"),
     File("job-specs/binary-build-tests.yml"),
     File("job-specs/docker_jobs.yml"),
     Header("Workflows"),
     Treegen(gen_build_workflows_tree, 0),
+    File("workflows/workflows-scheduled-ci.yml"),
+    File("workflows/workflows-ecr-gc.yml"),
+    File("workflows/workflows-promote.yml"),
 ]
 
 

.circleci/scripts/binary_checkout.sh

@@ -49,9 +49,8 @@ if [[ -n "${CIRCLE_PR_NUMBER:-}" ]]; then
   git reset --hard "$CIRCLE_SHA1"
 elif [[ -n "${CIRCLE_SHA1:-}" ]]; then
   # Scheduled workflows & "smoke" binary build on master on PR merges
-  DEFAULT_BRANCH="$(git remote show $CIRCLE_REPOSITORY_URL | awk '/HEAD branch/ {print $NF}')"
   git reset --hard "$CIRCLE_SHA1"
-  git checkout -q -B $DEFAULT_BRANCH
+  git checkout -q -B master
 else
   echo "Can't tell what to checkout"
   exit 1
@@ -62,7 +61,7 @@ git --no-pager log --max-count 1
 popd
 
 # Clone the Builder master repo
-retry git clone -q https://github.com/pytorch/builder.git "$BUILDER_ROOT"
+retry git clone -q https://github.com/pytorch/builder.git -b release/1.10 "$BUILDER_ROOT"
 pushd "$BUILDER_ROOT"
 echo "Using builder from "
 git --no-pager log --max-count 1

.circleci/scripts/binary_install_miniconda.sh

@@ -31,9 +31,9 @@ fi
 
 conda_sh="$workdir/install_miniconda.sh"
 if [[ "$(uname)" == Darwin ]]; then
-  curl --retry 3 --retry-all-errors -o "$conda_sh" https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
+  curl --retry 3 -o "$conda_sh" https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
 else
-  curl --retry 3 --retry-all-errors -o "$conda_sh" https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
+  curl --retry 3 -o "$conda_sh" https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
 fi
 chmod +x "$conda_sh"
 "$conda_sh" -b -p "$MINICONDA_ROOT"

.circleci/scripts/binary_ios_test.sh

@@ -1,19 +1,30 @@
 #!/bin/bash
 set -ex -o pipefail
 
-if ! [ "$IOS_PLATFORM" == "SIMULATOR" ]; then
-    exit 0
-fi
-
 echo ""
 echo "DIR: $(pwd)"
 PROJ_ROOT=/Users/distiller/project
 cd ${PROJ_ROOT}/ios/TestApp
 # install fastlane
 sudo gem install bundler && bundle install
+# install certificates
+echo "${IOS_CERT_KEY_2022}" >> cert.txt
+base64 --decode cert.txt -o Certificates.p12
+rm cert.txt
+bundle exec fastlane install_root_cert
+bundle exec fastlane install_dev_cert
+# install the provisioning profile
+PROFILE=PyTorch_CI_2022.mobileprovision
+PROVISIONING_PROFILES=~/Library/MobileDevice/Provisioning\ Profiles
+mkdir -pv "${PROVISIONING_PROFILES}"
+cd "${PROVISIONING_PROFILES}"
+echo "${IOS_SIGN_KEY_2022}" >> cert.txt
+base64 --decode cert.txt -o ${PROFILE}
+rm cert.txt
 # run the ruby build script
 if ! [ -x "$(command -v xcodebuild)" ]; then
     echo 'Error: xcodebuild is not installed.'
     exit 1
 fi
-ruby ${PROJ_ROOT}/scripts/xcode_build.rb -i ${PROJ_ROOT}/build_ios/install -x ${PROJ_ROOT}/ios/TestApp/TestApp.xcodeproj -p ${IOS_PLATFORM}
+PROFILE=PyTorch_CI_2022
+ruby ${PROJ_ROOT}/scripts/xcode_build.rb -i ${PROJ_ROOT}/build_ios/install -x ${PROJ_ROOT}/ios/TestApp/TestApp.xcodeproj -p ${IOS_PLATFORM} -c ${PROFILE} -t ${IOS_DEV_TEAM_ID} -f Accelerate,MetalPerformanceShaders,CoreML

.circleci/scripts/binary_ios_upload.sh

@@ -23,23 +23,14 @@ do
     fi
 done
 lipo -i ${ZIP_DIR}/install/lib/*.a
-echo "BUILD_LITE_INTERPRETER: ${BUILD_LITE_INTERPRETER}"
 # copy the umbrella header and license
-if [ "${BUILD_LITE_INTERPRETER}" == "1" ]; then
-    cp ${PROJ_ROOT}/ios/LibTorch-Lite.h ${ZIP_DIR}/src/
-else
-    cp ${PROJ_ROOT}/ios/LibTorch.h ${ZIP_DIR}/src/
-fi
+cp ${PROJ_ROOT}/ios/LibTorch-Lite.h ${ZIP_DIR}/src/
 cp ${PROJ_ROOT}/LICENSE ${ZIP_DIR}/
 # zip the library
 export DATE="$(date -u +%Y%m%d)"
-export IOS_NIGHTLY_BUILD_VERSION="1.14.0.${DATE}"
-if [ "${BUILD_LITE_INTERPRETER}" == "1" ]; then
-    # libtorch_lite_ios_nightly_1.11.0.20210810.zip
-    ZIPFILE="libtorch_lite_ios_nightly_${IOS_NIGHTLY_BUILD_VERSION}.zip"
-else
-    ZIPFILE="libtorch_ios_nightly_build.zip"
-fi
+export IOS_NIGHTLY_BUILD_VERSION="1.10.0.${DATE}"
+# libtorch_lite_ios_nightly_1.10.0.20210810.zip
+ZIPFILE="libtorch_lite_ios_nightly_${IOS_NIGHTLY_BUILD_VERSION}.zip"
 cd ${ZIP_DIR}
 #for testing
 touch version.txt
@@ -61,15 +52,13 @@ set +x
 # echo "AWS SECRET: ${AWS_SECRET_ACCESS_KEY}"
 aws s3 cp ${ZIPFILE} s3://ossci-ios-build/ --acl public-read
 
-if [ "${BUILD_LITE_INTERPRETER}" == "1" ]; then
-    # create a new LibTorch-Lite-Nightly.podspec from the template
-    echo "cp ${PROJ_ROOT}/ios/LibTorch-Lite-Nightly.podspec.template ${PROJ_ROOT}/ios/LibTorch-Lite-Nightly.podspec"
-    cp ${PROJ_ROOT}/ios/LibTorch-Lite-Nightly.podspec.template ${PROJ_ROOT}/ios/LibTorch-Lite-Nightly.podspec
+# create a new LibTorch-Lite-Nightly.podspec from the template
+echo "cp ${PROJ_ROOT}/ios/LibTorch-Lite-Nightly.podspec.template ${PROJ_ROOT}/ios/LibTorch-Lite-Nightly.podspec"
+cp ${PROJ_ROOT}/ios/LibTorch-Lite-Nightly.podspec.template ${PROJ_ROOT}/ios/LibTorch-Lite-Nightly.podspec
 
-    # update pod version
-    sed -i '' -e "s/IOS_NIGHTLY_BUILD_VERSION/${IOS_NIGHTLY_BUILD_VERSION}/g" ${PROJ_ROOT}/ios/LibTorch-Lite-Nightly.podspec
-    cat ${PROJ_ROOT}/ios/LibTorch-Lite-Nightly.podspec
+# update pod version
+sed -i '' -e "s/IOS_NIGHTLY_BUILD_VERSION/${IOS_NIGHTLY_BUILD_VERSION}/g" ${PROJ_ROOT}/ios/LibTorch-Lite-Nightly.podspec
+cat ${PROJ_ROOT}/ios/LibTorch-Lite-Nightly.podspec
 
-    # push the new LibTorch-Lite-Nightly.podspec to CocoaPods
-    pod trunk push --verbose --allow-warnings --use-libraries --skip-import-validation ${PROJ_ROOT}/ios/LibTorch-Lite-Nightly.podspec
-fi
+# push the new LibTorch-Lite-Nightly.podspec to CocoaPods
+pod trunk push --verbose --allow-warnings --use-libraries --skip-import-validation ${PROJ_ROOT}/ios/LibTorch-Lite-Nightly.podspec

.circleci/scripts/binary_linux_build.sh

@@ -11,7 +11,7 @@ NUM_CPUS=$(( $(nproc) - 2 ))
 # Defaults here for **binary** linux builds so they can be changed in one place
 export MAX_JOBS=${MAX_JOBS:-$(( ${NUM_CPUS} > ${MEMORY_LIMIT_MAX_JOBS} ? ${MEMORY_LIMIT_MAX_JOBS} : ${NUM_CPUS} ))}
 
-if [[ "${DESIRED_CUDA}" =~ cu11[0-9] ]]; then
+if [[ "${DESIRED_CUDA}" == "cu111" || "${DESIRED_CUDA}" == "cu113" ]]; then
   export BUILD_SPLIT_CUDA="ON"
 fi
 
@@ -26,7 +26,7 @@ else
   build_script='manywheel/build.sh'
 fi
 
-if [[ "$CIRCLE_BRANCH" == "main" ]] || [[ "$CIRCLE_BRANCH" == "master" ]] || [[ "$CIRCLE_BRANCH" == release/* ]]; then
+if [[ "$CIRCLE_BRANCH" == "master" ]] || [[ "$CIRCLE_BRANCH" == release/* ]]; then
   export BUILD_DEBUG_INFO=1
 fi
 

.circleci/scripts/binary_linux_test.sh

@@ -1,24 +1,10 @@
 #!/bin/bash
 
-OUTPUT_SCRIPT=${OUTPUT_SCRIPT:-/home/circleci/project/ci_test_script.sh}
-
-# only source if file exists
-if [[ -f /home/circleci/project/env ]]; then
-  source /home/circleci/project/env
-fi
-cat >"${OUTPUT_SCRIPT}" <<EOL
+source /home/circleci/project/env
+cat >/home/circleci/project/ci_test_script.sh <<EOL
 # =================== The following code will be executed inside Docker container ===================
 set -eux -o pipefail
 
-retry () {
-    "\$@"  || (sleep 1 && "\$@") || (sleep 2 && "\$@")
-}
-
-# Source binary env file here if exists
-if [[ -e "${BINARY_ENV_FILE:-/nofile}" ]]; then
-  source "${BINARY_ENV_FILE:-/nofile}"
-fi
-
 python_nodot="\$(echo $DESIRED_PYTHON | tr -d m.u)"
 
 # Set up Python
@@ -37,23 +23,16 @@ fi
 
 EXTRA_CONDA_FLAGS=""
 NUMPY_PIN=""
-PROTOBUF_PACKAGE="defaults::protobuf"
-if [[ "\$python_nodot" = *310* ]]; then
-  EXTRA_CONDA_FLAGS="-c=conda-forge"
-  # There's an issue with conda channel priority where it'll randomly pick 1.19 over 1.20
-  # we set a lower boundary here just to be safe
-  NUMPY_PIN=">=1.21.2"
-  PROTOBUF_PACKAGE="protobuf>=3.19.0"
-fi
-
-if [[ "\$python_nodot" = *39*  ]]; then
+if [[ "\$python_nodot" = *39* ]]; then
   EXTRA_CONDA_FLAGS="-c=conda-forge"
   # There's an issue with conda channel priority where it'll randomly pick 1.19 over 1.20
   # we set a lower boundary here just to be safe
   NUMPY_PIN=">=1.20"
 fi
 
-
+if [[ "$DESIRED_CUDA" == "cu112" ]]; then
+  EXTRA_CONDA_FLAGS="-c=conda-forge"
+fi
 
 # Move debug wheels out of the the package dir so they don't get installed
 mkdir -p /tmp/debug_final_pkgs
@@ -65,8 +44,7 @@ mv /final_pkgs/debug-*.zip /tmp/debug_final_pkgs || echo "no debug packages to m
 # TODO there is duplicated and inconsistent test-python-env setup across this
 #   file, builder/smoke_test.sh, and builder/run_tests.sh, and also in the
 #   conda build scripts themselves. These should really be consolidated
-# Pick only one package of multiple available (which happens as result of workflow re-runs)
-pkg="/final_pkgs/\$(ls -1 /final_pkgs|sort|tail -1)"
+pkg="/final_pkgs/\$(ls /final_pkgs)"
 if [[ "$PACKAGE_TYPE" == conda ]]; then
   (
     # For some reason conda likes to re-activate the conda environment when attempting this install
@@ -81,24 +59,23 @@ if [[ "$PACKAGE_TYPE" == conda ]]; then
       ninja \
       dataclasses \
       typing-extensions \
-      ${PROTOBUF_PACKAGE} \
+      defaults::protobuf \
       six
     if [[ "$DESIRED_CUDA" == 'cpu' ]]; then
       retry conda install -c pytorch -y cpuonly
     else
-
-      cu_ver="${DESIRED_CUDA:2:2}.${DESIRED_CUDA:4}"
-      CUDA_PACKAGE="cudatoolkit"
-      if [[ "$DESIRED_CUDA" == "cu116" || "$DESIRED_CUDA" == "cu117" ]]; then
-        CUDA_PACKAGE="cuda"
+      # DESIRED_CUDA is in format cu90 or cu102
+      if [[ "${#DESIRED_CUDA}" == 4 ]]; then
+        cu_ver="${DESIRED_CUDA:2:1}.${DESIRED_CUDA:3}"
+      else
+        cu_ver="${DESIRED_CUDA:2:2}.${DESIRED_CUDA:4}"
       fi
-
-      retry conda install \${EXTRA_CONDA_FLAGS} -yq -c nvidia -c pytorch "\${CUDA_PACKAGE}=\${cu_ver}"
+      retry conda install \${EXTRA_CONDA_FLAGS} -yq -c nvidia -c pytorch "cudatoolkit=\${cu_ver}"
     fi
     conda install \${EXTRA_CONDA_FLAGS} -y "\$pkg" --offline
   )
 elif [[ "$PACKAGE_TYPE" != libtorch ]]; then
-  pip install "\$pkg" --extra-index-url "https://download.pytorch.org/whl/nightly/${DESIRED_CUDA}"
+  pip install "\$pkg"
   retry pip install -q future numpy protobuf typing-extensions six
 fi
 if [[ "$PACKAGE_TYPE" == libtorch ]]; then
@@ -115,4 +92,4 @@ EOL
 echo
 echo
 echo "The script that will run in the next step is:"
-cat "${OUTPUT_SCRIPT}"
+cat /home/circleci/project/ci_test_script.sh

.circleci/scripts/binary_macos_build.sh

@@ -1,19 +1,28 @@
 #!/bin/bash
 set -eux -o pipefail
 
-source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
+source "/Users/distiller/project/env"
 mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR"
 
-if [[ -z "${GITHUB_ACTIONS:-}" ]]; then
-  export PATH="${workdir:-${HOME}}/miniconda/bin:${PATH}"
-fi
+# For some reason `unbuffer` breaks if we change the PATH here, so we
+# write a script with the PATH change in it and unbuffer the whole
+# thing
+build_script="$workdir/build_script.sh"
+touch "$build_script"
+chmod +x "$build_script"
 
