Disable autocast cache for tensor views as fix for #48049 (#48696) (#48936)

Co-authored-by: pbialecki <pbialecki@nvidia.com>

.bazelrc

@@ -1,115 +1,3 @@
-build --cxxopt=--std=c++14
+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
-# 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

.bazelversion

@@ -1 +1 @@
-4.2.1
+3.1.0

.buckconfig.oss

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-[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

@@ -0,0 +1,499 @@
+Structure of CI
+===============
+
+setup job:
+1. Does a git checkout
+2. Persists CircleCI scripts (everything in `.circleci`) into a workspace.  Why?
+   We don't always do a Git checkout on all subjobs, but we usually
+   still want to be able to call scripts one way or another in a subjob.
+   Persisting files this way lets us have access to them without doing a
+   checkout.  This workspace is conventionally mounted on `~/workspace`
+   (this is distinguished from `~/project`, which is the conventional
+   working directory that CircleCI will default to starting your jobs
+   in.)
+3. Write out the commit message to `.circleci/COMMIT_MSG`.  This is so
+   we can determine in subjobs if we should actually run the jobs or
+   not, even if there isn't a Git checkout.
+
+
+
+
+CircleCI configuration generator
+================================
+
+One may no longer make changes to the `.circleci/config.yml` file directly.
+Instead, one must edit these Python scripts or files in the `verbatim-sources/` directory.
+
+
+Usage
+----------
+
+1. Make changes to these scripts.
+2. Run the `regenerate.sh` script in this directory and commit the script changes and the resulting change to `config.yml`.
+
+You'll see a build failure on TravisCI if the scripts don't agree with the checked-in version.
+
+
+Motivation
+----------
+
+These scripts establish a single, authoritative source of documentation for the CircleCI configuration matrix.
+The documentation, in the form of diagrams, is automatically generated and cannot drift out of sync with the YAML content.
+
+Furthermore, consistency is enforced within the YAML config itself, by using a single source of data to generate
+multiple parts of the file.
+
+* Facilitates one-off culling/enabling of CI configs for testing PRs on special targets
+
+Also see https://github.com/pytorch/pytorch/issues/17038
+
+
+Future direction
+----------------
+
+### Declaring sparse config subsets
+See comment [here](https://github.com/pytorch/pytorch/pull/17323#pullrequestreview-206945747):
+
+In contrast with a full recursive tree traversal of configuration dimensions,
+> in the future 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.
+
+----------------
+----------------
+
+# How do the binaries / nightlies / releases work?
+
+### What is a binary?
+
+A binary or package (used interchangeably) is a pre-built collection of c++ libraries, header files, python bits, and other files. We build these and distribute them so that users do not need to install from source.
+
+A **binary configuration** is a collection of
+
+* release or nightly
+    * releases are stable, nightlies are beta and built every night
+* python version
+    * 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
+* operating system
+    * Linux - these are all built on CentOS. There haven't been any problems in the past building on CentOS and using on Ubuntu
+    * MacOS
+    * Windows - these are built on Azure pipelines
+* devtoolset version (gcc compiler version)
+    * This only matters on Linux cause only Linux uses gcc. tldr is gcc made a backwards incompatible change from gcc 4.8 to gcc 5, because it had to change how it implemented std::vector and std::string
+
+### Where are the binaries?
+
+The binaries are built in CircleCI. There are nightly binaries built every night at 9pm PST (midnight EST) and release binaries corresponding to Pytorch releases, usually every few months.
+
+We have 3 types of binary packages
+
+* pip packages - nightlies are stored on s3 (pip install -f <a s3 url>). releases are stored in a pip repo (pip install torch) (ask Soumith about this)
+* conda packages - nightlies and releases are both stored in a conda repo. Nighty packages have a '_nightly' suffix
+* libtorch packages - these are zips of all the c++ libraries, header files, and sometimes dependencies. These are c++ only
+    * shared with dependencies (the only supported option for Windows)
+    * static with dependencies
+    * shared without dependencies
+    * static without dependencies
+
+All binaries are built in CircleCI workflows except Windows. There are checked-in workflows (committed into the .circleci/config.yml) to build the nightlies every night. Releases are built by manually pushing a PR that builds the suite of release binaries (overwrite the config.yml to build the release)
+
+# CircleCI structure of the binaries
+
+Some quick vocab:
+
+* A\**workflow** is a CircleCI concept; it is a DAG of '**jobs**'. ctrl-f 'workflows' on\https://github.com/pytorch/pytorch/blob/master/.circleci/config.yml to see the workflows.
+* **jobs** are a sequence of '**steps**'
+* **steps** are usually just a bash script or a builtin CircleCI command.* All steps run in new environments, environment variables declared in one script DO NOT persist to following steps*
+* CircleCI has a **workspace**, which is essentially a cache between steps of the *same job* in which you can store artifacts between steps.
+
+## How are the workflows structured?
+
+The nightly binaries have 3 workflows. We have one job (actually 3 jobs:  build, test, and upload) per binary configuration
+
+1. binarybuilds
+    1. every day midnight EST
+    2. linux: https://github.com/pytorch/pytorch/blob/master/.circleci/verbatim-sources/linux-binary-build-defaults.yml
+    3. macos: https://github.com/pytorch/pytorch/blob/master/.circleci/verbatim-sources/macos-binary-build-defaults.yml
+    4. For each binary configuration, e.g. linux_conda_3.7_cpu there is a
+        1. binary_linux_conda_3.7_cpu_build
+            1. Builds the build. On linux jobs this uses the 'docker executor'.
+            2. Persists the package to the workspace
+        2. binary_linux_conda_3.7_cpu_test
+            1. Loads the package to the workspace
+            2. Spins up a docker image (on Linux), mapping the package and code repos into the docker
+            3. Runs some smoke tests in the docker
+            4. (Actually, for macos this is a step rather than a separate job)
+        3. binary_linux_conda_3.7_cpu_upload
+            1. Logs in to aws/conda
+            2. Uploads the package
+2. update_s3_htmls
+    1. every day 5am EST
+    2. https://github.com/pytorch/pytorch/blob/master/.circleci/verbatim-sources/binary_update_htmls.yml
+    3. See below for what these are for and why they're needed
+    4. Three jobs that each examine the current contents of aws and the conda repo and update some html files in s3
+3. binarysmoketests
+    1. every day
+    2. https://github.com/pytorch/pytorch/blob/master/.circleci/verbatim-sources/nightly-build-smoke-tests-defaults.yml
+    3. For each binary configuration, e.g. linux_conda_3.7_cpu there is a
+        1. smoke_linux_conda_3.7_cpu
+            1. Downloads the package from the cloud, e.g. using the official pip or conda instructions
+            2. Runs the smoke tests
+
+## How are the jobs structured?
+
+The jobs are in https://github.com/pytorch/pytorch/tree/master/.circleci/verbatim-sources . Jobs are made of multiple steps. There are some shared steps used by all the binaries/smokes. Steps of these jobs are all delegated to scripts in https://github.com/pytorch/pytorch/tree/master/.circleci/scripts .
+
+* Linux jobs: https://github.com/pytorch/pytorch/blob/master/.circleci/verbatim-sources/linux-binary-build-defaults.yml
+    * binary_linux_build.sh
+    * binary_linux_test.sh
+    * binary_linux_upload.sh
+* MacOS jobs: https://github.com/pytorch/pytorch/blob/master/.circleci/verbatim-sources/macos-binary-build-defaults.yml
+    * binary_macos_build.sh
+    * binary_macos_test.sh
+    * binary_macos_upload.sh
+* Update html jobs: https://github.com/pytorch/pytorch/blob/master/.circleci/verbatim-sources/binary_update_htmls.yml
+    * These delegate from the pytorch/builder repo
+    * https://github.com/pytorch/builder/blob/master/cron/update_s3_htmls.sh
+    * https://github.com/pytorch/builder/blob/master/cron/upload_binary_sizes.sh
+* Smoke jobs (both linux and macos): https://github.com/pytorch/pytorch/blob/master/.circleci/verbatim-sources/nightly-build-smoke-tests-defaults.yml
+    * These delegate from the pytorch/builder repo
+    * https://github.com/pytorch/builder/blob/master/run_tests.sh
+    * https://github.com/pytorch/builder/blob/master/smoke_test.sh
+    * https://github.com/pytorch/builder/blob/master/check_binary.sh
+* Common shared code (shared across linux and macos): https://github.com/pytorch/pytorch/blob/master/.circleci/verbatim-sources/nightly-binary-build-defaults.yml
+    * binary_checkout.sh - checks out pytorch/builder repo. Right now this also checks out pytorch/pytorch, but it shouldn't. pytorch/pytorch should just be shared through the workspace. This can handle being run before binary_populate_env.sh
+    * binary_populate_env.sh - parses BUILD_ENVIRONMENT into the separate env variables that make up a binary configuration. Also sets lots of default values, the date, the version strings, the location of folders in s3, all sorts of things. This generally has to be run before other steps.
+    * binary_install_miniconda.sh - Installs miniconda, cross platform. Also hacks this for the update_binary_sizes job that doesn't have the right env variables
+    * binary_run_in_docker.sh - Takes a bash script file (the actual test code) from a hardcoded location, spins up a docker image, and runs the script inside the docker image
+
+### **Why do the steps all refer to scripts?**
+
+CircleCI creates a  final yaml file by inlining every <<* segment, so if we were to keep all the code in the config.yml itself then the config size would go over 4 MB and cause infra problems.
+
+### **What is binary_run_in_docker for?**
+
+So, CircleCI has several executor types: macos, machine, and docker are the ones we use. The 'machine' executor gives you two cores on some linux vm. The 'docker' executor gives you considerably more cores (nproc was 32 instead of 2 back when I tried in February). Since the dockers are faster, we try to run everything that we can in dockers. Thus
+
+* linux build jobs use the docker executor. Running them on the docker executor was at least 2x faster than running them on the machine executor
+* linux test jobs use the machine executor in order for them to properly interface with GPUs since docker executors cannot execute with attached GPUs
+* linux upload jobs use the machine executor. The upload jobs are so short that it doesn't really matter what they use
+* linux smoke test jobs use the machine executor for the same reason as the linux test jobs
+
+binary_run_in_docker.sh is a way to share the docker start-up code between the binary test jobs and the binary smoke test jobs
+
+### **Why does binary_checkout also checkout pytorch? Why shouldn't it?**
+
+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
+
+The code that runs the binaries lives in two places, in the normal [github.com/pytorch/pytorch](http://github.com/pytorch/pytorch), but also in [github.com/pytorch/builder](http://github.com/pytorch/builder) , which is a repo that defines how all the binaries are built. The relevant code is
+
+
+```
+# All code needed to set-up environments for build code to run in,
+# but only code that is specific to the current CI system
+pytorch/pytorch
+- .circleci/                # Folder that holds all circleci related stuff
+  - 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
+  - pytorch-nightly/          # Build-folder
+- manywheel/
+  - build_cpu.sh              # Entrypoint for cpu builds
+  - build.sh                  # Entrypoint for CUDA builds
+  - build_common.sh           # Actual build script that ^^ call into
+- wheel/
+  - build_wheel.sh            # Entrypoint for wheel builds
+- windows/
+  - build_pytorch.bat         # Entrypoint for wheel builds on Windows
+```
+
+Every type of package has an entrypoint build script that handles the all the important logic.
+
+## Conda
+
+Linux, MacOS and Windows use the same code flow for the conda builds.
+