 # Build
-export USE_PYTORCH_METAL_EXPORT=1
-export USE_COREML_DELEGATE=1
+cat >"$build_script" <<EOL
+export PATH="$workdir/miniconda/bin:$PATH"
+if [[ "$CIRCLE_BRANCH" == "nightly" ]]; then
+  export USE_PYTORCH_METAL_EXPORT=1
+  export USE_COREML_DELEGATE=1
+fi
 if [[ "$PACKAGE_TYPE" == conda ]]; then
-  "${BUILDER_ROOT}/conda/build_pytorch.sh"
+  "$workdir/builder/conda/build_pytorch.sh"
 else
   export TORCH_PACKAGE_NAME="$(echo $TORCH_PACKAGE_NAME | tr '-' '_')"
-  "${BUILDER_ROOT}/wheel/build_wheel.sh"
+  "$workdir/builder/wheel/build_wheel.sh"
 fi
+EOL
+unbuffer "$build_script" | ts

.circleci/scripts/binary_populate_env.sh

@@ -5,32 +5,53 @@ export TZ=UTC
 tagged_version() {
   # Grabs version from either the env variable CIRCLE_TAG
   # or the pytorch git described version
-  if [[ "$OSTYPE" == "msys" &&  -z "${GITHUB_ACTIONS:-}" ]]; then
-    GIT_DIR="${workdir}/p/.git"
+  if [[ "$OSTYPE" == "msys" ]]; then
+    GIT_DESCRIBE="git --git-dir ${workdir}/p/.git describe"
   else
-    GIT_DIR="${workdir}/pytorch/.git"
+    GIT_DESCRIBE="git --git-dir ${workdir}/pytorch/.git describe"
   fi
-  GIT_DESCRIBE="git --git-dir ${GIT_DIR} describe --tags --match v[0-9]*.[0-9]*.[0-9]*"
   if [[ -n "${CIRCLE_TAG:-}" ]]; then
     echo "${CIRCLE_TAG}"
-  elif [[ ! -d "${GIT_DIR}" ]]; then
-    echo "Abort, abort! Git dir ${GIT_DIR} does not exists!"
-    kill $$
-  elif ${GIT_DESCRIBE} --exact >/dev/null; then
-    ${GIT_DESCRIBE}
+  elif ${GIT_DESCRIBE} --exact --tags >/dev/null; then
+    ${GIT_DESCRIBE} --tags
   else
     return 1
   fi
 }
 
-envfile=${BINARY_ENV_FILE:-/tmp/env}
-if [[ -n "${PYTORCH_ROOT}"  ]]; then
-  workdir=$(dirname "${PYTORCH_ROOT}")
+# We need to write an envfile to persist these variables to following
+# steps, but the location of the envfile depends on the circleci executor
+if [[ "$(uname)" == Darwin ]]; then
+  # macos executor (builds and tests)
+  workdir="/Users/distiller/project"
+elif [[ "$OSTYPE" == "msys" ]]; then
+  # windows executor (builds and tests)
+  workdir="/c/w"
+elif [[ -d "/home/circleci/project" ]]; then
+  # machine executor (binary tests)
+  workdir="/home/circleci/project"
 else
   # docker executor (binary builds)
   workdir="/"
 fi
+envfile="$workdir/env"
+touch "$envfile"
+chmod +x "$envfile"
 
+# Parse the BUILD_ENVIRONMENT to package type, python, and cuda
+configs=($BUILD_ENVIRONMENT)
+export PACKAGE_TYPE="${configs[0]}"
+export DESIRED_PYTHON="${configs[1]}"
+export DESIRED_CUDA="${configs[2]}"
+if [[ "${BUILD_FOR_SYSTEM:-}" == "windows" ]]; then
+  export DESIRED_DEVTOOLSET=""
+  export LIBTORCH_CONFIG="${configs[3]:-}"
+  if [[ "$LIBTORCH_CONFIG" == 'debug' ]]; then
+    export DEBUG=1
+  fi
+else
+  export DESIRED_DEVTOOLSET="${configs[3]:-}"
+fi
 if [[ "$PACKAGE_TYPE" == 'libtorch' ]]; then
   export BUILD_PYTHONLESS=1
 fi
@@ -53,13 +74,18 @@ if [[ ${DESIRED_CUDA} == "cpu" ]]; then
   USE_GOLD_LINKER="ON"
 fi
 
+USE_WHOLE_CUDNN="OFF"
+# Link whole cuDNN for CUDA-11.1 to include fp16 fast kernels
+if [[  "$(uname)" == "Linux" && "${DESIRED_CUDA}" == "cu111" ]]; then
+  USE_WHOLE_CUDNN="ON"
+fi
 
 # Default to nightly, since that's where this normally uploads to
 PIP_UPLOAD_FOLDER='nightly/'
 # We put this here so that OVERRIDE_PACKAGE_VERSION below can read from it
 export DATE="$(date -u +%Y%m%d)"
 #TODO: We should be pulling semver version from the base version.txt
-BASE_BUILD_VERSION="1.14.0.dev$DATE"
+BASE_BUILD_VERSION="1.10.0.dev$DATE"
 # Change BASE_BUILD_VERSION to git tag when on a git tag
 # Use 'git -C' to make doubly sure we're in the correct directory for checking
 # the git tag
@@ -76,11 +102,6 @@ if [[ "$(uname)" == 'Darwin' ]] || [[ "$PACKAGE_TYPE" == conda ]]; then
 else
   export PYTORCH_BUILD_VERSION="${BASE_BUILD_VERSION}+$DESIRED_CUDA"
 fi
-
-if [[ -n "${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:-}" ]]; then
-  export PYTORCH_BUILD_VERSION="${PYTORCH_BUILD_VERSION}-with-pypi-cudnn"
-fi
-
 export PYTORCH_BUILD_NUMBER=1
 
 
@@ -110,28 +131,24 @@ if [[ "$PACKAGE_TYPE" == libtorch ]]; then
   fi
 fi
 
-cat >"$envfile" <<EOL
+cat >>"$envfile" <<EOL
 # =================== The following code will be executed inside Docker container ===================
 export TZ=UTC
 echo "Running on $(uname -a) at $(date)"
 
 export PACKAGE_TYPE="$PACKAGE_TYPE"
-export DESIRED_PYTHON="${DESIRED_PYTHON:-}"
+export DESIRED_PYTHON="$DESIRED_PYTHON"
 export DESIRED_CUDA="$DESIRED_CUDA"
 export LIBTORCH_VARIANT="${LIBTORCH_VARIANT:-}"
 export BUILD_PYTHONLESS="${BUILD_PYTHONLESS:-}"
-if [[ "${OSTYPE}" == "msys" ]]; then
+export DESIRED_DEVTOOLSET="$DESIRED_DEVTOOLSET"
+if [[ "${BUILD_FOR_SYSTEM:-}" == "windows" ]]; then
   export LIBTORCH_CONFIG="${LIBTORCH_CONFIG:-}"
-  if [[ "${LIBTORCH_CONFIG:-}" == 'debug' ]]; then
-    export DEBUG=1
-  fi
-  export DESIRED_DEVTOOLSET=""
-else
-  export DESIRED_DEVTOOLSET="${DESIRED_DEVTOOLSET:-}"
+  export DEBUG="${DEBUG:-}"
 fi
-export PYTORCH_EXTRA_INSTALL_REQUIREMENTS="${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:-}"
+
 export DATE="$DATE"
-export NIGHTLIES_DATE_PREAMBLE=1.14.0.dev
+export NIGHTLIES_DATE_PREAMBLE=1.10.0.dev
 export PYTORCH_BUILD_VERSION="$PYTORCH_BUILD_VERSION"
 export PYTORCH_BUILD_NUMBER="$PYTORCH_BUILD_NUMBER"
 export OVERRIDE_PACKAGE_VERSION="$PYTORCH_BUILD_VERSION"
@@ -139,7 +156,6 @@ export OVERRIDE_PACKAGE_VERSION="$PYTORCH_BUILD_VERSION"
 # TODO: We don't need this anymore IIUC
 export TORCH_PACKAGE_NAME='torch'
 export TORCH_CONDA_BUILD_FOLDER='pytorch-nightly'
-export ANACONDA_USER='pytorch'
 
 export USE_FBGEMM=1
 export JAVA_HOME=$JAVA_HOME
@@ -147,48 +163,30 @@ export BUILD_JNI=$BUILD_JNI
 export PIP_UPLOAD_FOLDER="$PIP_UPLOAD_FOLDER"
 export DOCKER_IMAGE="$DOCKER_IMAGE"
 
+export workdir="$workdir"
+export MAC_PACKAGE_WORK_DIR="$workdir"
+if [[ "$OSTYPE" == "msys" ]]; then
+  export PYTORCH_ROOT="$workdir/p"
+  export BUILDER_ROOT="$workdir/b"
+else
+  export PYTORCH_ROOT="$workdir/pytorch"
+  export BUILDER_ROOT="$workdir/builder"
+fi
+export MINICONDA_ROOT="$workdir/miniconda"
+export PYTORCH_FINAL_PACKAGE_DIR="$workdir/final_pkgs"
+
+export CIRCLE_TAG="${CIRCLE_TAG:-}"
+export CIRCLE_SHA1="$CIRCLE_SHA1"
+export CIRCLE_PR_NUMBER="${CIRCLE_PR_NUMBER:-}"
+export CIRCLE_BRANCH="$CIRCLE_BRANCH"
+export CIRCLE_WORKFLOW_ID="$CIRCLE_WORKFLOW_ID"
 
 export USE_GOLD_LINKER="${USE_GOLD_LINKER}"
 export USE_GLOO_WITH_OPENSSL="ON"
+export USE_WHOLE_CUDNN="${USE_WHOLE_CUDNN}"
 # =================== The above code will be executed inside Docker container ===================
 EOL
 
-# nproc doesn't exist on darwin
-if [[ "$(uname)" != Darwin ]]; then
-  # Because most Circle executors only have 20 CPUs, using more causes OOMs w/ Ninja and nvcc parallelization
-  MEMORY_LIMIT_MAX_JOBS=18
-  NUM_CPUS=$(( $(nproc) - 2 ))
-
-  # Defaults here for **binary** linux builds so they can be changed in one place
-  export MAX_JOBS=${MAX_JOBS:-$(( ${NUM_CPUS} > ${MEMORY_LIMIT_MAX_JOBS} ? ${MEMORY_LIMIT_MAX_JOBS} : ${NUM_CPUS} ))}
-
-  cat >>"$envfile" <<EOL
-  export MAX_JOBS="${MAX_JOBS}"
-EOL
-fi
-
-if [[ -z "${GITHUB_ACTIONS:-}" ]]; then
-  cat >>"$envfile" <<EOL
-  export workdir="$workdir"
-  export MAC_PACKAGE_WORK_DIR="$workdir"
-  if [[ "$OSTYPE" == "msys" ]]; then
-    export PYTORCH_ROOT="$workdir/p"
-    export BUILDER_ROOT="$workdir/b"
-  else
-    export PYTORCH_ROOT="$workdir/pytorch"
-    export BUILDER_ROOT="$workdir/builder"
-  fi
-  export MINICONDA_ROOT="$workdir/miniconda"
-  export PYTORCH_FINAL_PACKAGE_DIR="$workdir/final_pkgs"
-
-  export CIRCLE_TAG="${CIRCLE_TAG:-}"
-  export CIRCLE_SHA1="$CIRCLE_SHA1"
-  export CIRCLE_PR_NUMBER="${CIRCLE_PR_NUMBER:-}"
-  export CIRCLE_BRANCH="$CIRCLE_BRANCH"
-  export CIRCLE_WORKFLOW_ID="$CIRCLE_WORKFLOW_ID"
-EOL
-fi
-
 echo 'retry () {' >> "$envfile"
 echo '    $*  || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)' >> "$envfile"
 echo '}' >> "$envfile"

.circleci/scripts/binary_upload.sh

@@ -14,12 +14,6 @@ UPLOAD_CHANNEL=${UPLOAD_CHANNEL:-nightly}
 UPLOAD_SUBFOLDER=${UPLOAD_SUBFOLDER:-cpu}
 UPLOAD_BUCKET="s3://pytorch"
 BACKUP_BUCKET="s3://pytorch-backup"
-BUILD_NAME=${BUILD_NAME:-}
-
-# this is temporary change to upload pypi-cudnn builds to separate folder
-if [[ ${BUILD_NAME} == *with-pypi-cudnn* ]]; then
-  UPLOAD_SUBFOLDER="${UPLOAD_SUBFOLDER}_pypi_cudnn"
-fi
 
 DRY_RUN=${DRY_RUN:-enabled}
 # Don't actually do work unless explicit
@@ -30,11 +24,6 @@ if [[ "${DRY_RUN}" = "disabled" ]]; then
   AWS_S3_CP="aws s3 cp"
 fi
 
-# Sleep 2 minutes between retries for conda upload
-retry () {
-  "$@"  || (sleep 5m && "$@") || (sleep 5m && "$@") || (sleep 5m && "$@") || (sleep 5m && "$@")
-}
-
 do_backup() {
   local backup_dir
   backup_dir=$1
@@ -48,14 +37,13 @@ do_backup() {
 conda_upload() {
   (
     set -x
-    retry \
     ${ANACONDA} \
-    upload  \
-    ${PKG_DIR}/*.tar.bz2 \
-    -u "pytorch-${UPLOAD_CHANNEL}" \
-    --label main \
-    --no-progress \
-    --force
+      upload  \
+      ${PKG_DIR}/*.tar.bz2 \
+      -u "pytorch-${UPLOAD_CHANNEL}" \
+      --label main \
+      --no-progress \
+      --force
   )
 }
 
@@ -75,10 +63,6 @@ s3_upload() {
   )
 }
 
-# Install dependencies (should be a no-op if previously installed)
-conda install -yq anaconda-client
-pip install -q awscli
-
 case "${PACKAGE_TYPE}" in
   conda)
     conda_upload

.circleci/scripts/binary_windows_build.sh

@@ -1,23 +1,21 @@
 #!/bin/bash
 set -eux -o pipefail
 
-source "${BINARY_ENV_FILE:-/c/w/env}"
+source "/c/w/env"
 mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR"
 
 export CUDA_VERSION="${DESIRED_CUDA/cu/}"
 export USE_SCCACHE=1
-export SCCACHE_BUCKET=ossci-compiler-cache
-export SCCACHE_IGNORE_SERVER_IO_ERROR=1
+export SCCACHE_BUCKET=ossci-compiler-cache-windows
+export NIGHTLIES_PYTORCH_ROOT="$PYTORCH_ROOT"
 export VC_YEAR=2019
 
-if [[ "${DESIRED_CUDA}" == *"cu11"* ]]; then
-    export BUILD_SPLIT_CUDA=ON
+if [[ "${DESIRED_CUDA}" == "cu111" || "${DESIRED_CUDA}" == "cu113" ]]; then
+    export BUILD_SPLIT_CUDA="ON"
 fi
 
-
 echo "Free Space for CUDA DEBUG BUILD"
-if [[ "${CIRCLECI:-}" == 'true' ]]; then
-    export NIGHTLIES_PYTORCH_ROOT="$PYTORCH_ROOT"
+if [[ "$CIRCLECI" == 'true' ]]; then
     if [[ -d "C:\\Program Files (x86)\\Microsoft Visual Studio\\2019\\Community" ]]; then
         rm -rf "C:\\Program Files (x86)\\Microsoft Visual Studio\\2019\\Community"
     fi
@@ -49,20 +47,23 @@ if [[ "${CIRCLECI:-}" == 'true' ]]; then
     if [[ -d "C:\\Program Files (x86)\\Google" ]]; then
         rm -rf "C:\\Program Files (x86)\\Google"
     fi
-    set +x
-    export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_SCCACHE_S3_BUCKET_V4:-}
-    export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_SCCACHE_S3_BUCKET_V4:-}
-    set -x
-    if [[ -d "C:\\ProgramData\\Microsoft\\VisualStudio\\Packages\\_Instances" ]]; then
-        mv "C:\\ProgramData\\Microsoft\\VisualStudio\\Packages\\_Instances" .
-        rm -rf "C:\\ProgramData\\Microsoft\\VisualStudio\\Packages"
-        mkdir -p "C:\\ProgramData\\Microsoft\\VisualStudio\\Packages"
-        mv _Instances "C:\\ProgramData\\Microsoft\\VisualStudio\\Packages"
-    fi
-    if [[ -d "C:\\Microsoft" ]]; then
-        # don't use quotes here
-        rm -rf /c/Microsoft/AndroidNDK*
-    fi
+fi
+
+set +x
+export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_SCCACHE_S3_BUCKET_V4:-}
+export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_SCCACHE_S3_BUCKET_V4:-}
+set -x
+
+if [[ "$CIRCLECI" == 'true' && -d "C:\\ProgramData\\Microsoft\\VisualStudio\\Packages\\_Instances" ]]; then
+  mv "C:\\ProgramData\\Microsoft\\VisualStudio\\Packages\\_Instances" .
+  rm -rf "C:\\ProgramData\\Microsoft\\VisualStudio\\Packages"
+  mkdir -p "C:\\ProgramData\\Microsoft\\VisualStudio\\Packages"
+  mv _Instances "C:\\ProgramData\\Microsoft\\VisualStudio\\Packages"
+fi
+
+if [[ "$CIRCLECI" == 'true' && -d "C:\\Microsoft" ]]; then
+  # don't use quotes here
+  rm -rf /c/Microsoft/AndroidNDK*
 fi
 
 echo "Free space on filesystem before build:"
@@ -70,10 +71,9 @@ df -h
 
 pushd "$BUILDER_ROOT"
 if [[ "$PACKAGE_TYPE" == 'conda' ]]; then
-    ./windows/internal/build_conda.bat
+  ./windows/internal/build_conda.bat
 elif [[ "$PACKAGE_TYPE" == 'wheel' || "$PACKAGE_TYPE" == 'libtorch' ]]; then
-    export NIGHTLIES_PYTORCH_ROOT="$PYTORCH_ROOT"
-    ./windows/internal/build_wheels.bat
+  ./windows/internal/build_wheels.bat
 fi
 
 echo "Free space on filesystem after build:"

.circleci/scripts/binary_windows_test.sh

@@ -1,7 +1,7 @@
 #!/bin/bash
 set -eux -o pipefail
 
-source "${BINARY_ENV_FILE:-/c/w/env}"
+source "/c/w/env"
 
 export CUDA_VERSION="${DESIRED_CUDA/cu/}"
 export VC_YEAR=2019

.circleci/scripts/build_android_gradle.sh

@@ -78,7 +78,7 @@ if [[ "${BUILD_ENVIRONMENT}" == *-gradle-build-only-x86_32* ]]; then
     GRADLE_PARAMS+=" -PABI_FILTERS=x86"
 fi
 
-if [ -n "${GRADLE_OFFLINE:-}" ]; then
+if [ -n "{GRADLE_OFFLINE:-}" ]; then
     GRADLE_PARAMS+=" --offline"
 fi
 

.circleci/scripts/cpp_doc_push_script.sh

@@ -34,9 +34,9 @@ echo "error: cpp_doc_push_script.sh: install_path (arg1) not specified"
   exit 1
 fi
 
-is_main_doc=false
+is_master_doc=false
 if [ "$version" == "master" ]; then
-  is_main_doc=true
+  is_master_doc=true
 fi
 
 echo "install_path: $install_path  version: $version"
@@ -51,10 +51,12 @@ git clone https://github.com/pytorch/cppdocs
 
 set -ex
 
+sudo apt-get -y install doxygen
+
 # Generate ATen files
 pushd "${pt_checkout}"
 pip install -r requirements.txt
-time python -m torchgen.gen \
+time python -m tools.codegen.gen \
   -s aten/src/ATen \
   -d build/aten/src/ATen
 
@@ -63,8 +65,9 @@ cp torch/_utils_internal.py tools/shared
 
 # Generate PyTorch files
 time python tools/setup_helpers/generate_code.py \
+  --declarations-path build/aten/src/ATen/Declarations.yaml \
   --native-functions-path aten/src/ATen/native/native_functions.yaml \
-  --tags-path aten/src/ATen/native/tags.yaml
+  --nn-path aten/src/
 
 # Build the docs
 pushd docs/cpp
@@ -94,12 +97,8 @@ git status
 git config user.email "soumith+bot@pytorch.org"
 git config user.name "pytorchbot"
 # If there aren't changes, don't make a commit; push is no-op
-git commit -m "Generate C++ docs from pytorch/pytorch@${GITHUB_SHA}" || true
+git commit -m "Generate C++ docs from pytorch/pytorch@$CIRCLE_SHA1" || true
 git status
 
-if [[ "${WITH_PUSH:-}" == true ]]; then
-  git push -u origin
-fi
-
 popd
 # =================== The above code **should** be executed inside Docker container ===================

.circleci/scripts/driver_update.bat

@@ -1,5 +1,5 @@
 set "DRIVER_DOWNLOAD_LINK=https://s3.amazonaws.com/ossci-windows/452.39-data-center-tesla-desktop-win10-64bit-international.exe"
-curl --retry 3 --retry-all-errors -kL %DRIVER_DOWNLOAD_LINK% --output 452.39-data-center-tesla-desktop-win10-64bit-international.exe
+curl --retry 3 -kL %DRIVER_DOWNLOAD_LINK% --output 452.39-data-center-tesla-desktop-win10-64bit-international.exe
 if errorlevel 1 exit /b 1
 
 start /wait 452.39-data-center-tesla-desktop-win10-64bit-international.exe -s -noreboot

.circleci/scripts/functorch_doc_push_script.sh

@@ -1,47 +0,0 @@
-#!/bin/bash
-# =================== The following code **should** be executed inside Docker container ===================
-
-# Install dependencies
-sudo apt-get -y update
-sudo apt-get -y install expect-dev
-
-# This is where the local pytorch install in the docker image is located
-pt_checkout="/var/lib/jenkins/workspace"
-source "$pt_checkout/.jenkins/pytorch/common_utils.sh"
-echo "functorch_doc_push_script.sh: Invoked with $*"
-
-set -ex
-
-version=${DOCS_VERSION:-nightly}
-echo "version: $version"
-
-# Build functorch docs
-pushd $pt_checkout/functorch/docs
-pip -q install -r requirements.txt
-make html
-popd
-
-git clone https://github.com/pytorch/functorch -b gh-pages --depth 1 functorch_ghpages
-pushd functorch_ghpages
-
-if [ $version == "master" ]; then
-  version=nightly
-fi
-
-git rm -rf "$version" || true
-mv "$pt_checkout/functorch/docs/build/html" "$version"
-
-git add "$version" || true
-git status
-git config user.email "soumith+bot@pytorch.org"
-git config user.name "pytorchbot"
-# If there aren't changes, don't make a commit; push is no-op
-git commit -m "Generate Python docs from pytorch/pytorch@${GITHUB_SHA}" || true
-git status
-
-if [[ "${WITH_PUSH:-}" == true ]]; then
-  git push -u origin gh-pages
-fi
-
-popd
-# =================== The above code **should** be executed inside Docker container ===================

.circleci/scripts/python_doc_push_script.sh

@@ -37,9 +37,9 @@ echo "error: python_doc_push_script.sh: install_path (arg1) not specified"
   exit 1
 fi
 
-is_main_doc=false
+is_master_doc=false
 if [ "$version" == "master" ]; then
-  is_main_doc=true
+  is_master_doc=true
 fi
 
 # Argument 3: The branch to push to. Usually is "site"
@@ -86,7 +86,7 @@ pushd docs
 
 # Build the docs
 pip -q install -r requirements.txt
-if [ "$is_main_doc" = true ]; then
+if [ "$is_master_doc" = true ]; then
   build_docs html
   [ $? -eq 0 ] || exit $?
   make coverage
@@ -131,15 +131,8 @@ git status
 git config user.email "soumith+bot@pytorch.org"
 git config user.name "pytorchbot"
 # If there aren't changes, don't make a commit; push is no-op
-git commit -m "Generate Python docs from pytorch/pytorch@${GITHUB_SHA}" || true
+git commit -m "Generate Python docs from pytorch/pytorch@$CIRCLE_SHA1" || true
 git status
 
-if [[ "${WITH_PUSH:-}" == true ]]; then
-  # push to a temp branch first to trigger CLA check and satisfy branch protections
-  git push -u origin HEAD:pytorchbot/temp-branch-py -f
-  sleep 30
-  git push -u origin "${branch}"
-fi
-
 popd
 # =================== The above code **should** be executed inside Docker container ===================

.circleci/scripts/setup_ci_environment.sh

@@ -32,7 +32,7 @@ if ! command -v aws >/dev/null; then
 fi
 
 if [ -n "${USE_CUDA_DOCKER_RUNTIME:-}" ]; then
-  DRIVER_FN="NVIDIA-Linux-x86_64-515.76.run"
+  DRIVER_FN="NVIDIA-Linux-x86_64-460.39.run"
   wget "https://s3.amazonaws.com/ossci-linux/nvidia_driver/$DRIVER_FN"
   sudo /bin/bash "$DRIVER_FN" -s --no-drm || (sudo cat /var/log/nvidia-installer.log && false)
   nvidia-smi
@@ -40,8 +40,8 @@ if [ -n "${USE_CUDA_DOCKER_RUNTIME:-}" ]; then
   # Taken directly from https://github.com/NVIDIA/nvidia-docker
   # Add the package repositories
   distribution=$(. /etc/os-release;echo "$ID$VERSION_ID")
-  curl -s -L --retry 3 --retry-all-errors https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
-  curl -s -L --retry 3 --retry-all-errors "https://nvidia.github.io/nvidia-docker/${distribution}/nvidia-docker.list" | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
+  curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
+  curl -s -L "https://nvidia.github.io/nvidia-docker/${distribution}/nvidia-docker.list" | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
 
   retry sudo apt-get update -qq
   # Necessary to get the `--gpus` flag to function within docker
@@ -66,6 +66,7 @@ add_to_env_file() {
   esac
 }
 
+add_to_env_file IN_CI 1
 add_to_env_file CI_MASTER "${CI_MASTER:-}"
 add_to_env_file COMMIT_SOURCE "${CIRCLE_BRANCH:-}"
 add_to_env_file BUILD_ENVIRONMENT "${BUILD_ENVIRONMENT}"

.circleci/scripts/setup_linux_system_environment.sh

@@ -2,7 +2,7 @@
 set -eux -o pipefail
 
 # Set up CircleCI GPG keys for apt, if needed
-curl --retry 3 --retry-all-errors -s -L https://packagecloud.io/circleci/trusty/gpgkey | sudo apt-key add -
+curl --retry 3 -s -L https://packagecloud.io/circleci/trusty/gpgkey | sudo apt-key add -
 
 # Stop background apt updates.  Hypothetically, the kill should not
 # be necessary, because stop is supposed to send a kill signal to

.circleci/scripts/trigger_azure_pipeline.py

@@ -11,7 +11,7 @@ AZURE_PIPELINE_BASE_URL = "https://aiinfra.visualstudio.com/PyTorch/"
 AZURE_DEVOPS_PAT_BASE64 = os.environ.get("AZURE_DEVOPS_PAT_BASE64_SECRET", "")
 PIPELINE_ID = "911"
 PROJECT_ID = "0628bce4-2d33-499e-bac5-530e12db160f"
-TARGET_BRANCH = os.environ.get("CIRCLE_BRANCH", "main")
+TARGET_BRANCH = os.environ.get("CIRCLE_BRANCH", "master")
 TARGET_COMMIT = os.environ.get("CIRCLE_SHA1", "")
 
 build_base_url = AZURE_PIPELINE_BASE_URL + "_apis/build/builds?api-version=6.0"

.circleci/scripts/vs_install.ps1

@@ -29,7 +29,7 @@ if (Test-Path "${env:ProgramFiles(x86)}\Microsoft Visual Studio\Installer\vswher
 }
 
 echo "Downloading VS installer from S3."
-curl.exe --retry 3 --retry-all-errors -kL $VS_DOWNLOAD_LINK --output vs_installer.exe
+curl.exe --retry 3 -kL $VS_DOWNLOAD_LINK --output vs_installer.exe
 if ($LASTEXITCODE -ne 0) {
     echo "Download of the VS 2019 Version ${env:VS_VERSION} installer failed"
     exit 1

.circleci/scripts/vs_install_cmath.ps1

@@ -1,5 +1,5 @@
 $CMATH_DOWNLOAD_LINK = "https://raw.githubusercontent.com/microsoft/STL/12c684bba78f9b032050526abdebf14f58ca26a3/stl/inc/cmath"
 $VC14_28_INSTALL_PATH="C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.28.29910\include"
 
-curl.exe --retry 3 --retry-all-errors -kL $CMATH_DOWNLOAD_LINK --output "$home\cmath"
+curl.exe --retry 3 -kL $CMATH_DOWNLOAD_LINK --output "$home\cmath"
 Move-Item -Path "$home\cmath" -Destination "$VC14_28_INSTALL_PATH" -Force