+Conda packages are built with conda-build, see https://conda.io/projects/conda-build/en/latest/resources/commands/conda-build.html
+
+Basically, you pass `conda build` a build folder (pytorch-nightly/ above) that contains a build script and a meta.yaml. The meta.yaml specifies in what python environment to build the package in, and what dependencies the resulting package should have, and the build script gets called in the env to build the thing.
+tldr; on conda-build is
+
+1. Creates a brand new conda environment, based off of deps in the meta.yaml
+    1. Note that environment variables do not get passed into this build env unless they are specified in the meta.yaml
+    2. If the build fails this environment will stick around. You can activate it for much easier debugging. The “General Python” section below explains what exactly a python “environment” is.
+2. Calls build.sh in the environment
+3. Copies the finished package to a new conda env, also specified by the meta.yaml
+4. Runs some simple import tests (if specified in the meta.yaml)
+5. Saves the finished package as a tarball
+
+The build.sh we use is essentially a wrapper around ```python setup.py build``` , but it also manually copies in some of our dependent libraries into the resulting tarball and messes with some rpaths.
+
+The entrypoint file `builder/conda/build_conda.sh` is complicated because
+
+* It works for Linux, MacOS and Windows
+    * The mac builds used to create their own environments, since they all used to be on the same machine. There’s now a lot of extra logic to handle conda envs. This extra machinery could be removed
+* It used to handle testing too, which adds more logic messing with python environments too. This extra machinery could be removed.
+
+## Manywheels (linux pip and libtorch packages)
+
+Manywheels are pip packages for linux distros. Note that these manywheels are not actually manylinux compliant.
+
+`builder/manywheel/build_cpu.sh` and `builder/manywheel/build.sh` (for CUDA builds) just set different env vars and then call into `builder/manywheel/build_common.sh`
+
+The entrypoint file `builder/manywheel/build_common.sh` is really really complicated because
+
+* This used to handle building for several different python versions at the same time. The loops have been removed, but there's still unnecessary folders and movements here and there.
+    * The script is never used this way anymore. This extra machinery could be removed.
+* This used to handle testing the pip packages too. This is why there’s testing code at the end that messes with python installations and stuff
+    * The script is never used this way anymore. This extra machinery could be removed.
+* This also builds libtorch packages
+    * This should really be separate. libtorch packages are c++ only and have no python. They should not share infra with all the python specific stuff in this file.
+* There is a lot of messing with rpaths. This is necessary, but could be made much much simpler if the above issues were fixed.
+
+## Wheels (MacOS pip and libtorch packages)
+
+The entrypoint file `builder/wheel/build_wheel.sh` is complicated because
+
+* The mac builds used to all run on one machine (we didn’t have autoscaling mac machines till circleci). So this script handled siloing itself by setting-up and tearing-down its build env and siloing itself into its own build directory.
+    * The script is never used this way anymore. This extra machinery could be removed.
+* This also builds libtorch packages
+    * Ditto the comment above. This should definitely be separated out.
+
+Note that the MacOS Python wheels are still built in conda environments. Some of the dependencies present during build also come from conda.
+
+## Windows Wheels (Windows pip and libtorch packages)
+
+The entrypoint file `builder/windows/build_pytorch.bat` is complicated because
+
+* This used to handle building for several different python versions at the same time. This is why there are loops everywhere
+    * The script is never used this way anymore. This extra machinery could be removed.
+* This used to handle testing the pip packages too. This is why there’s testing code at the end that messes with python installations and stuff
+    * The script is never used this way anymore. This extra machinery could be removed.
+* This also builds libtorch packages
+    * This should really be separate. libtorch packages are c++ only and have no python. They should not share infra with all the python specific stuff in this file.
+
+Note that the Windows Python wheels are still built in conda environments. Some of the dependencies present during build also come from conda.
+
+## General notes
+
+### Note on run_tests.sh, smoke_test.sh, and check_binary.sh
+
+* These should all be consolidated
+* These must run on all OS types: MacOS, Linux, and Windows
+* These all run smoke tests at the moment. They inspect the packages some, maybe run a few import statements. They DO NOT run the python tests nor the cpp tests. The idea is that python tests on master and PR merges will catch all breakages. All these tests have to do is make sure the special binary machinery didn’t mess anything up.
+* There are separate run_tests.sh and smoke_test.sh because one used to be called by the smoke jobs and one used to be called by the binary test jobs (see circleci structure section above). This is still true actually, but these could be united into a single script that runs these checks, given an installed pytorch package.
+
+### Note on libtorch
+
+Libtorch packages are built in the wheel build scripts: manywheel/build_*.sh for linux and build_wheel.sh for mac. There are several things wrong with this
+
+* It’s confusing. Most of those scripts deal with python specifics.
+* The extra conditionals everywhere severely complicate the wheel build scripts
+* The process for building libtorch is different from the official instructions (a plain call to cmake, or a call to a script)
+
+### Note on docker images / Dockerfiles
+
+All linux builds occur in docker images. The docker images are
+
+* pytorch/conda-cuda
+    * Has ALL CUDA versions installed. The script pytorch/builder/conda/switch_cuda_version.sh sets /usr/local/cuda to a symlink to e.g. /usr/local/cuda-10.0 to enable different CUDA builds
+    * Also used for cpu builds
+* pytorch/manylinux-cuda90
+* pytorch/manylinux-cuda92
+* pytorch/manylinux-cuda100
+    * Also used for cpu builds
+
+The Dockerfiles are available in pytorch/builder, but there is no circleci job or script to build these docker images, and they cannot be run locally (unless you have the correct local packages/paths). Only Soumith can build them right now.
+
+### General Python
+
+* This is still a good explanation of python installations https://caffe2.ai/docs/faq.html#why-do-i-get-import-errors-in-python-when-i-try-to-use-caffe2
+
+# How to manually rebuild the binaries
+
+tldr; make a PR that looks like https://github.com/pytorch/pytorch/pull/21159
+
+Sometimes we want to push a change to master and then rebuild all of today's binaries after that change. As of May 30, 2019 there isn't a way to manually run a workflow in the UI. You can manually re-run a workflow, but it will use the exact same git commits as the first run and will not include any changes. So we have to make a PR and then force circleci to run the binary workflow instead of the normal tests. The above PR is an example of how to do this; essentially you copy-paste the binarybuilds workflow steps into the default workflow steps. If you need to point the builder repo to a different commit then you'd need to change https://github.com/pytorch/pytorch/blob/master/.circleci/scripts/binary_checkout.sh#L42-L45 to checkout what you want.
+
+## How to test changes to the binaries via .circleci
+
+Writing PRs that test the binaries is annoying, since the default circleci jobs that run on PRs are not the jobs that you want to run. Likely, changes to the binaries will touch something under .circleci/ and require that .circleci/config.yml be regenerated (.circleci/config.yml controls all .circleci behavior, and is generated using ```.circleci/regenerate.sh``` in python 3.7). But you also need to manually hardcode the binary jobs that you want to test into the .circleci/config.yml workflow, so you should actually make at least two commits, one for your changes and one to temporarily hardcode jobs. See https://github.com/pytorch/pytorch/pull/22928 as an example of how to do this.
+
+```
+# 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
+```
+
+The advantage of this flow is that you can make new changes to the base commit and regenerate the .circleci without having to re-write which binary jobs you want to test on. The downside is that all updates will be force pushes.
+
+## How to build a binary locally
+
+### Linux
+
+You can build Linux binaries locally easily using docker.
+
+```
+# Run the docker
+# Use the correct docker image, pytorch/conda-cuda used here as an example
+#
+# -v path/to/foo:path/to/bar makes path/to/foo on your local machine (the
+#    machine that you're running the command on) accessible to the docker
+#    container at path/to/bar. So if you then run `touch path/to/bar/baz`
+#    in the docker container then you will see path/to/foo/baz on your local
+#    machine. You could also clone the pytorch and builder repos in the docker.
+#
+# If you know how, add ccache as a volume too and speed up everything
+docker run \
+    -v your/pytorch/repo:/pytorch \
+    -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=3.6
+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
+# building locally.
+/builder/conda/build_pytorch.sh |& tee build_output.log
+```
+
+**Building CUDA binaries on docker**
+
+You can build CUDA binaries on CPU only machines, but you can only run CUDA binaries on CUDA machines. This means that you can build a CUDA binary on a docker on your laptop if you so choose (though it’s gonna take a long time).
+
+For Facebook employees, ask about beefy machines that have docker support and use those instead of your laptop; it will be 5x as fast.
+
+### MacOS
+
+There’s no easy way to generate reproducible hermetic MacOS environments. If you have a Mac laptop then you can try emulating the .circleci environments as much as possible, but you probably have packages in /usr/local/, possibly installed by brew, that will probably interfere with the build. If you’re trying to repro an error on a Mac build in .circleci and you can’t seem to repro locally, then my best advice is actually to iterate on .circleci    :/
+
+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
+new_conda="~/my_new_conda"
+conda_sh="$new_conda/install_miniconda.sh"
+curl -o "$conda_sh" https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
+chmod +x "$conda_sh"
+"$conda_sh" -b -p "$MINICONDA_ROOT"
+rm -f "$conda_sh"
+export PATH="~/my_new_conda/bin:$PATH"
+
+# Create a clean python env
+# All MacOS builds use conda to manage the python env and dependencies
+# that are built with, even the pip packages
+conda create -yn binary python=2.7
+conda activate binary
+
+# Export whatever variables are important to you. All variables that you'd
+# possibly need are in .circleci/scripts/binary_populate_env.sh
+# You should probably always export at least these 3 variables
+export PACKAGE_TYPE=conda
+export DESIRED_PYTHON=3.6
+export DESIRED_CUDA=cpu
+
+# Call the entrypoint you want
+path/to/builder/wheel/build_wheel.sh
+```
+
+N.B. installing a brand new miniconda is important. This has to do with how conda installations work. See the “General Python” section above, but tldr; is that
+
+1. You make the ‘conda’ command accessible by prepending `path/to/conda_root/bin` to your PATH.
+2. You make a new env and activate it, which then also gets prepended to your PATH. Now you have `path/to/conda_root/envs/new_env/bin:path/to/conda_root/bin:$PATH`
+3. Now say you (or some code that you ran) call python executable `foo`
+    1. if you installed `foo` in `new_env`, then `path/to/conda_root/envs/new_env/bin/foo` will get called, as expected.
+    2. But if you forgot to installed `foo` in `new_env` but happened to previously install it in your root conda env (called ‘base’), then unix/linux will still find `path/to/conda_root/bin/foo` . This is dangerous, since `foo` can be a different version than you want; `foo` can even be for an incompatible python version!
+
+Newer conda versions and proper python hygiene can prevent this, but just install a new miniconda to be safe.
+
+### Windows
+
+TODO: fill in

.circleci/cimodel/data/binary_build_data.py

@@ -30,7 +30,39 @@ 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",
+        ],
+    )),
+    # Skip CUDA-9.2 builds on Windows
+    windows=(
+        [v for v in dimensions.GPU_VERSIONS if v not in ['cuda92'] + dimensions.ROCM_VERSION_LABELS],
+        OrderedDict(
+            wheel=dimensions.STANDARD_PYTHON_VERSIONS,
+            conda=dimensions.STANDARD_PYTHON_VERSIONS,
+            libtorch=[
+                "3.7",
+            ],
+        )
+    ),
 )
 
 # GCC config variants:
@@ -85,7 +117,6 @@ class PackageFormatConfigNode(ConfigNode):
         self.props["python_versions"] = python_versions
         self.props["package_format"] = package_format
 
-
     def get_children(self):
         if self.find_prop("os_name") == "linux":
             return [LinuxGccConfigNode(self, v) for v in LINUX_GCC_CONFIG_VARIANTS[self.find_prop("package_format")]]

.circleci/cimodel/data/binary_build_definitions.py

@@ -27,19 +27,7 @@ class Conf(object):
 
     def gen_docker_image(self):
         if self.gcc_config_variant == 'gcc5.4_cxx11-abi':
-            if self.gpu_version is None:
-                return miniutils.quote("pytorch/libtorch-cxx11-builder:cpu")
-            else:
-                return miniutils.quote(
-                    f"pytorch/libtorch-cxx11-builder:{self.gpu_version}"
-                )
-        if self.pydistro == "conda":
-            if self.gpu_version is None:
-                return miniutils.quote("pytorch/conda-builder:cpu")
-            else:
-                return miniutils.quote(
-                    f"pytorch/conda-builder:{self.gpu_version}"
-                )
+            return miniutils.quote("pytorch/pytorch-binary-docker-image-ubuntu16.04:latest")
 
         docker_word_substitution = {
             "manywheel": "manylinux",
@@ -124,9 +112,9 @@ class Conf(object):
         Output looks similar to:
 
       - binary_upload:
-          name: binary_linux_manywheel_3_7m_cu113_devtoolset7_nightly_upload
+          name: binary_linux_manywheel_3_7m_cu92_devtoolset7_nightly_upload
           context: org-member
-          requires: binary_linux_manywheel_3_7m_cu113_devtoolset7_nightly_test
+          requires: binary_linux_manywheel_3_7m_cu92_devtoolset7_nightly_test
           filters:
             branches:
               only:
@@ -134,7 +122,7 @@ class Conf(object):
             tags:
               only: /v[0-9]+(\\.[0-9]+)*-rc[0-9]+/
           package_type: manywheel
-          upload_subfolder: cu113
+          upload_subfolder: cu92
         """
         return {
             "binary_upload": OrderedDict({
@@ -176,7 +164,7 @@ def gen_build_env_list(smoke):
             c.find_prop("gpu"),
             c.find_prop("package_format"),
             [c.find_prop("pyver")],
-            c.find_prop("smoke") and not (c.find_prop("os_name") == "macos_arm64"),  # don't test arm64
+            c.find_prop("smoke"),
             c.find_prop("libtorch_variant"),
             c.find_prop("gcc_config_variant"),
             c.find_prop("libtorch_config_variant"),
@@ -228,9 +216,7 @@ def get_jobs(toplevel_key, smoke):
     configs = gen_build_env_list(smoke)
     phase = "build" if toplevel_key == "binarybuilds" else "test"
     for build_config in configs:
-        # don't test for macos_arm64 as it's cross compiled
-        if phase != "test" or build_config.os != "macos_arm64":
-            jobs_list.append(build_config.gen_workflow_job(phase, nightly=True))
+        jobs_list.append(build_config.gen_workflow_job(phase, nightly=True))
 
     return jobs_list
 

.circleci/cimodel/data/dimensions.py

@@ -1,15 +1,15 @@
 PHASES = ["build", "test"]
 
 CUDA_VERSIONS = [
+    "92",
+    "101",
     "102",
-    "113",
-    "116",
-    "117",
+    "110",
 ]
 
 ROCM_VERSIONS = [
-    "4.3.1",
-    "4.5.2",
+    "3.7",
+    "3.8",
 ]
 