.circleci/scripts/windows_cuda_install.sh

@@ -2,23 +2,22 @@
 set -eux -o pipefail
 
 case ${CUDA_VERSION} in
+    10.1)
+        cuda_installer_name="cuda_10.1.243_426.00_win10"
+        cuda_install_packages="nvcc_10.1 cuobjdump_10.1 nvprune_10.1 cupti_10.1 cublas_10.1 cublas_dev_10.1 cudart_10.1 cufft_10.1 cufft_dev_10.1 curand_10.1 curand_dev_10.1 cusolver_10.1 cusolver_dev_10.1 cusparse_10.1 cusparse_dev_10.1 nvgraph_10.1 nvgraph_dev_10.1 npp_10.1 npp_dev_10.1 nvrtc_10.1 nvrtc_dev_10.1 nvml_dev_10.1"
+        ;;
     10.2)
         cuda_installer_name="cuda_10.2.89_441.22_win10"
         cuda_install_packages="nvcc_10.2 cuobjdump_10.2 nvprune_10.2 cupti_10.2 cublas_10.2 cublas_dev_10.2 cudart_10.2 cufft_10.2 cufft_dev_10.2 curand_10.2 curand_dev_10.2 cusolver_10.2 cusolver_dev_10.2 cusparse_10.2 cusparse_dev_10.2 nvgraph_10.2 nvgraph_dev_10.2 npp_10.2 npp_dev_10.2 nvrtc_10.2 nvrtc_dev_10.2 nvml_dev_10.2"
         ;;
+    11.1)
+        cuda_installer_name="cuda_11.1.0_456.43_win10"
+        cuda_install_packages="nvcc_11.1 cuobjdump_11.1 nvprune_11.1 nvprof_11.1 cupti_11.1 cublas_11.1 cublas_dev_11.1 cudart_11.1 cufft_11.1 cufft_dev_11.1 curand_11.1 curand_dev_11.1 cusolver_11.1 cusolver_dev_11.1 cusparse_11.1 cusparse_dev_11.1 npp_11.1 npp_dev_11.1 nvrtc_11.1 nvrtc_dev_11.1 nvml_dev_11.1"
+        ;;
     11.3)
         cuda_installer_name="cuda_11.3.0_465.89_win10"
         cuda_install_packages="thrust_11.3 nvcc_11.3 cuobjdump_11.3 nvprune_11.3 nvprof_11.3 cupti_11.3 cublas_11.3 cublas_dev_11.3 cudart_11.3 cufft_11.3 cufft_dev_11.3 curand_11.3 curand_dev_11.3 cusolver_11.3 cusolver_dev_11.3 cusparse_11.3 cusparse_dev_11.3 npp_11.3 npp_dev_11.3 nvrtc_11.3 nvrtc_dev_11.3 nvml_dev_11.3"
         ;;
-    11.6)
-        cuda_installer_name="cuda_11.6.0_511.23_windows"
-        cuda_install_packages="thrust_11.6 nvcc_11.6 cuobjdump_11.6 nvprune_11.6 nvprof_11.6 cupti_11.6 cublas_11.6 cublas_dev_11.6 cudart_11.6 cufft_11.6 cufft_dev_11.6 curand_11.6 curand_dev_11.6 cusolver_11.6 cusolver_dev_11.6 cusparse_11.6 cusparse_dev_11.6 npp_11.6 npp_dev_11.6 nvrtc_11.6 nvrtc_dev_11.6 nvml_dev_11.6"
-        ;;
-    11.7)
-        cuda_installer_name="cuda_11.7.0_516.01_windows"
-        cuda_install_packages="thrust_11.7 nvcc_11.7 cuobjdump_11.7 nvprune_11.7 nvprof_11.7 cupti_11.7 cublas_11.7 cublas_dev_11.7 cudart_11.7 cufft_11.7 cufft_dev_11.7 curand_11.7 curand_dev_11.7 cusolver_11.7 cusolver_dev_11.7 cusparse_11.7 cusparse_dev_11.7 npp_11.7 npp_dev_11.7 nvrtc_11.7 nvrtc_dev_11.7 nvml_dev_11.7"
-        ;;
-
     *)
         echo "CUDA_VERSION $CUDA_VERSION is not supported yet"
         exit 1

.circleci/scripts/windows_cudnn_install.sh

@@ -1,24 +1,23 @@
 #!/bin/bash
 set -eux -o pipefail
 
-
-windows_s3_link="https://ossci-windows.s3.amazonaws.com"
+# This is typically blank but for CUDA 10* it'll be set to 10
+windows_version_qualifier=""
 
 case ${CUDA_VERSION} in
+    10.1)
+        archive_version="v7.6.4.38"
+        windows_version_qualifier="10"
+        ;;
     10.2)
-        cudnn_file_name="cudnn-${CUDA_VERSION}-windows10-x64-v7.6.5.32"
+        archive_version="v7.6.5.32"
+        windows_version_qualifier="10"
+        ;;
+    11.1)
+        archive_version="v8.0.5.39"
         ;;
     11.3)
-        # Use cudnn8.3 with hard-coded cuda11.3 version
-        cudnn_file_name="cudnn-windows-x86_64-8.3.2.44_cuda11.5-archive"
-        ;;
-    11.6)
-        # Use cudnn8.3 with hard-coded cuda11.5 version
-        cudnn_file_name="cudnn-windows-x86_64-8.3.2.44_cuda11.5-archive"
-        ;;
-    11.7)
-        # Use cudnn8.3 with hard-coded cuda11.5 version
-        cudnn_file_name="cudnn-windows-x86_64-8.5.0.96_cuda11-archive"
+        archive_version="v8.2.0.53"
         ;;
     *)
         echo "CUDA_VERSION: ${CUDA_VERSION} not supported yet"
@@ -27,7 +26,7 @@ case ${CUDA_VERSION} in
 esac
 
 cudnn_installer_name="cudnn_installer.zip"
-cudnn_installer_link="${windows_s3_link}/${cudnn_file_name}.zip"
+cudnn_installer_link="https://ossci-windows.s3.amazonaws.com/cudnn-${CUDA_VERSION}-windows${windows_version_qualifier}-x64-${archive_version}.zip"
 cudnn_install_folder="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v${CUDA_VERSION}/"
 
 if [[ -f "${cudnn_install_folder}/include/cudnn.h" ]]; then
@@ -36,17 +35,12 @@ else
     tmp_dir=$(mktemp -d)
     (
         pushd "${tmp_dir}"
-        curl --retry 3 --retry-all-errors -o "${cudnn_installer_name}" "$cudnn_installer_link"
+        curl --retry 3 -o "${cudnn_installer_name}" "$cudnn_installer_link"
         7z x "${cudnn_installer_name}" -ocudnn
         # Use '${var:?}/*' to avoid potentially expanding to '/*'
         # Remove all of the directories before attempting to copy files
         rm -rf "${cudnn_install_folder:?}/*"
         cp -rf cudnn/cuda/* "${cudnn_install_folder}"
-
-        #Make sure windows path contains zlib dll
-        curl -k -L "${windows_s3_link}/zlib123dllx64.zip" --output "${tmp_dir}\zlib123dllx64.zip"
-        7z x "${tmp_dir}\zlib123dllx64.zip" -o"${tmp_dir}\zlib"
-        xcopy /Y "${tmp_dir}\zlib\dll_x64\*.dll" "C:\Windows\System32"
     )
     rm -rf "${tmp_dir}"
 fi

.circleci/verbatim-sources/build-parameters/binary-build-params.yml

@@ -62,4 +62,5 @@ binary_windows_params: &binary_windows_params
       default: "windows-xlarge-cpu-with-nvidia-cuda"
   environment:
     BUILD_ENVIRONMENT: << parameters.build_environment >>
+    BUILD_FOR_SYSTEM: windows
     JOB_EXECUTOR: <<parameters.executor>>

.circleci/verbatim-sources/build-parameters/promote-build-params.yml

@@ -0,0 +1,14 @@
+
+promote_common: &promote_common
+  docker:
+    - image: pytorch/release
+  parameters:
+    package_name:
+      description: "package name to promote"
+      type: string
+      default: ""
+  environment:
+    PACKAGE_NAME: << parameters.package_name >>
+    ANACONDA_API_TOKEN: ${CONDA_PYTORCHBOT_TOKEN}
+    AWS_ACCESS_KEY_ID: ${PYTORCH_BINARY_AWS_ACCESS_KEY_ID}
+    AWS_SECRET_ACCESS_KEY: ${PYTORCH_BINARY_AWS_SECRET_ACCESS_KEY}

.circleci/verbatim-sources/build-parameters/pytorch-build-params.yml

@@ -26,6 +26,24 @@ pytorch_params: &pytorch_params
     CI_MASTER: << pipeline.parameters.run_master_build >>
   resource_class: << parameters.resource_class >>
 
+pytorch_android_params: &pytorch_android_params
+  parameters:
+    build_environment:
+      type: string
+      default: ""
+    op_list:
+      type: string
+      default: ""
+    lite_interpreter:
+      type: string
+      default: "1"
+  environment:
+    BUILD_ENVIRONMENT: pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-custom-build-single
+    DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c"
+    PYTHON_VERSION: "3.6"
+    SELECTED_OP_LIST: << parameters.op_list >>
+    BUILD_LITE_INTERPRETER: << parameters.lite_interpreter >>
+
 pytorch_ios_params: &pytorch_ios_params
   parameters:
     build_environment:

.circleci/verbatim-sources/commands.yml

@@ -132,3 +132,43 @@ commands:
             else
               echo "This is not a pull request, skipping..."
             fi
+
+  upload_binary_size_for_android_build:
+    description: "Upload binary size data for Android build"
+    parameters:
+      build_type:
+        type: string
+        default: ""
+      artifacts:
+        type: string
+        default: ""
+    steps:
+      - run:
+          name: "Binary Size - Install Dependencies"
+          no_output_timeout: "5m"
+          command: |
+            retry () {
+              $* || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
+            }
+            retry pip3 install requests
+      - run:
+          name: "Binary Size - Untar Artifacts"
+          no_output_timeout: "5m"
+          command: |
+            # The artifact file is created inside docker container, which contains the result binaries.
+            # Now unpackage it into the project folder. The subsequent script will scan project folder
+            # to locate result binaries and report their sizes.
+            # If artifact file is not provided it assumes that the project folder has been mounted in
+            # the docker during build and already contains the result binaries, so this step can be skipped.
+            export ARTIFACTS="<< parameters.artifacts >>"
+            if [ -n "${ARTIFACTS}" ]; then
+              tar xf "${ARTIFACTS}" -C ~/project
+            fi
+      - run:
+          name: "Binary Size - Upload << parameters.build_type >>"
+          no_output_timeout: "5m"
+          command: |
+            cd ~/project
+            export ANDROID_BUILD_TYPE="<< parameters.build_type >>"
+            export COMMIT_TIME=$(git log --max-count=1 --format=%ct || echo 0)
+            python3 -m tools.stats.upload_binary_size_to_scuba android

.circleci/verbatim-sources/job-specs/binary-build-tests.yml

@@ -3,12 +3,12 @@
 #  binary_linux_libtorch_3.6m_cpu_test:
 #    environment:
 #      BUILD_ENVIRONMENT: "libtorch 3.6m cpu"
-#    resource_class: gpu.nvidia.small
+#    resource_class: gpu.medium
 #    <<: *binary_linux_test
 #
 #  binary_linux_libtorch_3.6m_cu90_test:
 #    environment:
 #      BUILD_ENVIRONMENT: "libtorch 3.6m cu90"
-#    resource_class: gpu.nvidia.small
+#    resource_class: gpu.medium
 #    <<: *binary_linux_test
 #

.circleci/verbatim-sources/job-specs/binary-job-specs.yml

@@ -1,4 +1,241 @@
-jobs:
+  binary_linux_build:
+    <<: *binary_linux_build_params
+    steps:
+    - checkout
+    - calculate_docker_image_tag
+    - run:
+        <<: *binary_checkout
+    - run:
+        <<: *binary_populate_env
+    - run:
+        name: Build
+        no_output_timeout: "1h"
+        command: |
+            source "/pytorch/.circleci/scripts/binary_linux_build.sh"
+            # Preserve build log
+            if [ -f /pytorch/build/.ninja_log ]; then
+              cp /pytorch/build/.ninja_log /final_pkgs
+            fi
+    - run:
+        name: Output binary sizes
+        no_output_timeout: "1m"
+        command: |
+            ls -lah /final_pkgs
+    - run:
+        name: upload build & binary data
+        no_output_timeout: "5m"
+        command: |
+            source /env
+            cd /pytorch && export COMMIT_TIME=$(git log --max-count=1 --format=%ct || echo 0)
+            python3 -mpip install requests && \
+            SCRIBE_GRAPHQL_ACCESS_TOKEN=${SCRIBE_GRAPHQL_ACCESS_TOKEN} \
+            python3 -m tools.stats.upload_binary_size_to_scuba || exit 0
+    - persist_to_workspace:
+        root: /
+        paths: final_pkgs
+
+    - store_artifacts:
+        path: /final_pkgs
+
+    # This should really just be another step of the binary_linux_build job above.
+    # This isn't possible right now b/c the build job uses the docker executor
+    # (otherwise they'd be really really slow) but this one uses the macine
+    # executor (b/c we have to run the docker with --runtime=nvidia and we can't do
+    # that on the docker executor)
+  binary_linux_test:
+    <<: *binary_linux_test_upload_params
+    machine:
+        image: ubuntu-2004:202104-01
+    steps:
+    # See Note [Workspace for CircleCI scripts] in job-specs-setup.yml
+    - checkout
+    - attach_workspace:
+        at: /home/circleci/project
+    - setup_linux_system_environment
+    - setup_ci_environment
+    - run:
+        <<: *binary_checkout
+    - run:
+        <<: *binary_populate_env
+    - run:
+        name: Prepare test code
+        no_output_timeout: "1h"
+        command: .circleci/scripts/binary_linux_test.sh
+    - run:
+        <<: *binary_run_in_docker
+
+  binary_upload:
+    parameters:
+      package_type:
+        type: string
+        description: "What type of package we are uploading (eg. wheel, libtorch, conda)"
+        default: "wheel"
+      upload_subfolder:
+        type: string
+        description: "What subfolder to put our package into (eg. cpu, cudaX.Y, etc.)"
+        default: "cpu"
+    docker:
+      - image: continuumio/miniconda3
+    environment:
+      - DRY_RUN: disabled
+      - PACKAGE_TYPE: "<< parameters.package_type >>"
+      - UPLOAD_SUBFOLDER: "<< parameters.upload_subfolder >>"
+    steps:
+      - attach_workspace:
+          at: /tmp/workspace
+      - checkout
+      - designate_upload_channel
+      - run:
+          name: Install dependencies
+          no_output_timeout: "1h"
+          command: |
+            conda install -yq anaconda-client
+            pip install -q awscli
+      - run:
+          name: Do upload
+          no_output_timeout: "1h"
+          command: |
+            AWS_ACCESS_KEY_ID="${PYTORCH_BINARY_AWS_ACCESS_KEY_ID}" \
+              AWS_SECRET_ACCESS_KEY="${PYTORCH_BINARY_AWS_SECRET_ACCESS_KEY}" \
+              ANACONDA_API_TOKEN="${CONDA_PYTORCHBOT_TOKEN}" \
+              .circleci/scripts/binary_upload.sh
+
+  # Nighlty build smoke tests defaults
+  # These are the second-round smoke tests. These make sure that the binaries are
+  # correct from a user perspective, testing that they exist from the cloud are
+  # are runnable. Note that the pytorch repo is never cloned into these jobs
+  ##############################################################################
+  smoke_linux_test:
+    <<: *binary_linux_test_upload_params
+    machine:
+      image: ubuntu-2004:202104-01
+    steps:
+    - checkout
+    - calculate_docker_image_tag
+    - setup_linux_system_environment
+    - setup_ci_environment
+    - run:
+        <<: *binary_checkout
+    - run:
+        <<: *binary_populate_env
+    - run:
+        name: Test
+        no_output_timeout: "1h"
+        command: |
+          set -ex
+          cat >/home/circleci/project/ci_test_script.sh \<<EOL
+          # The following code will be executed inside Docker container
+          set -eux -o pipefail
+          /builder/smoke_test.sh
+          # The above code will be executed inside Docker container
+          EOL
+    - run:
+        <<: *binary_run_in_docker
+
+  smoke_mac_test:
+    <<: *binary_linux_test_upload_params
+    macos:
+      xcode: "12.0"
+    steps:
+      - checkout
+      - run:
+          <<: *binary_checkout
+      - run:
+          <<: *binary_populate_env
+      - brew_update
+      - run:
+          <<: *binary_install_miniconda
+      - run:
+          name: Build
+          no_output_timeout: "1h"
+          command: |
+            set -ex
+            source "/Users/distiller/project/env"
+            export "PATH=$workdir/miniconda/bin:$PATH"
+            # TODO unbuffer and ts this, but it breaks cause miniconda overwrites
+            # tclsh. But unbuffer and ts aren't that important so they're just
+            # disabled for now
+            ./builder/smoke_test.sh
+
+  binary_mac_build:
+    <<: *binary_mac_params
+    macos:
+      xcode: "12.0"
+    steps:
+    # See Note [Workspace for CircleCI scripts] in job-specs-setup.yml
+    - checkout
+    - run:
+        <<: *binary_checkout
+    - run:
+        <<: *binary_populate_env
+    - brew_update
+    - run:
+        <<: *binary_install_miniconda
+
+    - run:
+        name: Build
+        no_output_timeout: "90m"
+        command: |
+          # Do not set -u here; there is some problem with CircleCI
+          # variable expansion with PROMPT_COMMAND
+          set -ex -o pipefail
+          script="/Users/distiller/project/pytorch/.circleci/scripts/binary_macos_build.sh"
+          cat "$script"
+          source "$script"
+
+    - run:
+        name: Test
+        no_output_timeout: "1h"
+        command: |
+          # Do not set -u here; there is some problem with CircleCI
+          # variable expansion with PROMPT_COMMAND
+          set -ex -o pipefail
+          script="/Users/distiller/project/pytorch/.circleci/scripts/binary_macos_test.sh"
+          cat "$script"
+          source "$script"
+
+    - persist_to_workspace:
+        root: /Users/distiller/project
+        paths: final_pkgs
+
+    - store_artifacts:
+        path: /Users/distiller/project/final_pkgs
+
+  binary_macos_arm64_build:
+    <<: *binary_mac_params
+    macos:
+      xcode: "12.3.0"
+    steps:
+    # See Note [Workspace for CircleCI scripts] in job-specs-setup.yml
+    - checkout
+    - run:
+        <<: *binary_checkout
+    - run:
+        <<: *binary_populate_env
+    - brew_update
+    - run:
+        <<: *binary_install_miniconda
+
+    - run:
+        name: Build
+        no_output_timeout: "90m"
+        command: |
+          # Do not set -u here; there is some problem with CircleCI
+          # variable expansion with PROMPT_COMMAND
+          set -ex -o pipefail
+          export CROSS_COMPILE_ARM64=1
+          script="/Users/distiller/project/pytorch/.circleci/scripts/binary_macos_build.sh"
+          cat "$script"
+          source "$script"
+
+    - persist_to_workspace:
+        root: /Users/distiller/project
+        paths: final_pkgs
+
+    - store_artifacts:
+        path: /Users/distiller/project/final_pkgs
+
+
   binary_ios_build:
     <<: *pytorch_ios_params
     macos:
@@ -43,6 +280,90 @@ jobs:
           cat "$script"
           source "$script"
 