 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 +1,89 @@
-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)]),
+                    ("parallel_tbb", [X(True)]),
+                    ("parallel_native", [X(True)]),
+                    ("pure_torch", [X(True)]),
+                ]),
+            ]),
+            # TODO: bring back libtorch test
+            ("7", [X("3.6")]),
+        ]),
+        ("clang", [
+            ("5", [
+                ("3.6", [
+                    ("asan", [XImportant(True)]),
+                ]),
+            ]),
+            ("7", [
+                ("3.6", [
+                    ("onnx", [XImportant(True)]),
+                ]),
+            ]),
+        ]),
+        ("cuda", [
+            ("9.2", [
+                ("3.6", [
+                    X(True),
+                    ("cuda_gcc_override", [
+                        ("gcc5.4", [
+                            ('build_only', [XImportant(True)]),
+                        ]),
+                    ]),
+                ])
+            ]),
+            ("10.1", [
+                ("3.6", [
+                    ('build_only', [X(True)]),
+                ]),
+            ]),
+            ("10.2", [
+                ("3.6", [
+                    ("important", [X(True)]),
+                    ("libtorch", [X(True)]),
+                ]),
+            ]),
+            ("11.0", [
+                ("3.8", [
+                    X(True),
+                    ("libtorch", [XImportant(True)])
+                ]),
+            ]),
+        ]),
+    ]),
+    ("bionic", [
+        ("clang", [
+            ("9", [
+                XImportant("3.6"),
+            ]),
+            ("9", [
+                ("3.6", [
+                    ("xla", [XImportant(True)]),
+                    ("vulkan", [XImportant(True)]),
+                ]),
+            ]),
+        ]),
+        ("gcc", [
+            ("9", [
+                ("3.8", [
+                    ("coverage", [XImportant(True)]),
+                ]),
+            ]),
+        ]),
+        ("rocm", [
+            ("3.7", [
+                ("3.6", [
+                    ('build_only', [XImportant(True)]),
+                ]),
+            ]),
+        ]),
+    ]),
 ]
 
 
@@ -53,8 +135,6 @@ class PyVerConfigNode(TreeConfigNode):
     def init2(self, node_name):
         self.props["pyver"] = node_name
         self.props["abbreviated_pyver"] = get_major_pyver(node_name)
-        if node_name == "3.9":
-            self.props["abbreviated_pyver"] = "py3.9"
 
     # noinspection PyMethodMayBeStatic
     def child_constructor(self):
@@ -71,31 +151,20 @@ class ExperimentalFeatureConfigNode(TreeConfigNode):
         next_nodes = {
             "asan": AsanConfigNode,
             "xla": XlaConfigNode,
-            "mps": MPSConfigNode,
             "vulkan": VulkanConfigNode,
             "parallel_tbb": ParallelTBBConfigNode,
-            "crossref": CrossRefConfigNode,
-            "dynamo": DynamoConfigNode,
             "parallel_native": ParallelNativeConfigNode,
             "onnx": ONNXConfigNode,
             "libtorch": LibTorchConfigNode,
             "important": ImportantConfigNode,
             "build_only": BuildOnlyConfigNode,
-            "shard_test": ShardTestConfigNode,
             "cuda_gcc_override": CudaGccOverrideConfigNode,
+            "coverage": CoverageConfigNode,
             "pure_torch": PureTorchConfigNode,
-            "slow_gradcheck": SlowGradcheckConfigNode,
         }
         return next_nodes[experimental_feature]
 
 
-class SlowGradcheckConfigNode(TreeConfigNode):
-    def init2(self, node_name):
-        self.props["is_slow_gradcheck"] = True
-
-    def child_constructor(self):
-        return ExperimentalFeatureConfigNode
-
 class PureTorchConfigNode(TreeConfigNode):
     def modify_label(self, label):
         return "PURE_TORCH=" + str(label)
@@ -117,16 +186,6 @@ class XlaConfigNode(TreeConfigNode):
     def child_constructor(self):
         return ImportantConfigNode
 
-class MPSConfigNode(TreeConfigNode):
-    def modify_label(self, label):
-        return "MPS=" + str(label)
-
-    def init2(self, node_name):
-        self.props["is_mps"] = node_name
-
-    def child_constructor(self):
-        return ImportantConfigNode
-
 
 class AsanConfigNode(TreeConfigNode):
     def modify_label(self, label):
@@ -136,7 +195,7 @@ class AsanConfigNode(TreeConfigNode):
         self.props["is_asan"] = node_name
 
     def child_constructor(self):
-        return ExperimentalFeatureConfigNode
+        return ImportantConfigNode
 
 
 class ONNXConfigNode(TreeConfigNode):
@@ -172,22 +231,6 @@ class ParallelTBBConfigNode(TreeConfigNode):
         return ImportantConfigNode
 
 
-class CrossRefConfigNode(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
-
-    def child_constructor(self):
-        return ImportantConfigNode
-
-
 class ParallelNativeConfigNode(TreeConfigNode):
     def modify_label(self, label):
         return "PARALLELNATIVE=" + str(label)
@@ -207,7 +250,7 @@ class LibTorchConfigNode(TreeConfigNode):
         self.props["is_libtorch"] = node_name
 
     def child_constructor(self):
-        return ExperimentalFeatureConfigNode
+        return ImportantConfigNode
 
 
 class CudaGccOverrideConfigNode(TreeConfigNode):
@@ -217,8 +260,8 @@ class CudaGccOverrideConfigNode(TreeConfigNode):
     def child_constructor(self):
         return ExperimentalFeatureConfigNode
 
-
 class BuildOnlyConfigNode(TreeConfigNode):
+
     def init2(self, node_name):
         self.props["build_only"] = node_name
 
@@ -226,12 +269,13 @@ class BuildOnlyConfigNode(TreeConfigNode):
         return ExperimentalFeatureConfigNode
 
 
-class ShardTestConfigNode(TreeConfigNode):
+class CoverageConfigNode(TreeConfigNode):
+
     def init2(self, node_name):
-        self.props["shard_test"] = node_name
+        self.props["is_coverage"] = node_name
 
     def child_constructor(self):
-        return ImportantConfigNode
+        return ExperimentalFeatureConfigNode
 
 
 class ImportantConfigNode(TreeConfigNode):
@@ -246,6 +290,7 @@ class ImportantConfigNode(TreeConfigNode):
 
 
 class XenialCompilerConfigNode(TreeConfigNode):
+
     def modify_label(self, label):
         return label or "<unspecified>"
 
@@ -259,6 +304,7 @@ class XenialCompilerConfigNode(TreeConfigNode):
 
 
 class BionicCompilerConfigNode(TreeConfigNode):
+
     def modify_label(self, label):
         return label or "<unspecified>"
 

.circleci/cimodel/data/pytorch_build_definitions.py

@@ -31,7 +31,6 @@ class Conf:
     is_libtorch: bool = False
     is_important: bool = False
     parallel_backend: Optional[str] = None
-    build_only: bool = False
 
     @staticmethod
     def is_test_phase(phase):
@@ -113,8 +112,6 @@ class Conf:
             parameters["resource_class"] = "xlarge"
         if hasattr(self, 'filters'):
             parameters['filters'] = self.filters
-        if self.build_only:
-            parameters['build_only'] = miniutils.quote(str(int(True)))
         return parameters
 
     def gen_workflow_job(self, phase):
@@ -178,6 +175,35 @@ class DocPushConf(object):
             }
         }
 
+# TODO Convert these to graph nodes
+def gen_dependent_configs(xenial_parent_config):
+
+    extra_parms = [
+        (["multigpu"], "large"),
+        (["nogpu", "NO_AVX2"], None),
+        (["nogpu", "NO_AVX"], None),
+        (["slow"], "medium"),
+    ]
+
+    configs = []
+    for parms, gpu in extra_parms:
+
+        c = Conf(
+            xenial_parent_config.distro,
+            ["py3"] + parms,
+            pyver=xenial_parent_config.pyver,
+            cuda_version=xenial_parent_config.cuda_version,
+            restrict_phases=["test"],
+            gpu_resource=gpu,
+            parent_build=xenial_parent_config,
+            is_important=False,
+        )
+
+        configs.append(c)
+
+    return configs
+
+
 def gen_docs_configs(xenial_parent_config):
     configs = []
 
@@ -185,7 +211,7 @@ 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=r"/.*/",
                                     tags_list=RC_PATTERN),
         )
     )
@@ -201,7 +227,7 @@ 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=r"/.*/",
                                     tags_list=RC_PATTERN),
         )
     )
@@ -212,6 +238,13 @@ def gen_docs_configs(xenial_parent_config):
             branch="master",
         )
     )
+
+    configs.append(
+        HiddenConf(
+            "pytorch_doc_test",
+            parent_build=xenial_parent_config
+        )
+    )
     return configs
 
 
@@ -225,7 +258,7 @@ def gen_tree():
     return configs_list
 
 
-def instantiate_configs(only_slow_gradcheck):
+def instantiate_configs():
 
     config_list = []
 
@@ -239,17 +272,11 @@ 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_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
-        is_slow_gradcheck = fc.find_prop("is_slow_gradcheck") or False
         parms_list_ignored_for_docker_image = []
 
-        if only_slow_gradcheck ^ is_slow_gradcheck:
-            continue
-
         python_version = None
         if compiler_name == "cuda" or compiler_name == "android":
             python_version = fc.find_prop("pyver")
@@ -283,12 +310,7 @@ def instantiate_configs(only_slow_gradcheck):
             parms_list.append("asan")
             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_dynamo:
-            parms_list_ignored_for_docker_image.append("dynamo")
+            restrict_phases = ["build", "test1", "test2"]
 
         if is_onnx:
             parms_list.append("onnx")
@@ -304,17 +326,13 @@ def instantiate_configs(only_slow_gradcheck):
         is_important = fc.find_prop("is_important") or False
         parallel_backend = fc.find_prop("parallel_backend") or None
         build_only = fc.find_prop("build_only") or False
-        shard_test = fc.find_prop("shard_test") or False
+        is_coverage = fc.find_prop("is_coverage") or False
         # TODO: fix pure_torch python test packaging issue.
-        if shard_test:
-            restrict_phases = ["build"] if restrict_phases is None else restrict_phases
-            restrict_phases.extend(["test1", "test2"])
         if build_only or is_pure_torch:
             restrict_phases = ["build"]
+        if is_coverage and restrict_phases is None:
+            restrict_phases = ["build", "coverage_test"]
 
-        if is_slow_gradcheck:
-            parms_list_ignored_for_docker_image.append("old")
-            parms_list_ignored_for_docker_image.append("gradcheck")
 
         gpu_resource = None
         if cuda_version and cuda_version != "10":
@@ -335,15 +353,15 @@ def instantiate_configs(only_slow_gradcheck):
             is_libtorch=is_libtorch,
             is_important=is_important,
             parallel_backend=parallel_backend,
-            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
@@ -355,14 +373,36 @@ def instantiate_configs(only_slow_gradcheck):
                                         tags_list=RC_PATTERN)
             c.dependent_tests = gen_docs_configs(c)
 
+        if cuda_version == "10.2" and python_version == "3.6" and not is_libtorch:
+            c.dependent_tests = gen_dependent_configs(c)
+
+        if (
+            compiler_name == "gcc"
+            and compiler_version == "5.4"
+            and not is_libtorch
+            and not is_vulkan
+            and not is_pure_torch
+            and parallel_backend is None
+        ):
+            bc_breaking_check = Conf(
+                "backward-compatibility-check",
+                [],
+                is_xla=False,
+                restrict_phases=["test"],
+                is_libtorch=False,
+                is_important=True,
+                parent_build=c,
+            )
+            c.dependent_tests.append(bc_breaking_check)
+
         config_list.append(c)
 
     return config_list
 
 
-def get_workflow_jobs(only_slow_gradcheck=False):
+def get_workflow_jobs():
 
-    config_list = instantiate_configs(only_slow_gradcheck)
+    config_list = instantiate_configs()
 
     x = []
     for conf_options in config_list:

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

@@ -0,0 +1,106 @@
+import cimodel.data.simple.util.branch_filters as branch_filters
+from cimodel.data.simple.util.docker_constants import (
+    DOCKER_IMAGE_NDK, DOCKER_REQUIREMENT_NDK
+)
+
+
+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):
+
+        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
+
+    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)
+
+        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"),
+    AndroidJob(["vulkan", "x86_32"], "pytorch_linux_build", is_master_only=False),
+    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-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=False,
+        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=False,
+    ),
+    SmoketestJob(
+        "binary_windows_build",
+        ["libtorch", "3.7", "cpu", "release"],
+        None,
+        "binary_windows_libtorch_3_7_cpu_release_build",
+        is_master_only=False,
+    ),
+    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=False,
+        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=False,
+        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=False,
+        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

@@ -4,29 +4,44 @@ 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-cuda11.0-cudnn8-py3.6-gcc9",
+    "pytorch-linux-bionic-cuda11.0-cudnn8-py3.8-gcc9",
+    "pytorch-linux-bionic-cuda10.2-cudnn7-py3.8-gcc9",
+    "pytorch-linux-bionic-py3.6-clang9",
+    "pytorch-linux-bionic-cuda10.2-cudnn7-py3.6-clang9",
+    "pytorch-linux-bionic-py3.8-gcc9",
+    "pytorch-linux-bionic-rocm3.5.1-py3.6",
+    "pytorch-linux-xenial-cuda10-cudnn7-py3-gcc7",
+    "pytorch-linux-xenial-cuda10.1-cudnn7-py3-gcc7",
+    "pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7",
+    "pytorch-linux-xenial-cuda11.0-cudnn8-py3-gcc7",
+    "pytorch-linux-xenial-cuda9.2-cudnn7-py3-gcc5.4",
+    "pytorch-linux-xenial-cuda9.2-cudnn7-py3-gcc7",
+    "pytorch-linux-xenial-py3-clang5-android-ndk-r19c",
+    "pytorch-linux-xenial-py3-clang5-asan",
+    "pytorch-linux-xenial-py3-clang7-onnx",
+    "pytorch-linux-xenial-py3.8",
+    "pytorch-linux-xenial-py3.6-clang7",
+    "pytorch-linux-xenial-py3.6-gcc4.8",
+    "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-rocm3.7-py3.6",
+    "pytorch-linux-bionic-rocm3.8-py3.6",
 ]
 
-# This entry should be an element from the list above
-# This should contain the image matching the "slow_gradcheck" entry in
-# 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():
     """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-')
-        if only_slow_gradcheck and image_name is not SLOW_GRADCHECK_IMAGE_NAME:
-            continue
-
+    for image_name in IMAGE_NAMES:
         parameters = OrderedDict({
             "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/ge_config_tests.py

@@ -0,0 +1,103 @@
+import cimodel.lib.miniutils as miniutils
+from cimodel.data.simple.util.versions import MultiPartVersion, CudaVersion
+from cimodel.data.simple.util.docker_constants import DOCKER_IMAGE_BASIC, DOCKER_IMAGE_CUDA_10_2
+
+
+class GeConfigTestJob:
+    def __init__(self,
+                 py_version,
+                 gcc_version,
+                 cuda_version,
+                 variant_parts,
+                 extra_requires,
+                 use_cuda_docker=False,
+                 build_env_override=None):
+
+        self.py_version = py_version
+        self.gcc_version = gcc_version
+        self.cuda_version = cuda_version
+        self.variant_parts = variant_parts
+        self.extra_requires = extra_requires
+        self.use_cuda_docker = use_cuda_docker
+        self.build_env_override = build_env_override
+
+    def get_all_parts(self, with_dots):
+
+        maybe_py_version = self.py_version.render_dots_or_parts(with_dots) if self.py_version else []
+        maybe_gcc_version = self.gcc_version.render_dots_or_parts(with_dots) if self.gcc_version else []
+        maybe_cuda_version = self.cuda_version.render_dots_or_parts(with_dots) if self.cuda_version else []
+
+        common_parts = [
+            "pytorch",
+            "linux",
+            "xenial",
+        ] + maybe_cuda_version + maybe_py_version + maybe_gcc_version
+
+        return common_parts + self.variant_parts
+
+    def gen_tree(self):
+
+        resource_class = "gpu.medium" if self.use_cuda_docker else "large"
+        docker_image = DOCKER_IMAGE_CUDA_10_2 if self.use_cuda_docker else DOCKER_IMAGE_BASIC
+        full_name = "_".join(self.get_all_parts(False))
+        build_env = self.build_env_override or "-".join(self.get_all_parts(True))
+
+        props_dict = {
+            "name": full_name,
+            "build_environment": build_env,
+            "requires": self.extra_requires,
+            "resource_class": resource_class,
+            "docker_image": docker_image,
+        }
+
+        if self.use_cuda_docker:
+            props_dict["use_cuda_docker_runtime"] = miniutils.quote(str(1))
+
+        return [{"pytorch_linux_test": props_dict}]
+
+
+WORKFLOW_DATA = [
+    GeConfigTestJob(
+        MultiPartVersion([3, 6], "py"),
+        MultiPartVersion([5, 4], "gcc"),
+        None,
+        ["ge_config_legacy", "test"],
+        ["pytorch_linux_xenial_py3_6_gcc5_4_build"]),
+    GeConfigTestJob(
+        MultiPartVersion([3, 6], "py"),
+        MultiPartVersion([5, 4], "gcc"),
+        None,
+        ["ge_config_profiling", "test"],
+        ["pytorch_linux_xenial_py3_6_gcc5_4_build"]),
+    GeConfigTestJob(
+        MultiPartVersion([3, 6], "py"),
+        MultiPartVersion([5, 4], "gcc"),
+        None,
+        ["ge_config_simple", "test"],
+        ["pytorch_linux_xenial_py3_6_gcc5_4_build"],
+    ),
+    GeConfigTestJob(
+        None,
+        None,
+        CudaVersion(10, 2),
+        ["cudnn7", "py3", "ge_config_legacy", "test"],
+        ["pytorch_linux_xenial_cuda10_2_cudnn7_py3_gcc7_build"],
+        use_cuda_docker=True,
+        # TODO Why does the build environment specify cuda10.1, while the
+        # job name is cuda10_2?
+        build_env_override="pytorch-linux-xenial-cuda10.1-cudnn7-ge_config_legacy-test"),
+    GeConfigTestJob(
+        None,
+        None,
+        CudaVersion(10, 2),
+        ["cudnn7", "py3", "ge_config_profiling", "test"],
+        ["pytorch_linux_xenial_cuda10_2_cudnn7_py3_gcc7_build"],
+        use_cuda_docker=True,
+        # TODO Why does the build environment specify cuda10.1, while the
+        # job name is cuda10_2?
+        build_env_override="pytorch-linux-xenial-cuda10.1-cudnn7-ge_config_profiling-test"),
+]
+
+
+def get_workflow_jobs():
+    return [item.gen_tree() for item in WORKFLOW_DATA]