+  binary_windows_build:
+    <<: *binary_windows_params
+    parameters:
+      build_environment:
+        type: string
+        default: ""
+      executor:
+        type: string
+        default: "windows-xlarge-cpu-with-nvidia-cuda"
+    executor: <<parameters.executor>>
+    steps:
+    # See Note [Workspace for CircleCI scripts] in job-specs-setup.yml
+    - checkout
+    - run:
+        <<: *binary_checkout
+    - run:
+        <<: *binary_populate_env
+    - run:
+        name: Build
+        no_output_timeout: "1h"
+        command: |
+          set -eux -o pipefail
+          script="/c/w/p/.circleci/scripts/binary_windows_build.sh"
+          cat "$script"
+          source "$script"
+    - persist_to_workspace:
+        root: "C:/w"
+        paths: final_pkgs
+    - store_artifacts:
+        path: C:/w/final_pkgs
+
+  binary_windows_test:
+    <<: *binary_windows_params
+    parameters:
+      build_environment:
+        type: string
+        default: ""
+      executor:
+        type: string
+        default: "windows-medium-cpu-with-nvidia-cuda"
+    executor: <<parameters.executor>>
+    steps:
+    - checkout
+    - attach_workspace:
+        at: c:/users/circleci/project
+    - run:
+        <<: *binary_checkout
+    - run:
+        <<: *binary_populate_env
+    - run:
+        name: Test
+        no_output_timeout: "1h"
+        command: |
+          set -eux -o pipefail
+          script="/c/w/p/.circleci/scripts/binary_windows_test.sh"
+          cat "$script"
+          source "$script"
+
+  smoke_windows_test:
+    <<: *binary_windows_params
+    parameters:
+      build_environment:
+        type: string
+        default: ""
+      executor:
+        type: string
+        default: "windows-medium-cpu-with-nvidia-cuda"
+    executor: <<parameters.executor>>
+    steps:
+    - checkout
+    - run:
+        <<: *binary_checkout
+    - run:
+        <<: *binary_populate_env
+    - run:
+        name: Test
+        no_output_timeout: "1h"
+        command: |
+          set -eux -o pipefail
+          export TEST_NIGHTLY_PACKAGE=1
+          script="/c/w/p/.circleci/scripts/binary_windows_test.sh"
+          cat "$script"
+          source "$script"
+
   anaconda_prune:
     parameters:
       packages:

.circleci/verbatim-sources/job-specs/docker_jobs.yml

@@ -54,3 +54,61 @@
               export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_DOCKER_BUILDER_V1}
               set -x
               cd .circleci/docker && ./build_docker.sh
+  docker_for_ecr_gc_build_job:
+      machine:
+        image: ubuntu-2004:202104-01
+      steps:
+        - checkout
+        - run:
+            name: build_docker_image_for_ecr_gc
+            no_output_timeout: "1h"
+            command: |
+              cd .circleci/ecr_gc_docker
+              docker build . -t 308535385114.dkr.ecr.us-east-1.amazonaws.com/gc/ecr
+              set +x
+              export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_DOCKER_BUILDER_V1}
+              export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_DOCKER_BUILDER_V1}
+              export AWS_ACCOUNT_ID=$(aws sts get-caller-identity|grep Account|cut -f4 -d\")
+              export AWS_REGION=us-east-1
+              aws ecr get-login-password --region $AWS_REGION|docker login --username AWS \
+                       --password-stdin $AWS_ACCOUNT_ID.dkr.ecr.$AWS_REGION.amazonaws.com
+              set -x
+              docker push $AWS_ACCOUNT_ID.dkr.ecr.$AWS_REGION.amazonaws.com/gc/ecr
+  ecr_gc_job:
+      parameters:
+        project:
+          type: string
+          default: "pytorch"
+        tags_to_keep:  # comma separate values
+          type: string
+      environment:
+        PROJECT: << parameters.project >>
+        # TODO: Remove legacy image tags once we feel comfortable with new docker image tags
+        IMAGE_TAG: << parameters.tags_to_keep >>
+      docker:
+        - image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/gc/ecr
+          aws_auth:
+            aws_access_key_id: ${CIRCLECI_AWS_ACCESS_KEY_FOR_DOCKER_BUILDER_V1}
+            aws_secret_access_key: ${CIRCLECI_AWS_SECRET_KEY_FOR_DOCKER_BUILDER_V1}
+
+      steps:
+        - checkout
+        - run:
+            # NOTE: see 'docker_build_job' for how these tags actually get built
+            name: dynamically generate tags to keep
+            no_output_timeout: "1h"
+            command: |
+              GENERATED_IMAGE_TAG=$(\
+                git log --oneline --pretty='%H' .circleci/docker \
+                  | xargs -I '{}' git rev-parse '{}:.circleci/docker' \
+                  | paste -sd "," -)
+              echo "export GENERATED_IMAGE_TAG='${GENERATED_IMAGE_TAG}'" >> ${BASH_ENV}
+        - run:
+            name: garbage collecting for ecr images
+            no_output_timeout: "1h"
+            command: |
+              set +x
+              export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_DOCKER_BUILDER_V1}
+              export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_DOCKER_BUILDER_V1}
+              set -x
+              /usr/bin/gc.py --filter-prefix ${PROJECT}  --ignore-tags "${IMAGE_TAG},${GENERATED_IMAGE_TAG}"

.circleci/verbatim-sources/job-specs/job-specs-custom.yml

@@ -5,7 +5,7 @@
     parameters:
       branch:
         type: string
-        default: "main"
+        default: "master"
     steps:
     - attach_workspace:
         at: /tmp/workspace
@@ -24,6 +24,93 @@
           pushd /tmp/workspace
           git push -u origin "<< parameters.branch >>"
 
+  pytorch_python_doc_build:
+    environment:
+      BUILD_ENVIRONMENT: pytorch-python-doc-push
+      DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-py3.6-gcc5.4"
+    resource_class: large
+    machine:
+      image: ubuntu-2004:202104-01
+    steps:
+    - checkout
+    - calculate_docker_image_tag
+    - setup_linux_system_environment
+    - setup_ci_environment
+    - run:
+        name: Doc Build and Push
+        no_output_timeout: "1h"
+        command: |
+          set -ex
+          export COMMIT_DOCKER_IMAGE=${DOCKER_IMAGE}:build-${DOCKER_TAG}-${CIRCLE_SHA1}
+          echo "DOCKER_IMAGE: "${COMMIT_DOCKER_IMAGE}
+          tag=${CIRCLE_TAG:1:5}
+          target=${tag:-master}
+          echo "building for ${target}"
+          time docker pull ${COMMIT_DOCKER_IMAGE} >/dev/null
+          export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${COMMIT_DOCKER_IMAGE})
+
+          export COMMAND='((echo "sudo chown -R jenkins workspace && cd workspace && '"export CIRCLE_SHA1='$CIRCLE_SHA1'"' && . ./.circleci/scripts/python_doc_push_script.sh docs/'$target' '$target' site") | docker exec -u jenkins -i "$id" bash) 2>&1'
+
+          echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
+
+          mkdir -p ~/workspace/build_artifacts
+          docker cp $id:/var/lib/jenkins/workspace/pytorch.github.io/docs/master ~/workspace/build_artifacts
+          docker cp $id:/var/lib/jenkins/workspace/pytorch.github.io /tmp/workspace
+
+          # Save the docs build so we can debug any problems
+          export DEBUG_COMMIT_DOCKER_IMAGE=${COMMIT_DOCKER_IMAGE}-debug
+          docker commit "$id" ${DEBUG_COMMIT_DOCKER_IMAGE}
+          time docker push ${DEBUG_COMMIT_DOCKER_IMAGE}
+    - persist_to_workspace:
+        root: /tmp/workspace
+        paths:
+          - .
+    - store_artifacts:
+        path: ~/workspace/build_artifacts/master
+        destination: docs
+
+  pytorch_cpp_doc_build:
+    environment:
+      BUILD_ENVIRONMENT: pytorch-cpp-doc-push
+      DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-py3.6-gcc5.4"
+    resource_class: large
+    machine:
+      image: ubuntu-2004:202104-01
+    steps:
+    - checkout
+    - calculate_docker_image_tag
+    - setup_linux_system_environment
+    - setup_ci_environment
+    - run:
+        name: Doc Build and Push
+        no_output_timeout: "1h"
+        command: |
+          set -ex
+          export COMMIT_DOCKER_IMAGE=${DOCKER_IMAGE}:build-${DOCKER_TAG}-${CIRCLE_SHA1}
+          echo "DOCKER_IMAGE: "${COMMIT_DOCKER_IMAGE}
+          tag=${CIRCLE_TAG:1:5}
+          target=${tag:-master}
+          echo "building for ${target}"
+          time docker pull ${COMMIT_DOCKER_IMAGE} >/dev/null
+          export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${COMMIT_DOCKER_IMAGE})
+
+          export COMMAND='((echo "sudo chown -R jenkins workspace && cd workspace && '"export CIRCLE_SHA1='$CIRCLE_SHA1'"' && . ./.circleci/scripts/cpp_doc_push_script.sh docs/"$target" master") | docker exec -u jenkins -i "$id" bash) 2>&1'
+
+          echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
+
+          mkdir -p ~/workspace/build_artifacts
+          docker cp $id:/var/lib/jenkins/workspace/cppdocs/ /tmp/workspace
+
+          # Save the docs build so we can debug any problems
+          export DEBUG_COMMIT_DOCKER_IMAGE=${COMMIT_DOCKER_IMAGE}-debug
+          docker commit "$id" ${DEBUG_COMMIT_DOCKER_IMAGE}
+          time docker push ${DEBUG_COMMIT_DOCKER_IMAGE}
+
+    - persist_to_workspace:
+        root: /tmp/workspace
+        paths:
+          - .
+
   pytorch_macos_10_15_py3_build:
     environment:
       BUILD_ENVIRONMENT: pytorch-macos-10.15-py3-arm64-build
@@ -37,6 +124,7 @@
           no_output_timeout: "1h"
           command: |
             set -e
+            export IN_CI=1
             export CROSS_COMPILE_ARM64=1
             export JOB_BASE_NAME=$CIRCLE_JOB
 
@@ -74,6 +162,7 @@
           no_output_timeout: "1h"
           command: |
             set -e
+            export IN_CI=1
             export JOB_BASE_NAME=$CIRCLE_JOB
 