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

@@ -1,18 +1,17 @@
 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])
+
+IOS_VERSION = MultiPartVersion([12, 0, 0])
 
 
 class ArchVariant:
-    def __init__(self, name, custom_build_name=""):
+    def __init__(self, name, is_custom=False):
         self.name = name
-        self.custom_build_name = custom_build_name
+        self.is_custom = is_custom
 
     def render(self):
-        extra_parts = [self.custom_build_name] if len(self.custom_build_name) > 0 else []
-        return "-".join([self.name] + extra_parts).replace("_", "-")
+        extra_parts = ["custom"] if self.is_custom else []
+        return "_".join([self.name] + extra_parts)
 
 
 def get_platform(arch_variant_name):
@@ -20,31 +19,36 @@ def get_platform(arch_variant_name):
 
 
 class IOSJob:
-    def __init__(self, xcode_version, arch_variant, is_org_member_context=True, extra_props=None):
-        self.xcode_version = xcode_version
+    def __init__(self, ios_version, arch_variant, is_org_member_context=True, extra_props=None):
+        self.ios_version = ios_version
         self.arch_variant = arch_variant
         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.ios_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 +57,13 @@ 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))),
-        "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)))}),
+    IOSJob(IOS_VERSION, ArchVariant("x86_64"), is_org_member_context=False),
+    IOSJob(IOS_VERSION, ArchVariant("arm64")),
+    IOSJob(IOS_VERSION, ArchVariant("arm64", True), extra_props={"op_list": "mobilenetv2.yaml"}),
 ]
 
 

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

@@ -1,31 +1,14 @@
-from collections import OrderedDict
-from cimodel.lib.miniutils import quote
-from cimodel.data.simple.util.branch_filters import gen_filter_dict_exclude
-
-
 class MacOsJob:
-    def __init__(self, os_version, is_build=False, is_test=False, extra_props=tuple()):
-        # extra_props is tuple type, because mutable data structures for argument defaults
-        # is not recommended.
+    def __init__(self, os_version, is_test=False):
         self.os_version = os_version
-        self.is_build = is_build
         self.is_test = is_test
-        self.extra_props = dict(extra_props)
 
     def gen_tree(self):
         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,
-            ]
-        )
+        phase_name = "test" if self.is_test else "build"
 
-        full_job_name = "_".join(list(filter(None, full_job_name_list)))
+        full_job_name = "_".join(non_phase_parts + [phase_name])
 
         test_build_dependency = "_".join(non_phase_parts + ["build"])
         extra_dependencies = [test_build_dependency] if self.is_test else []
@@ -38,110 +21,7 @@ class MacOsJob:
         return [{full_job_name: props_dict}]
 
 
-WORKFLOW_DATA = [
-    MacOsJob("10_15", is_build=True),
-    MacOsJob("10_13", is_build=True),
-    MacOsJob(
-        "10_13",
-        is_build=False,
-        is_test=True,
-    ),
-    MacOsJob(
-        "10_13",
-        is_build=True,
-        is_test=True,
-        extra_props=tuple({"lite_interpreter": True}.items()),
-    ),
-]
-
-
-def get_new_workflow_jobs():
-    return [
-        OrderedDict(
-            {
-                "mac_build": OrderedDict(
-                    {
-                        "name": "macos-12-py3-x86-64-build",
-                        "build-environment": "macos-12-py3-x86-64",
-                        "xcode-version": quote("13.3.1"),
-                        "filters": gen_filter_dict_exclude()
-                    }
-                )
-            }
-        ),
-        OrderedDict(
-            {
-                "mac_test": OrderedDict(
-                    {
-                        "name": "macos-12-py3-x86-64-test-1-2-default",
-                        "build-environment": "macos-12-py3-x86-64",
-                        "xcode-version": quote("13.3.1"),
-                        "shard-number": quote("1"),
-                        "num-test-shards": quote("2"),
-                        "requires": ["macos-12-py3-x86-64-build"],
-                        "filters": gen_filter_dict_exclude()
-                    }
-                )
-            }
-        ),
-        OrderedDict(
-            {
-                "mac_test": OrderedDict(
-                    {
-                        "name": "macos-12-py3-x86-64-test-2-2-default",
-                        "build-environment": "macos-12-py3-x86-64",
-                        "xcode-version": quote("13.3.1"),
-                        "shard-number": quote("2"),
-                        "num-test-shards": quote("2"),
-                        "requires": ["macos-12-py3-x86-64-build"],
-                        "filters": gen_filter_dict_exclude()
-                    }
-                )
-            }
-        ),
-        OrderedDict(
-            {
-                "mac_test": OrderedDict(
-                    {
-                        "name": "macos-12-py3-x86-64-test-1-1-functorch",
-                        "build-environment": "macos-12-py3-x86-64",
-                        "xcode-version": quote("13.3.1"),
-                        "shard-number": quote("1"),
-                        "num-test-shards": quote("1"),
-                        "test-config": "functorch",
-                        "requires": ["macos-12-py3-x86-64-build"],
-                        "filters": gen_filter_dict_exclude()
-                    }
-                )
-            }
-        ),
-        OrderedDict(
-            {
-                "mac_build": OrderedDict(
-                    {
-                        "name": "macos-12-py3-x86-64-lite-interpreter-build-test",
-                        "build-environment": "macos-12-py3-lite-interpreter-x86-64",
-                        "xcode-version": quote("13.3.1"),
-                        "build-generates-artifacts": "false",
-                        "filters": gen_filter_dict_exclude()
-                    }
-                )
-            }
-        ),
-        OrderedDict(
-            {
-                "mac_build": OrderedDict(
-                    {
-                        "name": "macos-12-py3-arm64-build",
-                        "build-environment": "macos-12-py3-arm64",
-                        "xcode-version": quote("13.3.1"),
-                        "python-version": quote("3.9.12"),
-                        "filters": gen_filter_dict_exclude()
-                    }
-                )
-            }
-        ),
-    ]
+WORKFLOW_DATA = [MacOsJob("10_13"), MacOsJob("10_13", True)]
 
 
 def get_workflow_jobs():

.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 +52,27 @@ 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"]
+    ),
+
+    # 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

@@ -1,30 +1,24 @@
 import cimodel.data.simple.ios_definitions as ios_definitions
-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.IOS_VERSION.render_dots_or_parts(with_version_dots) + [
             "nightly",
             self.variant,
             "build",
@@ -33,14 +27,13 @@ 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"}},
@@ -50,11 +43,6 @@ class IOSNightlyJob:
             props_dict["ios_arch"] = self.variant
             props_dict["ios_platform"] = ios_definitions.get_platform(self.variant)
             props_dict["name"] = self.gen_job_name()
-            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",
@@ -70,14 +58,9 @@ 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/upload_test_stats_definition.py

@@ -1,22 +0,0 @@
-from typing import OrderedDict
-from cimodel.data.simple.util.branch_filters import gen_filter_dict_exclude
-
-
-def get_workflow_job():
-    return [
-        OrderedDict(
-            {
-                "upload_test_stats": OrderedDict(
-                    {
-                        "name": "upload test status",
-                        "requires": [
-                            "macos-12-py3-x86-64-test-1-2-default",
-                            "macos-12-py3-x86-64-test-2-2-default",
-                            "macos-12-py3-x86-64-test-1-1-functorch",
-                        ],
-                        "filters": gen_filter_dict_exclude()
-                    }
-                )
-            }
-        ),
-    ]

.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
@@ -12,15 +9,18 @@ class MultiPartVersion:
         with the prefix string.
         """
         if self.parts:
-            return [self.prefix + str(self.parts[0])] + [str(part) for part in self.parts[1:]]
+            return [self.prefix + str(self.parts[0])] + list(map(str, self.parts[1:]))
         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):
@@ -29,6 +29,3 @@ class CudaVersion(MultiPartVersion):
         self.minor = minor
 
         super().__init__([self.major, self.minor], "cuda")
-
-    def __str__(self):
-        return f"{self.major}.{self.minor}"

.circleci/cimodel/data/windows_build_definitions.py

@@ -0,0 +1,147 @@
+import cimodel.data.simple.util.branch_filters
+import cimodel.lib.miniutils as miniutils
+from cimodel.data.simple.util.versions import CudaVersion
+
+
+class WindowsJob:
+    def __init__(
+        self,
+        test_index,
+        vscode_spec,
+        cuda_version,
+        force_on_cpu=False,
+        master_only_pred=lambda job: job.vscode_spec.year != 2019,
+    ):
+        self.test_index = test_index
+        self.vscode_spec = vscode_spec
+        self.cuda_version = cuda_version
+        self.force_on_cpu = force_on_cpu
+        self.master_only_pred = master_only_pred
+
+    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_name = "_".join(["pytorch", "windows", base_phase])
+
+        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"
+
+        base_name_parts = [
+            "pytorch",
+            "windows",
+            self.vscode_spec.render(),
+            "py36",
+            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), "cudnn" + str(self.cudnn_version)]
+            if self.cuda_version
+            else ["cpu"]
+        )
+
+        build_environment_string = "-".join(
+            ["pytorch", "win"]
+            + self.vscode_spec.get_elements()
+            + arch_env_elements
+            + ["py3"]
+        )
+
+        is_running_on_cuda = bool(self.cuda_version) and not self.force_on_cpu
+
+        props_dict = {
+            "build_environment": build_environment_string,
+            "python_version": miniutils.quote("3.6"),
+            "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_pred(self):
+            props_dict[
+                "filters"
+            ] = cimodel.data.simple.util.branch_filters.gen_filter_dict()
+
+        name_parts = base_name_parts + cpu_forcing_name_parts + [numbered_phase]
+
+        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.major))
+            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 "Community" if self.year == 2019 else "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())
+
+def FalsePred(_):
+    return False
+
+def TruePred(_):
+    return True
+
+_VC2019 = VcSpec(2019)
+
+WORKFLOW_DATA = [
+    # VS2019 CUDA-10.1
+    WindowsJob(None, _VC2019, CudaVersion(10, 1)),
+    WindowsJob(1, _VC2019, CudaVersion(10, 1)),
+    WindowsJob(2, _VC2019, CudaVersion(10, 1)),
+    # VS2019 CUDA-11.0
+    WindowsJob(None, _VC2019, CudaVersion(11, 0)),
+    WindowsJob(1, _VC2019, CudaVersion(11, 0), master_only_pred=TruePred),
+    WindowsJob(2, _VC2019, CudaVersion(11, 0), master_only_pred=TruePred),
+    # VS2019 CPU-only
+    WindowsJob(None, _VC2019, None),
+    WindowsJob(1, _VC2019, None, master_only_pred=TruePred),
+    WindowsJob(2, _VC2019, None, master_only_pred=TruePred),
+    WindowsJob(1, _VC2019, CudaVersion(10, 1), force_on_cpu=True, master_only_pred=TruePred),
+]
+
+
+def get_windows_workflows():
+    return [item.gen_tree() for item in WORKFLOW_DATA]

.circleci/docker/README.md

@@ -12,20 +12,8 @@ each image as the `BUILD_ENVIRONMENT` environment variable.
 
 See `build.sh` for valid build environments (it's the giant switch).
 
-Docker builds are now defined with `.circleci/cimodel/data/simple/docker_definitions.py`
-
 ## Contents
 
 * `build.sh` -- dispatch script to launch all builds
 * `common` -- scripts used to execute individual Docker build stages
 * `ubuntu-cuda` -- Dockerfile for Ubuntu image with CUDA support for nvidia-docker
-
-## Usage
-
-```bash
-# Build a specific image
-./build.sh pytorch-linux-bionic-py3.8-gcc9 -t myimage:latest
-
-# Set flags (see build.sh) and build image
-sudo bash -c 'PROTOBUF=1 ./build.sh pytorch-linux-bionic-py3.8-gcc9 -t myimage:latest
-```

.circleci/docker/android/build.gradle

@@ -20,8 +20,10 @@ buildscript {
     }
 
     dependencies {
-        classpath 'com.android.tools.build:gradle:4.1.2'
-        classpath 'com.vanniktech:gradle-maven-publish-plugin:0.14.2'
+        classpath 'com.android.tools.build:gradle:3.3.2'
+        classpath "com.jfrog.bintray.gradle:gradle-bintray-plugin:1.8.0"
+        classpath "com.github.dcendents:android-maven-gradle-plugin:2.1"
+        classpath "org.jfrog.buildinfo:build-info-extractor-gradle:4.9.8"
     }
 }
 
@@ -51,9 +53,9 @@ 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

@@ -40,13 +40,9 @@ function extract_all_from_image_name() {
   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" == *-xenial* ]]; then
+if [[ "$image" == *-trusty* ]]; then
+  UBUNTU_VERSION=14.04
+elif [[ "$image" == *-xenial* ]]; then
   UBUNTU_VERSION=16.04
 elif [[ "$image" == *-artful* ]]; then
   UBUNTU_VERSION=17.10
@@ -54,8 +50,6 @@ elif [[ "$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
@@ -72,157 +66,148 @@ 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
 
-if [[ "$image" == *xenial* ]] || [[ "$image" == *bionic* ]]; then
-  CMAKE_VERSION=3.13.5
-fi
-
 TRAVIS_DL_URL_PREFIX="https://s3.amazonaws.com/travis-python-archives/binaries/ubuntu/14.04/x86_64"
-_UCX_COMMIT=31e74cac7bee0ef66bef2af72e7d86d9c282e5ab
-_UCC_COMMIT=12944da33f911daf505d9bbc51411233d0ed85e1
 