             # Install sccache
@@ -95,198 +184,6 @@
           paths:
             - miniconda3
 
-  mac_build:
-    parameters:
-      build-environment:
-        type: string
-        description: Top-level label for what's being built/tested.
-      xcode-version:
-        type: string
-        default: "13.3.1"
-        description: What xcode version to build with.
-      build-generates-artifacts:
-        type: boolean
-        default: true
-        description: if the build generates build artifacts
-      python-version:
-        type: string
-        default: "3.8"
-    macos:
-      xcode: << parameters.xcode-version >>
-    resource_class: medium
-    environment:
-      BUILD_ENVIRONMENT: << parameters.build-environment >>
-      AWS_REGION: us-east-1
-    steps:
-
-      - checkout
-      - run_brew_for_macos_build
-
-      - run:
-          name: Install sccache
-          command: |
-            sudo curl --retry 3 https://s3.amazonaws.com/ossci-macos/sccache_v2.15 --output /usr/local/bin/sccache
-            sudo chmod +x /usr/local/bin/sccache
-            echo "export SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2" >> "${BASH_ENV}"
-            echo "export SCCACHE_S3_KEY_PREFIX=${GITHUB_WORKFLOW}" >> "${BASH_ENV}"
-
-            set +x
-            echo "export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_SCCACHE_S3_BUCKET_V4}" >> "${BASH_ENV}"
-            echo "export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_SCCACHE_S3_BUCKET_V4}" >> "${BASH_ENV}"
-            set -x
-
-      - run:
-          name: Get workflow job id
-          command: |
-            echo "export OUR_GITHUB_JOB_ID=${CIRCLE_WORKFLOW_JOB_ID}" >> "${BASH_ENV}"
-
-      - run:
-          name: Build
-          command: |
-            set -x
-
-            git submodule sync
-            git submodule update --init --recursive --depth 1 --jobs 0
-
-            export PATH="/usr/local/bin:$PATH"
-            export WORKSPACE_DIR="${HOME}/workspace"
-            mkdir -p "${WORKSPACE_DIR}"
-            MINICONDA_URL="https://repo.anaconda.com/miniconda/Miniconda3-py38_4.12.0-MacOSX-x86_64.sh"
-            if [  << parameters.python-version >> == 3.9.12 ]; then
-              MINICONDA_URL="https://repo.anaconda.com/miniconda/Miniconda3-py39_4.12.0-MacOSX-x86_64.sh"
-            fi
-
-            # If a local installation of conda doesn't exist, we download and install conda
-            if [ ! -d "${WORKSPACE_DIR}/miniconda3" ]; then
-              mkdir -p "${WORKSPACE_DIR}"
-              curl --retry 3 ${MINICONDA_URL} -o "${WORKSPACE_DIR}"/miniconda3.sh
-              bash "${WORKSPACE_DIR}"/miniconda3.sh -b -p "${WORKSPACE_DIR}"/miniconda3
-            fi
-            export PATH="${WORKSPACE_DIR}/miniconda3/bin:$PATH"
-            # shellcheck disable=SC1091
-            source "${WORKSPACE_DIR}"/miniconda3/bin/activate
-
-            brew link --force libomp
-
-            echo "export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname "$(which conda)")/../"}" >> "${BASH_ENV}"
-            .jenkins/pytorch/macos-build.sh
-
-      - when:
-          condition: << parameters.build-generates-artifacts >>
-          steps:
-            - run:
-                name: Archive artifacts into zip
-                command: |
-                  zip -1 -r artifacts.zip dist/ build/.ninja_log build/compile_commands.json .pytorch-test-times.json
-                  cp artifacts.zip /Users/distiller/workspace
-
-      - persist_to_workspace:
-          root: /Users/distiller/workspace/
-          paths:
-            - miniconda3
-            - artifacts.zip
-
-      - store_artifacts:
-          path: /Users/distiller/project/artifacts.zip
-
-  mac_test:
-    parameters:
-      build-environment:
-        type: string
-      shard-number:
-        type: string
-      num-test-shards:
-        type: string
-      xcode-version:
-        type: string
-      test-config:
-        type: string
-        default: 'default'
-
-    macos:
-      xcode: << parameters.xcode-version >>
-    environment:
-      GIT_DEFAULT_BRANCH: 'master'
-      BUILD_ENVIRONMENT: << parameters.build-environment >>
-      TEST_CONFIG: << parameters.test-config >>
-      SHARD_NUMBER: << parameters.shard-number >>
-      NUM_TEST_SHARDS: << parameters.num-test-shards >>
-      PYTORCH_RETRY_TEST_CASES: 1
-      PYTORCH_OVERRIDE_FLAKY_SIGNAL: 1
-    steps:
-      - checkout
-      - attach_workspace:
-          at: ~/workspace
-      - run_brew_for_macos_build
-      - run:
-          name: Test
-          no_output_timeout: "2h"
-          command: |
-            set -x
-
-            git submodule sync --recursive
-            git submodule update --init --recursive
-
-            mv ~/workspace/artifacts.zip .
-            unzip artifacts.zip
-
-            export IN_CI=1
-
-            COMMIT_MESSAGES=$(git cherry -v "origin/${GIT_DEFAULT_BRANCH:-master}")
-
-            export PATH="/usr/local/bin:$PATH"
-            export WORKSPACE_DIR="${HOME}/workspace"
-            mkdir -p "${WORKSPACE_DIR}"
-
-            export PATH="${WORKSPACE_DIR}/miniconda3/bin:$PATH"
-            source "${WORKSPACE_DIR}"/miniconda3/bin/activate
-
-            # sanitize the input commit message and PR body here:
-
-            # trim all new lines from commit messages to avoid issues with batch environment
-            # variable copying. see https://github.com/pytorch/pytorch/pull/80043#issuecomment-1167796028
-            COMMIT_MESSAGES="${COMMIT_MESSAGES//[$'\n\r']}"
-
-            # then trim all special characters like single and double quotes to avoid unescaped inputs to
-            # wreak havoc internally
-            export COMMIT_MESSAGES="${COMMIT_MESSAGES//[\'\"]}"
-
-            python3 -mpip install dist/*.whl
-            .jenkins/pytorch/macos-test.sh
-      - run:
-          name: Copy files for uploading test stats
-          command: |
-            # copy into a parent folder test-reports because we can't use CIRCLEI_BUILD_NUM in path when persisting to workspace
-            mkdir -p test-reports/test-reports_${CIRCLE_BUILD_NUM}/test/test-reports
-            cp -r test/test-reports test-reports/test-reports_${CIRCLE_BUILD_NUM}/test/test-reports
-      - store_test_results:
-          path: test/test-reports
-      - persist_to_workspace:
-          root: /Users/distiller/project/
-          paths:
-            - test-reports
-
-  upload_test_stats:
-    machine: # executor type
-      image: ubuntu-2004:202010-01 # # recommended linux image - includes Ubuntu 20.04, docker 19.03.13, docker-compose 1.27.4
-    steps:
-      - checkout
-      - attach_workspace:
-          at: ~/workspace
-      - run:
-          name: upload
-          command: |
-            set -ex
-            if [ -z ${AWS_ACCESS_KEY_FOR_OSSCI_ARTIFACT_UPLOAD} ]; then
-              echo "No credentials found, cannot upload test stats (are you on a fork?)"
-              exit 0
-            fi
-            cp -r ~/workspace/test-reports/* ~/project
-            pip3 install requests==2.26 rockset==0.8.3 boto3==1.19.12 six==1.16.0
-            export AWS_ACCESS_KEY_ID=${AWS_ACCESS_KEY_FOR_OSSCI_ARTIFACT_UPLOAD}
-            export AWS_SECRET_ACCESS_KEY=${AWS_SECRET_KEY_FOR_OSSCI_ARTIFACT_UPLOAD}
-            # i dont know how to get the run attempt number for reruns so default to 1
-            python3 -m tools.stats.upload_test_stats --workflow-run-id "${CIRCLE_WORKFLOW_JOB_ID}" --workflow-run-attempt 1 --head-branch << pipeline.git.branch >> --circleci
   pytorch_macos_10_13_py3_test:
     environment:
       BUILD_ENVIRONMENT: pytorch-macos-10.13-py3-test
@@ -302,6 +199,7 @@
           no_output_timeout: "1h"
           command: |
             set -e
+            export IN_CI=1
             export JOB_BASE_NAME=$CIRCLE_JOB
 
             chmod a+x .jenkins/pytorch/macos-test.sh
@@ -312,8 +210,9 @@
           command: |
             set -ex
             source /Users/distiller/workspace/miniconda3/bin/activate
-            python3 -m pip install boto3==1.19.12
+            pip install boto3
 
+            export IN_CI=1
             export JOB_BASE_NAME=$CIRCLE_JOB
 
             # Using the same IAM user to write stats to our OSS bucket
@@ -339,6 +238,7 @@
           no_output_timeout: "1h"
           command: |
             set -e
+            export IN_CI=1
             export BUILD_LITE_INTERPRETER=1
             export JOB_BASE_NAME=$CIRCLE_JOB
             chmod a+x ${HOME}/project/.jenkins/pytorch/macos-lite-interpreter-build-test.sh
@@ -350,7 +250,7 @@
     environment:
       BUILD_ENVIRONMENT: pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-build
       DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c"
-      PYTHON_VERSION: "3.7"
+      PYTHON_VERSION: "3.6"
     resource_class: large
     machine:
       image: ubuntu-2004:202104-01
@@ -428,6 +328,9 @@
           output_image=$docker_image_libtorch_android_x86_32-gradle
           docker commit "$id_x86_32" ${output_image}
           time docker push ${output_image}
+    - upload_binary_size_for_android_build:
+        build_type: prebuilt
+        artifacts: /home/circleci/workspace/build_android_artifacts/artifacts.tgz
     - store_artifacts:
         path: ~/workspace/build_android_artifacts/artifacts.tgz
         destination: artifacts.tgz
@@ -436,7 +339,7 @@
     environment:
       BUILD_ENVIRONMENT: pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-publish-snapshot
       DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c"
-      PYTHON_VERSION: "3.7"
+      PYTHON_VERSION: "3.6"
     resource_class: large
     machine:
       image: ubuntu-2004:202104-01
@@ -472,7 +375,7 @@
     environment:
       BUILD_ENVIRONMENT: pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-build-only-x86_32
       DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c"
-      PYTHON_VERSION: "3.7"
+      PYTHON_VERSION: "3.6"
     resource_class: large
     machine:
       image: ubuntu-2004:202104-01
@@ -503,52 +406,59 @@
           output_image=${docker_image_libtorch_android_x86_32}-gradle
           docker commit "$id" ${output_image}
           time docker push ${output_image}
+    - upload_binary_size_for_android_build:
+        build_type: prebuilt-single
+        artifacts: /home/circleci/workspace/build_android_x86_32_artifacts/artifacts.tgz
     - store_artifacts:
         path: ~/workspace/build_android_x86_32_artifacts/artifacts.tgz
         destination: artifacts.tgz
 
+  pytorch_android_gradle_custom_build_single:
+    <<: *pytorch_android_params
+    resource_class: large
+    machine:
+      image: ubuntu-2004:202104-01
+    steps:
+    - checkout
+    - calculate_docker_image_tag
+    - setup_linux_system_environment
+    - checkout
+    - calculate_docker_image_tag
+    - setup_ci_environment
+    - run:
+        name: pytorch android gradle custom build single architecture (for PR)
+        no_output_timeout: "1h"
+        command: |
+          set -e
+          # Unlike other gradle jobs, it's not worth building libtorch in a separate CI job and share via docker, because:
+          # 1) Not shareable: it's custom selective build, which is different from default libtorch mobile build;
+          # 2) Not parallelizable by architecture: it only builds libtorch for one architecture;
+
+          echo "DOCKER_IMAGE: ${DOCKER_IMAGE}:${DOCKER_TAG}"
+          time docker pull ${DOCKER_IMAGE}:${DOCKER_TAG} >/dev/null
+
+          git submodule sync && git submodule update -q --init --recursive --depth 1 --jobs 0
+          VOLUME_MOUNTS="-v /home/circleci/project/:/var/lib/jenkins/workspace"
+          export id=$(docker run --env-file "${BASH_ENV}" ${VOLUME_MOUNTS} --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${DOCKER_IMAGE}:${DOCKER_TAG})
+
+          export COMMAND='((echo "export GRADLE_OFFLINE=1" && echo "export BUILD_LITE_INTERPRETER=${BUILD_LITE_INTERPRETER}" && echo "sudo chown -R jenkins workspace && cd workspace && ./.circleci/scripts/build_android_gradle.sh") | docker exec -u jenkins -i "$id" bash) 2>&1'
+          echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
+
+          # Skip docker push as this job is purely for size analysis purpose.
+          # Result binaries are already in `/home/circleci/project/` as it's mounted instead of copied.
+
+    - upload_binary_size_for_android_build:
+        build_type: custom-build-single
+
   pytorch_ios_build:
     <<: *pytorch_ios_params
     macos:
       xcode: "12.5.1"
     steps:
-      - run:
-          name: checkout with retry
-          command: |
-            checkout() {
-              set -ex
-              # Workaround old docker images with incorrect $HOME
-              # check https://github.com/docker/docker/issues/2968 for details
-              if [ "${HOME}" = "/" ]
-                then
-                export HOME=$(getent passwd $(id -un) | cut -d: -f6)
-              fi
-
-              mkdir -p ~/.ssh
-
-              echo 'github.com ssh-rsa AAAAB3NzaC1yc2EAAAABIwAAAQEAq2A7hRGmdnm9tUDbO9IDSwBK6TbQa+PXYPCPy6rbTrTtw7PHkccKrpp0yVhp5HdEIcKr6pLlVDBfOLX9QUsyCOV0wzfjIJNlGEYsdlLJizHhbn2mUjvSAHQqZETYP81eFzLQNnPHt4EVVUh7VfDESU84KezmD5QlWpXLmvU31/yMf+Se8xhHTvKSCZIFImWwoG6mbUoWf9nzpIoaSjB+weqqUUmpaaasXVal72J+UX2B+2RPW3RcT0eOzQgqlJL3RKrTJvdsjE3JEAvGq3lGHSZXy28G3skua2SmVi/w4yCE6gbODqnTWlg7+wC604ydGXA8VJiS5ap43JXiUFFAaQ==
-              ' >> ~/.ssh/known_hosts
-
-              # use git+ssh instead of https
-              git config --global url."ssh://git@github.com".insteadOf "https://github.com" || true
-              git config --global gc.auto 0 || true
-
-              echo 'Cloning git repository'
-              mkdir -p '/Users/distiller/project'
-              cd '/Users/distiller/project'
-              git clone "$CIRCLE_REPOSITORY_URL" .
-              echo 'Checking out branch'
-              git checkout --force -B "$CIRCLE_BRANCH" "$CIRCLE_SHA1"
-              git --no-pager log --no-color -n 1 --format='HEAD is now at %h %s'
-            }
-
-            retry () {
-              $* || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
-            }
-            retry checkout
+      - checkout
       - run_brew_for_ios_build
       - run:
-          name: Setup Fastlane
+          name: Run Fastlane
           no_output_timeout: "1h"
           command: |
             set -e
@@ -556,11 +466,26 @@
             cd ${PROJ_ROOT}/ios/TestApp
             # install fastlane
             sudo gem install bundler && bundle install
+            # install certificates
+            echo ${IOS_CERT_KEY_2022} >> cert.txt
+            base64 --decode cert.txt -o Certificates.p12
+            rm cert.txt
+            bundle exec fastlane install_root_cert
+            bundle exec fastlane install_dev_cert
+            # install the provisioning profile
+            PROFILE=PyTorch_CI_2022.mobileprovision
+            PROVISIONING_PROFILES=~/Library/MobileDevice/Provisioning\ Profiles
+            mkdir -pv "${PROVISIONING_PROFILES}"
+            cd "${PROVISIONING_PROFILES}"
+            echo ${IOS_SIGN_KEY_2022} >> cert.txt
+            base64 --decode cert.txt -o ${PROFILE}
+            rm cert.txt
       - run:
           name: Build
           no_output_timeout: "1h"
           command: |
             set -e
+            export IN_CI=1
             WORKSPACE=/Users/distiller/workspace
             PROJ_ROOT=/Users/distiller/project
             export TCLLIBPATH="/usr/local/lib"
@@ -593,7 +518,6 @@
             echo "IOS_PLATFORM: ${IOS_PLATFORM}"
             echo "USE_PYTORCH_METAL": "${USE_METAL}"
             echo "BUILD_LITE_INTERPRETER": "${BUILD_LITE_INTERPRETER}"
-            echo "USE_COREML_DELEGATE": "${USE_COREML_DELEGATE}"
 