 # 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-xenial-py3.8)
-    ANACONDA_PYTHON_VERSION=3.8
+    # TODO: This is a hack, get rid of this as soon as you get rid of the travis downloads
+    TRAVIS_DL_URL_PREFIX="https://s3.amazonaws.com/travis-python-archives/binaries/ubuntu/16.04/x86_64"
+    TRAVIS_PYTHON_VERSION=3.8
     GCC_VERSION=7
     # Do not install PROTOBUF, DB, and VISION as a test
     ;;
-  pytorch-linux-xenial-py3.7-gcc7.2)
-    ANACONDA_PYTHON_VERSION=3.7
+  pytorch-linux-xenial-py3.6-gcc4.8)
+    ANACONDA_PYTHON_VERSION=3.6
+    GCC_VERSION=4.8
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    ;;
+  pytorch-linux-xenial-py3.6-gcc5.4)
+    ANACONDA_PYTHON_VERSION=3.6
+    GCC_VERSION=5
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    KATEX=yes
+    ;;
+  pytorch-linux-xenial-py3.6-gcc7.2)
+    ANACONDA_PYTHON_VERSION=3.6
     GCC_VERSION=7
     # Do not install PROTOBUF, DB, and VISION as a test
     ;;
-  pytorch-linux-xenial-py3.7-gcc7)
-    ANACONDA_PYTHON_VERSION=3.7
+  pytorch-linux-xenial-py3.6-gcc7)
+    ANACONDA_PYTHON_VERSION=3.6
     GCC_VERSION=7
     PROTOBUF=yes
     DB=yes
     VISION=yes
     ;;
+  pytorch-linux-xenial-cuda9.2-cudnn7-py3-gcc5.4)
+    CUDA_VERSION=9.2
+    CUDNN_VERSION=7
+    ANACONDA_PYTHON_VERSION=3.6
+    GCC_VERSION=5
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    ;;
+  pytorch-linux-xenial-cuda9.2-cudnn7-py3-gcc7)
+    CUDA_VERSION=9.2
+    CUDNN_VERSION=7
+    ANACONDA_PYTHON_VERSION=3.6
+    GCC_VERSION=7
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    ;;
+  pytorch-linux-xenial-cuda10-cudnn7-py3-gcc7)
+    CUDA_VERSION=10.0
+    CUDNN_VERSION=7
+    ANACONDA_PYTHON_VERSION=3.6
+    GCC_VERSION=7
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    ;;
+  pytorch-linux-xenial-cuda10.1-cudnn7-py3-gcc7)
+    CUDA_VERSION=10.1
+    CUDNN_VERSION=7
+    ANACONDA_PYTHON_VERSION=3.6
+    GCC_VERSION=7
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    KATEX=yes
+    ;;
   pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7)
     CUDA_VERSION=10.2
     CUDNN_VERSION=7
-    ANACONDA_PYTHON_VERSION=3.7
+    ANACONDA_PYTHON_VERSION=3.6
     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
+  pytorch-linux-xenial-cuda11.0-cudnn8-py3-gcc7)
+    CUDA_VERSION=11.0
     CUDNN_VERSION=8
-    TENSORRT_VERSION=8.0.1.6
-    ANACONDA_PYTHON_VERSION=3.7
+    ANACONDA_PYTHON_VERSION=3.6
     GCC_VERSION=7
     PROTOBUF=yes
     DB=yes
     VISION=yes
     KATEX=yes
     ;;
-  pytorch-linux-bionic-cuda11.3-cudnn8-py3-clang9)
-    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
-    ;;
-  pytorch-linux-bionic-cuda11.6-cudnn8-py3-gcc7)
-    CUDA_VERSION=11.6.2
-    CUDNN_VERSION=8
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=7
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    ;;
-  pytorch-linux-bionic-cuda11.7-cudnn8-py3-gcc7)
-    CUDA_VERSION=11.7.0
-    CUDNN_VERSION=8
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=7
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    ;;
   pytorch-linux-xenial-py3-clang5-asan)
-    ANACONDA_PYTHON_VERSION=3.7
+    ANACONDA_PYTHON_VERSION=3.6
     CLANG_VERSION=5.0
     PROTOBUF=yes
     DB=yes
     VISION=yes
     ;;
-  pytorch-linux-xenial-py3-clang7-asan)
-    ANACONDA_PYTHON_VERSION=3.7
-    CLANG_VERSION=7
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    ;;
-  pytorch-linux-focal-py3-clang7-asan)
-    ANACONDA_PYTHON_VERSION=3.7
-    CLANG_VERSION=7
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    ;;
   pytorch-linux-xenial-py3-clang7-onnx)
-    ANACONDA_PYTHON_VERSION=3.7
+    ANACONDA_PYTHON_VERSION=3.6
     CLANG_VERSION=7
     PROTOBUF=yes
     DB=yes
     VISION=yes
     ;;
-  pytorch-linux-focal-py3-clang10-onnx)
-    ANACONDA_PYTHON_VERSION=3.7
-    CLANG_VERSION=10
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    ;;
   pytorch-linux-xenial-py3-clang5-android-ndk-r19c)
-    ANACONDA_PYTHON_VERSION=3.7
+    ANACONDA_PYTHON_VERSION=3.6
     CLANG_VERSION=5.0
     LLVMDEV=yes
     PROTOBUF=yes
     ANDROID=yes
     ANDROID_NDK_VERSION=r19c
-    GRADLE_VERSION=6.8.3
+    GRADLE_VERSION=4.10.3
+    CMAKE_VERSION=3.7.0
     NINJA_VERSION=1.9.0
     ;;
-  pytorch-linux-xenial-py3.7-clang7)
-    ANACONDA_PYTHON_VERSION=3.7
+  pytorch-linux-xenial-py3.6-clang7)
+    ANACONDA_PYTHON_VERSION=3.6
     CLANG_VERSION=7
     PROTOBUF=yes
     DB=yes
     VISION=yes
     ;;
-  pytorch-linux-bionic-py3.7-clang9)
-    ANACONDA_PYTHON_VERSION=3.7
+  pytorch-linux-bionic-py3.6-clang9)
+    ANACONDA_PYTHON_VERSION=3.6
     CLANG_VERSION=9
     PROTOBUF=yes
     DB=yes
     VISION=yes
-    VULKAN_SDK_VERSION=1.2.162.1
+    VULKAN_SDK_VERSION=1.2.148.0
     SWIFTSHADER=yes
     ;;
   pytorch-linux-bionic-py3.8-gcc9)
@@ -232,66 +217,57 @@ case "$image" in
     DB=yes
     VISION=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
     ;;
-  pytorch-linux-bionic-cuda10.2-cudnn7-py3.9-gcc7)
+  pytorch-linux-bionic-cuda10.2-cudnn7-py3.8-gcc9)
     CUDA_VERSION=10.2
     CUDNN_VERSION=7
-    ANACONDA_PYTHON_VERSION=3.9
-    GCC_VERSION=7
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    ;;
-  pytorch-linux-focal-rocm5.1-py3.7)
-    ANACONDA_PYTHON_VERSION=3.7
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=9
     PROTOBUF=yes
     DB=yes
     VISION=yes
-    ROCM_VERSION=5.1.1
     ;;
-  pytorch-linux-focal-rocm5.2-py3.7)
-    ANACONDA_PYTHON_VERSION=3.7
+  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=5.2
-    ;;
-  pytorch-linux-focal-py3.7-gcc7)
-    ANACONDA_PYTHON_VERSION=3.7
-    CMAKE_VERSION=3.16.9  # Required for precompiled header support
-    GCC_VERSION=7
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
     KATEX=yes
     ;;
-  pytorch-linux-jammy-cuda11.6-cudnn8-py3.8-clang12)
-    ANACONDA_PYTHON_VERSION=3.8
-    CUDA_VERSION=11.6
+  pytorch-linux-bionic-cuda11.0-cudnn8-py3.8-gcc9)
+    CUDA_VERSION=11.0
     CUDNN_VERSION=8
-    CLANG_VERSION=12
+    ANACONDA_PYTHON_VERSION=3.8
+    GCC_VERSION=9
     PROTOBUF=yes
     DB=yes
     VISION=yes
+    KATEX=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-rocm3.7-py3.6)
+    ANACONDA_PYTHON_VERSION=3.6
     PROTOBUF=yes
     DB=yes
     VISION=yes
+    ROCM_VERSION=3.7
+    ;;
+  pytorch-linux-bionic-rocm3.8-py3.6)
+    ANACONDA_PYTHON_VERSION=3.6
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    ROCM_VERSION=3.8
     ;;
   *)
     # Catch-all for builds that are not hardcoded.
@@ -333,15 +309,7 @@ if [ -n "${JENKINS:-}" ]; then
   JENKINS_GID=$(id -g jenkins)
 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${UBUNTU_VERSION}"
-  fi
-fi
+tmp_tag="tmp-$(cat /dev/urandom | tr -dc 'a-z' | fold -w 32 | head -n 1)"
 
 # Build image
 # TODO: build-arg THRIFT is not turned on for any image, remove it once we confirm
@@ -366,10 +334,10 @@ docker build \
        --build-arg "GLIBC_VERSION=${GLIBC_VERSION}" \
        --build-arg "CLANG_VERSION=${CLANG_VERSION}" \
        --build-arg "ANACONDA_PYTHON_VERSION=${ANACONDA_PYTHON_VERSION}" \
+       --build-arg "TRAVIS_PYTHON_VERSION=${TRAVIS_PYTHON_VERSION}" \
        --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=${GRADLE_VERSION}" \
@@ -379,10 +347,6 @@ docker build \
        --build-arg "NINJA_VERSION=${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}" \
        -f $(dirname ${DOCKERFILE})/Dockerfile \
        -t "$tmp_tag" \
        "$@" \
@@ -401,7 +365,6 @@ function drun() {
 }
 
 if [[ "$OS" == "ubuntu" ]]; then
-
   if !(drun lsb_release -a 2>&1 | grep -qF Ubuntu); then
     echo "OS=ubuntu, but:"
     drun lsb_release -a
@@ -414,6 +377,19 @@ if [[ "$OS" == "ubuntu" ]]; then
   fi
 fi
 
+if [ -n "$TRAVIS_PYTHON_VERSION" ]; then
+  if [[ "$TRAVIS_PYTHON_VERSION" != nightly ]]; then
+    if !(drun python --version 2>&1 | grep -qF "Python $TRAVIS_PYTHON_VERSION"); then
+      echo "TRAVIS_PYTHON_VERSION=$TRAVIS_PYTHON_VERSION, but:"
+      drun python --version
+      exit 1
+    fi
+  else
+    echo "Please manually check nightly is OK:"
+    drun python --version
+  fi
+fi
+
 if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
   if !(drun python --version 2>&1 | grep -qF "Python $ANACONDA_PYTHON_VERSION"); then
     echo "ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION, but:"

.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 +43,7 @@ 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}-${tag}"
-  fi
-fi
-
-if [ -z "${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
+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

.circleci/docker/centos-rocm/Dockerfile

@@ -4,99 +4,84 @@ 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
 ENV PATH /opt/conda/bin:$PATH
 ARG ANACONDA_PYTHON_VERSION
-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:$PATH
 ENV PATH /opt/rocm/opencl/bin:$PATH
 ENV PATH /opt/rocm/llvm/bin:$PATH
-ENV MAGMA_HOME /opt/rocm/magma
+ENV HIP_PLATFORM hcc
 ENV LANG en_US.utf8
 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_android.sh

@@ -99,7 +99,7 @@ echo "ndk.dir=/opt/ndk" >> $GRADLE_LOCAL_PROPERTIES
 chown -R jenkins /var/lib/jenkins/gradledeps