             #check the custom build flag
             echo "SELECTED_OP_LIST: ${SELECTED_OP_LIST}"
@@ -602,7 +526,6 @@
             fi
             export IOS_ARCH=${IOS_ARCH}
             export IOS_PLATFORM=${IOS_PLATFORM}
-            export USE_COREML_DELEGATE=${USE_COREML_DELEGATE}
             if [ ${IOS_PLATFORM} != "SIMULATOR" ]; then
               export USE_PYTORCH_METAL=${USE_METAL}
             fi
@@ -613,12 +536,18 @@
           command: |
             set -e
             PROJ_ROOT=/Users/distiller/project
+            PROFILE=PyTorch_CI_2022
             # run the ruby build script
             if ! [ -x "$(command -v xcodebuild)" ]; then
               echo 'Error: xcodebuild is not installed.'
               exit 1
             fi
-            ruby ${PROJ_ROOT}/scripts/xcode_build.rb -i ${PROJ_ROOT}/build_ios/install -x ${PROJ_ROOT}/ios/TestApp/TestApp.xcodeproj -p ${IOS_PLATFORM}
+            echo ${IOS_DEV_TEAM_ID}
+            if [ ${IOS_PLATFORM} != "SIMULATOR" ]; then
+              ruby ${PROJ_ROOT}/scripts/xcode_build.rb -i ${PROJ_ROOT}/build_ios/install -x ${PROJ_ROOT}/ios/TestApp/TestApp.xcodeproj -p ${IOS_PLATFORM} -c ${PROFILE} -t ${IOS_DEV_TEAM_ID}
+            else
+              ruby ${PROJ_ROOT}/scripts/xcode_build.rb -i ${PROJ_ROOT}/build_ios/install -x ${PROJ_ROOT}/ios/TestApp/TestApp.xcodeproj -p ${IOS_PLATFORM}
+            fi
             if ! [ "$?" -eq "0" ]; then
               echo 'xcodebuild failed!'
               exit 1
@@ -636,33 +565,20 @@
             PROJ_ROOT=/Users/distiller/project
             source ~/anaconda/bin/activate
             # use the pytorch nightly build to generate models
-            pip3 install --pre torch torchvision torchaudio -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
+            conda install pytorch torchvision -c pytorch-nightly --yes
             # generate models for differnet backends
             cd ${PROJ_ROOT}/ios/TestApp/benchmark
             mkdir -p ../models
-            if [ ${USE_COREML_DELEGATE} == 1 ]; then
-              pip install coremltools==5.0b5 protobuf==3.20.1 six==1.16.0
-              python coreml_backend.py
-            else
-              cd "${PROJ_ROOT}"
-              python test/mobile/model_test/gen_test_model.py ios-test
-            fi
-            cd "${PROJ_ROOT}/ios/TestApp/benchmark"
+            python trace_model.py
             if [ ${BUILD_LITE_INTERPRETER} == 1 ]; then
-              echo "Setting up the TestApp for LiteInterpreter"
               ruby setup.rb --lite 1
             else
-              echo "Setting up the TestApp for Full JIT"
               ruby setup.rb
             fi
-            cd "${PROJ_ROOT}/ios/TestApp"
-            # instruments -s -devices
-            if [ "${BUILD_LITE_INTERPRETER}" == 1 ]; then
-              if [ "${USE_COREML_DELEGATE}" == 1 ]; then
-                fastlane scan --only_testing TestAppTests/TestAppTests/testCoreML
-              else
-                fastlane scan --only_testing TestAppTests/TestAppTests/testLiteInterpreter
-              fi
+            cd ${PROJ_ROOT}/ios/TestApp
+            instruments -s -devices
+            if [ ${BUILD_LITE_INTERPRETER} == 1 ]; then
+              fastlane scan --only_testing TestAppTests/TestAppTests/testLiteInterpreter
             else
               fastlane scan --only_testing TestAppTests/TestAppTests/testFullJIT
             fi
@@ -685,7 +601,7 @@
           time docker pull ${DOCKER_IMAGE}:${DOCKER_TAG} >/dev/null
           export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${DOCKER_IMAGE}:${DOCKER_TAG})
 
-          echo "Do NOT merge main branch into $CIRCLE_BRANCH in environment $BUILD_ENVIRONMENT"
+          echo "Do NOT merge master branch into $CIRCLE_BRANCH in environment $BUILD_ENVIRONMENT"
 
           git submodule sync && git submodule update -q --init --recursive --depth 1 --jobs 0
 
@@ -760,3 +676,27 @@
             set -e
             python3 -m pip install requests
             python3 ./.circleci/scripts/trigger_azure_pipeline.py
+
+  pytorch_doc_test:
+    environment:
+      BUILD_ENVIRONMENT: pytorch-doc-test
+      DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-py3.6-gcc5.4"
+    resource_class: medium
+    machine:
+      image: ubuntu-2004:202104-01
+    steps:
+    - checkout
+    - calculate_docker_image_tag
+    - setup_linux_system_environment
+    - setup_ci_environment
+    - run:
+        name: Doc test
+        no_output_timeout: "30m"
+        command: |
+          set -ex
+          export COMMIT_DOCKER_IMAGE=${DOCKER_IMAGE}:build-${DOCKER_TAG}-${CIRCLE_SHA1}
+          echo "DOCKER_IMAGE: "${COMMIT_DOCKER_IMAGE}
+          time docker pull ${COMMIT_DOCKER_IMAGE} >/dev/null
+          export id=$(docker run --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${COMMIT_DOCKER_IMAGE})
+          export COMMAND='((echo "sudo chown -R jenkins workspace && cd workspace && . ./.jenkins/pytorch/docs-test.sh") | docker exec -u jenkins -i "$id" bash) 2>&1'
+          echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts

.circleci/verbatim-sources/job-specs/pytorch-job-specs.yml

@@ -0,0 +1,400 @@
+jobs:
+  pytorch_linux_build:
+    <<: *pytorch_params
+    machine:
+      image: ubuntu-2004:202104-01
+    steps:
+    # See Note [Workspace for CircleCI scripts] in job-specs-setup.yml
+    - checkout
+    - calculate_docker_image_tag
+    - setup_linux_system_environment
+    - optional_merge_target_branch
+    - setup_ci_environment
+    - run:
+        name: Build
+        no_output_timeout: "1h"
+        command: |
+          set -e
+          if [[ ${BUILD_ENVIRONMENT} == *"pure_torch"* ]]; then
+            echo 'BUILD_CAFFE2=OFF' >> "${BASH_ENV}"
+          fi
+          if [[ ${BUILD_ENVIRONMENT} == *"paralleltbb"* ]]; then
+            echo 'ATEN_THREADING=TBB' >> "${BASH_ENV}"
+            echo 'USE_TBB=1' >> "${BASH_ENV}"
+          elif [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
+            echo 'ATEN_THREADING=NATIVE' >> "${BASH_ENV}"
+          fi
+          echo "Parallel backend flags: "${PARALLEL_FLAGS}
+          # Pull Docker image and run build
+          echo "DOCKER_IMAGE: "${DOCKER_IMAGE}:${DOCKER_TAG}
+          time docker pull ${DOCKER_IMAGE}:${DOCKER_TAG} >/dev/null
+          export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${DOCKER_IMAGE}:${DOCKER_TAG})
+
+          git submodule sync && git submodule update -q --init --recursive --depth 1 --jobs 0
+
+          docker cp /home/circleci/project/. $id:/var/lib/jenkins/workspace
+
+          export COMMAND='((echo "sudo chown -R jenkins workspace && export JOB_BASE_NAME="$CIRCLE_JOB" && cd workspace && .jenkins/pytorch/build.sh && find ${BUILD_ROOT} -type f -name "*.a" -or -name "*.o" -delete") | docker exec -u jenkins -i "$id" bash) 2>&1'
+
+          echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
+
+          # Copy dist folder back
+          docker cp $id:/var/lib/jenkins/workspace/dist /home/circleci/project/. || echo "Dist folder not found"
+
+          # Push intermediate Docker image for next phase to use
+          if [ -z "${BUILD_ONLY}" ]; then
+            # Note [Special build images]
+            # The xla build uses the same docker image as
+            # pytorch_linux_bionic_py3_6_clang9_build. In the push step, we have to
+            # distinguish between them so the test can pick up the correct image.
+            output_image=${DOCKER_IMAGE}:build-${DOCKER_TAG}-${CIRCLE_SHA1}
+            if [[ ${BUILD_ENVIRONMENT} == *"xla"* ]]; then
+              export COMMIT_DOCKER_IMAGE=$output_image-xla
+            elif [[ ${BUILD_ENVIRONMENT} == *"libtorch"* ]]; then
+              export COMMIT_DOCKER_IMAGE=$output_image-libtorch
+            elif [[ ${BUILD_ENVIRONMENT} == *"paralleltbb"* ]]; then
+              export COMMIT_DOCKER_IMAGE=$output_image-paralleltbb
+            elif [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
+              export COMMIT_DOCKER_IMAGE=$output_image-parallelnative
+            elif [[ ${BUILD_ENVIRONMENT} == *"android-ndk-r19c-x86_64"* ]]; then
+              export COMMIT_DOCKER_IMAGE=$output_image-android-x86_64
+            elif [[ ${BUILD_ENVIRONMENT} == *"android-ndk-r19c-arm-v7a"* ]]; then
+              export COMMIT_DOCKER_IMAGE=$output_image-android-arm-v7a
+            elif [[ ${BUILD_ENVIRONMENT} == *"android-ndk-r19c-arm-v8a"* ]]; then
+              export COMMIT_DOCKER_IMAGE=$output_image-android-arm-v8a
+            elif [[ ${BUILD_ENVIRONMENT} == *"android-ndk-r19c-x86_32"* ]]; then
+              export COMMIT_DOCKER_IMAGE=$output_image-android-x86_32
+            elif [[ ${BUILD_ENVIRONMENT} == *"android-ndk-r19c-vulkan-x86_32"* ]]; then
+              export COMMIT_DOCKER_IMAGE=$output_image-android-vulkan-x86_32
+            elif [[ ${BUILD_ENVIRONMENT} == *"vulkan-linux"* ]]; then
+              export COMMIT_DOCKER_IMAGE=$output_image-vulkan
+            else
+              export COMMIT_DOCKER_IMAGE=$output_image
+            fi
+            docker commit "$id" ${COMMIT_DOCKER_IMAGE}
+            time docker push ${COMMIT_DOCKER_IMAGE}
+          fi
+    - run:
+        name: upload build & binary data
+        no_output_timeout: "5m"
+        command: |
+            cd /pytorch && export COMMIT_TIME=$(git log --max-count=1 --format=%ct || echo 0)
+            python3 -mpip install requests && \
+            SCRIBE_GRAPHQL_ACCESS_TOKEN=${SCRIBE_GRAPHQL_ACCESS_TOKEN} \
+            python3 -m tools.stats.upload_binary_size_to_scuba || exit 0
+    - store_artifacts:
+        path: /home/circleci/project/dist
+
+  pytorch_linux_test:
+    <<: *pytorch_params
+    machine:
+      image: ubuntu-2004:202104-01
+    steps:
+    # See Note [Workspace for CircleCI scripts] in job-specs-setup.yml
+    - checkout
+    - calculate_docker_image_tag
+    - setup_linux_system_environment
+    - setup_ci_environment
+    - run:
+        name: Download Docker image
+        no_output_timeout: "90m"
+        command: |
+          set -e
+          export PYTHONUNBUFFERED=1
+          if [[ "${DOCKER_IMAGE}" == *rocm3.9* ]]; then
+            export DOCKER_TAG="f3d89a32912f62815e4feaeed47e564e887dffd6"
+          fi
+          # See Note [Special build images]
+          output_image=${DOCKER_IMAGE}:build-${DOCKER_TAG}-${CIRCLE_SHA1}
+          if [[ ${BUILD_ENVIRONMENT} == *"xla"* ]]; then
+            export COMMIT_DOCKER_IMAGE=$output_image-xla
+          elif [[ ${BUILD_ENVIRONMENT} == *"libtorch"* ]]; then
+            export COMMIT_DOCKER_IMAGE=$output_image-libtorch
+          elif [[ ${BUILD_ENVIRONMENT} == *"paralleltbb"* ]]; then
+            export COMMIT_DOCKER_IMAGE=$output_image-paralleltbb
+          elif [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
+            export COMMIT_DOCKER_IMAGE=$output_image-parallelnative
+          elif [[ ${BUILD_ENVIRONMENT} == *"vulkan-linux"* ]]; then
+            export COMMIT_DOCKER_IMAGE=$output_image-vulkan
+          else
+            export COMMIT_DOCKER_IMAGE=$output_image
+          fi
+          echo "DOCKER_IMAGE: "${COMMIT_DOCKER_IMAGE}
+
+          if [[ ${BUILD_ENVIRONMENT} == *"paralleltbb"* ]]; then
+            echo 'ATEN_THREADING=TBB' >> "${BASH_ENV}"
+            echo 'USE_TBB=1' >> "${BASH_ENV}"
+          elif [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
+            echo 'ATEN_THREADING=NATIVE' >> "${BASH_ENV}"
+          fi
+          echo "Parallel backend flags: "${PARALLEL_FLAGS}
+
+          time docker pull ${COMMIT_DOCKER_IMAGE} >/dev/null
+
+          # TODO: Make this less painful
+          if [ -n "${USE_CUDA_DOCKER_RUNTIME}" ]; then
+            export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --gpus all --shm-size=2g -t -d -w /var/lib/jenkins ${COMMIT_DOCKER_IMAGE})
+          elif [[ ${BUILD_ENVIRONMENT} == *"rocm"* ]]; then
+            hostname
+            export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --shm-size=8g --ipc=host --device /dev/kfd --device /dev/dri --group-add video -t -d -w /var/lib/jenkins ${COMMIT_DOCKER_IMAGE})
+          else
+            export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --shm-size=1g --ipc=host -t -d -w /var/lib/jenkins ${COMMIT_DOCKER_IMAGE})
+          fi
+          echo "id=${id}" >> "${BASH_ENV}"
+
+    - run:
+        name: Check for no AVX instruction by default
+        no_output_timeout: "20m"
+        command: |
+          set -e
+          is_vanilla_build() {
+            if [ "${BUILD_ENVIRONMENT}" == "pytorch-linux-bionic-py3.6-clang9-test" ]; then
+              return 0
+            fi
+            if [ "${BUILD_ENVIRONMENT}" == "pytorch-linux-xenial-py3.6-gcc5.4-test" ]; then
+              return 0
+            fi
+            return 1
+          }
+
+          if is_vanilla_build; then
+            echo "apt-get update || apt-get install libgnutls30" | docker exec -u root -i "$id" bash
+            echo "apt-get install -y qemu-user gdb" | docker exec -u root -i "$id" bash
+            echo "cd workspace/build; qemu-x86_64 -g 2345 -cpu Broadwell -E ATEN_CPU_CAPABILITY=default ./bin/basic --gtest_filter=BasicTest.BasicTestCPU & gdb ./bin/basic -ex 'set pagination off' -ex 'target remote :2345' -ex 'continue' -ex 'bt' -ex='set confirm off' -ex 'quit \$_isvoid(\$_exitcode)'" | docker exec -u jenkins -i "$id" bash
+          else
+            echo "Skipping for ${BUILD_ENVIRONMENT}"
+          fi
+    - run:
+        name: Test
+        no_output_timeout: "90m"
+        command: |
+          set -e
+
+          cat >docker_commands.sh \<<EOL
+          # =================== The following code will be executed inside Docker container ===================
+          set -ex
+          export SCRIBE_GRAPHQL_ACCESS_TOKEN="${SCRIBE_GRAPHQL_ACCESS_TOKEN}"
+          export JOB_BASE_NAME="$CIRCLE_JOB"
+          # temporary fix for https://github.com/pytorch/pytorch/issues/60746
+          if [ -z "$CIRCLE_PR_NUMBER" ]; then
+            if [[ $CIRCLE_BRANCH =~ .*pull.* ]]; then
+              export PR_NUMBER="$(echo $CIRCLE_BRANCH | sed 's/[^0-9]//g')"
+              export CIRCLE_PR_NUMBER="$PR_NUMBER"
+            fi
+          else
+            export PR_NUMBER="$CIRCLE_PR_NUMBER"
+          fi
+          ${PARALLEL_FLAGS}
+          cd workspace
+          EOL
+          if [[ ${BUILD_ENVIRONMENT} == *"multigpu"* ]]; then
+            echo ".jenkins/pytorch/multigpu-test.sh" >> docker_commands.sh
+          elif [[ ${BUILD_ENVIRONMENT} == *onnx* ]]; then
+            echo "pip install click mock tabulate networkx==2.0" >> docker_commands.sh
+            echo "pip -q install --user \"file:///var/lib/jenkins/workspace/third_party/onnx#egg=onnx\"" >> docker_commands.sh
+            echo ".jenkins/caffe2/test.sh" >> docker_commands.sh
+          else
+            echo ".jenkins/pytorch/test.sh" >> docker_commands.sh
+          fi
+          echo "(cat docker_commands.sh | docker exec -u jenkins -i "$id" bash) 2>&1" > command.sh
+          unbuffer bash command.sh | ts
+
+          if [[ ${BUILD_ENVIRONMENT} == *"coverage"* ]]; then
+              echo "Retrieving C++ coverage report"
+              docker cp $id:/var/lib/jenkins/workspace/build/coverage.info ./test
+          fi
+          if [[ ${BUILD_ENVIRONMENT} == *"coverage"* || ${BUILD_ENVIRONMENT} == *"onnx"* ]]; then
+              echo "Retrieving Python coverage report"
+              docker cp $id:/var/lib/jenkins/workspace/test/.coverage ./test
+              docker cp $id:/var/lib/jenkins/workspace/test/coverage.xml ./test
+              python3 -mpip install codecov
+              python3 -mcodecov
+          fi
+    - run:
+        name: Report results
+        no_output_timeout: "5m"
+        command: |
+          set -e
+          # Retrieving test results should be done as very first step as command never fails
+          # But is always executed if previous step fails for some reason
+          echo "Retrieving test reports"
+          docker cp $id:/var/lib/jenkins/workspace/test/test-reports ./ || echo 'No test reports found!'
+          docker stats --all --no-stream
+
+          cat >docker_commands.sh \<<EOL
+          # =================== The following code will be executed inside Docker container ===================
+          set -ex
+          export BUILD_ENVIRONMENT=${BUILD_ENVIRONMENT}
+          export SCRIBE_GRAPHQL_ACCESS_TOKEN="${SCRIBE_GRAPHQL_ACCESS_TOKEN}"
+          export CIRCLE_TAG="${CIRCLE_TAG:-}"
+          export CIRCLE_SHA1="$CIRCLE_SHA1"
+          export CIRCLE_PR_NUMBER="${CIRCLE_PR_NUMBER:-}"
+          export CIRCLE_BRANCH="$CIRCLE_BRANCH"
+          export JOB_BASE_NAME="$CIRCLE_JOB"
+          export CIRCLE_WORKFLOW_ID="$CIRCLE_WORKFLOW_ID"
+          cd workspace
+          python -m tools.stats.print_test_stats --upload-to-s3 --compare-with-s3 test
+          EOL
+          echo "(cat docker_commands.sh | docker exec -u jenkins -e LANG=C.UTF-8 -i "$id" bash) 2>&1" > command.sh
+          unbuffer bash command.sh | ts
+        when: always
+    - store_test_results:
+        path: test-reports
+    - store_artifacts:
+        path: test/.coverage
+    - store_artifacts:
+        path: test/coverage.xml
+
+  pytorch_windows_build:
+    <<: *pytorch_windows_params
+    parameters:
+      executor:
+        type: string
+        default: "windows-xlarge-cpu-with-nvidia-cuda"
+      build_environment:
+        type: string
+        default: ""
+      test_name:
+        type: string
+        default: ""
+      cuda_version:
+        type: string
+        default: "10.1"
+      python_version:
+        type: string
+        default: "3.8"
+      vs_version:
+        type: string
+        default: "16.8.6"
+      vc_version:
+        type: string
+        default: "14.16"
+      vc_year:
+        type: string
+        default: "2019"
+      vc_product:
+        type: string
+        default: "BuildTools"
+      use_cuda:
+        type: string
+        default: ""
+    executor: <<parameters.executor>>
+    steps:
+      - checkout
+      - run:
+          name: Install VS2019 toolchain
+          no_output_timeout: 10m
+          command: |
+              powershell .circleci/scripts/vs_install.ps1
+      - run:
+          name: Install Cuda
+          no_output_timeout: 30m
+          command: |
+            if [[ "${USE_CUDA}" == "1" ]]; then
+              .circleci/scripts/windows_cuda_install.sh
+            fi
+      - run:
+          name: Install Cudnn
+          command : |
+            if [[ "${USE_CUDA}" == "1" ]]; then
+              .circleci/scripts/windows_cudnn_install.sh
+            fi
+      - run:
+          name: Build
+          no_output_timeout: "90m"
+          command: |
+            set -e
+            set +x
+            export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_WIN_BUILD_V1}
+            export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_WIN_BUILD_V1}
+            set -x
+            .jenkins/pytorch/win-build.sh
+      - persist_to_workspace:
+          root: "C:/w"
+          paths: build-results
+      - store_artifacts:
+          path: C:/w/build-results
+
+  pytorch_windows_test:
+    <<: *pytorch_windows_params
+    parameters:
+      executor:
+        type: string
+        default: "windows-medium-cpu-with-nvidia-cuda"
+      build_environment:
+        type: string
+        default: ""
+      test_name:
+        type: string
+        default: ""
+      cuda_version:
+        type: string
+        default: "10.1"
+      python_version:
+        type: string
+        default: "3.8"
+      vs_version:
+        type: string
+        default: "16.8.6"
+      vc_version:
+        type: string
+        default: "14.16"
+      vc_year:
+        type: string
+        default: "2019"
+      vc_product:
+        type: string
+        default: "BuildTools"
+      use_cuda:
+        type: string
+        default: ""
+    executor: <<parameters.executor>>
+    steps:
+      - checkout
+      - attach_workspace:
+          at: c:/users/circleci/workspace
+      - run:
+          name: Install VS2019 toolchain
+          no_output_timeout: 10m
+          command: |
+              powershell .circleci/scripts/vs_install.ps1
+      - run:
+          name: Install Cuda
+          no_output_timeout: 30m
+          command: |
+            if [[ "${CUDA_VERSION}" != "cpu" ]]; then
+              if [[ "${CUDA_VERSION}" != "10" || "${JOB_EXECUTOR}" != "windows-with-nvidia-gpu" ]]; then
+                .circleci/scripts/windows_cuda_install.sh
+              fi
+            fi
+      - run:
+          name: Install Cudnn
+          command : |
+            if [[ "${CUDA_VERSION}" != "cpu" ]]; then
+              .circleci/scripts/windows_cudnn_install.sh
+            fi
+      - run:
+          name: Test
+          no_output_timeout: "30m"
+          command: |
+            set -e
+            export IN_CI=1
+            set +x
+            export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_WIN_BUILD_V1}
+            export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_WIN_BUILD_V1}
+            set -x
+            .jenkins/pytorch/win-test.sh
+      - run:
+          name: Report results
+          no_output_timeout: "5m"
+          command: |
+            set -ex
+            export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_WIN_BUILD_V1}
+            export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_WIN_BUILD_V1}
+            pip install typing_extensions boto3
+            python -m tools.stats.print_test_stats --upload-to-s3 --compare-with-s3 test
+          when: always
+      - store_test_results:
+          path: test/test-reports
+      - store_artifacts:
+          path: test/coverage.xml

.circleci/verbatim-sources/nightly-binary-build-defaults.yml

@@ -26,7 +26,6 @@
 # (smoke tests and upload jobs do not need the pytorch repo).
 binary_checkout: &binary_checkout
   name: Checkout pytorch/builder repo
-  no_output_timeout: "30m"
   command: .circleci/scripts/binary_checkout.sh
 
 # Parses circleci arguments in a consistent way, essentially routing to the

.circleci/verbatim-sources/workflows/workflows-ecr-gc.yml

@@ -0,0 +1,34 @@
+  ecr_gc:
+    triggers:
+      - schedule:
+          cron: "45 * * * *"
+          filters:
+            branches:
+              only:
+                - master
+    jobs:
+      - docker_for_ecr_gc_build_job
+      - ecr_gc_job:
+            name: ecr_gc_job_for_pytorch
+            project: pytorch
+            tags_to_keep: "271,262,256,278,282,291,300,323,327,347,389,401,402,403,405,a8006f9a-272d-4478-b137-d121c6f05c83,6e7b11da-a919-49e5-b2ba-da66e3d4bb0a,f990c76a-a798-42bb-852f-5be5006f8026,e43973a9-9d5a-4138-9181-a08a0fc55e2f,8fcf46ef-4a34-480b-a8ee-b0a30a4d3e59,9a3986fa-7ce7-4a36-a001-3c9bef9892e2,1bc00f11-e0f3-4e5c-859f-15937dd938cd,209062ef-ab58-422a-b295-36c4eed6e906,be76e8fd-44e2-484d-b090-07e0cc3a56f0,fff7795428560442086f7b2bb6004b65245dc11a,ab1632df-fa59-40e6-8c23-98e004f61148"
+            requires:
+              - docker_for_ecr_gc_build_job
+      - ecr_gc_job:
+            name: ecr_gc_job_for_caffe2
+            project: caffe2
+            tags_to_keep: "376,373,369,348,345,336,325,324,315,306,301,287,283,276,273,266,253,248,238,230,213"
+            requires:
+              - docker_for_ecr_gc_build_job
+      - ecr_gc_job:
+            name: ecr_gc_job_for_translate
+            project: translate
+            tags_to_keep: "8"
+            requires:
+              - docker_for_ecr_gc_build_job
+      - ecr_gc_job:
+            name: ecr_gc_job_for_tensorcomp
+            project: tensorcomp
+            tags_to_keep: "34"
+            requires:
+              - docker_for_ecr_gc_build_job

.circleci/verbatim-sources/workflows/workflows-promote.yml

@@ -0,0 +1,46 @@
+  # Promotion workflow
+  promote:
+    jobs:
+      # Requires manual approval by someone in org-member
+      # CircleCI security context
+      - promote_approval:
+          context: org-member
+          filters:
+            branches:
+              ignore: /.*/
+            tags:
+              only: /v[0-9]+(\.[0-9]+)*/
+          type: approval
+      - promote_s3:
+          context: org-member
+          filters:
+            branches:
+              ignore: /.*/
+            tags:
+              only: /v[0-9]+(\.[0-9]+)*/
+          name: promote_s3_libtorch
+          package_name: libtorch
+          requires:
+            - promote_approval
+      - promote_s3:
+          context: org-member
+          filters:
+            branches:
+              ignore: /.*/
+            tags:
+              only: /v[0-9]+(\.[0-9]+)*/
+          name: promote_s3_torch
+          package_name: torch
+          requires:
+            - promote_approval
+      - promote_conda:
+          context: org-member
+          filters:
+            branches:
+              ignore: /.*/
+            tags:
+              only: /v[0-9]+(\.[0-9]+)*/
+          name: promote_conda_pytorch
+          package_name: pytorch
+          requires:
+            - promote_approval

.circleci/verbatim-sources/workflows/workflows-scheduled-ci.yml

@@ -0,0 +1,37 @@
+  # the following clones pytorch_linux_xenial_cuda10_2_cudnn7_py3_gcc7's tests but enables
+  # slow tests and sets an environment variable so gradcheck runs with fast_mode=False
+  slow-gradcheck-scheduled-ci:
+    triggers:
+      - schedule:
+          # runs every 8 hours on the 45th minute
+          cron: "45 0,8,16 * * *"
+          filters:
+            branches:
+              only:
+                - master
+    jobs:
+      - docker_build_job:
+          name: "docker-pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7"
+          image_name: "pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7"
+      - pytorch_linux_build:
+          name: periodic_pytorch_xenial_cuda10_2_cudnn7_gcc7_build
+          requires:
+            - "docker-pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7"
+          build_environment: "pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7-build"
+          docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7"
+      - pytorch_linux_test:
+          name: periodic_pytorch_xenial_cuda10_2_cudnn7_gcc7_old_gradcheck_test1
+          requires:
+            - periodic_pytorch_xenial_cuda10_2_cudnn7_gcc7_build
+          build_environment: "pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7-old-gradcheck-test1"
+          docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7"
+          use_cuda_docker_runtime: "1"
+          resource_class: gpu.medium
+      - pytorch_linux_test:
+          name: periodic_pytorch_xenial_cuda10_2_cudnn7_gcc7_old_gradcheck_test2
+          requires:
+            - periodic_pytorch_xenial_cuda10_2_cudnn7_gcc7_build
+          build_environment: "pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7-old-gradcheck-test2"
+          docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7"
+          use_cuda_docker_runtime: "1"
+          resource_class: gpu.medium

.clang-tidy

@@ -33,12 +33,11 @@ modernize-*,
 -modernize-use-default-member-init,
 -modernize-use-using,
 -modernize-use-trailing-return-type,
--modernize-use-nodiscard,
 performance-*,
 -performance-noexcept-move-constructor,
 -performance-unnecessary-value-param,
 '
-HeaderFilterRegex: 'torch/csrc/(?!deploy/interpreter/cpython).*'
+HeaderFilterRegex: 'torch/csrc/.*'
 AnalyzeTemporaryDtors: false
 WarningsAsErrors: '*'
 CheckOptions: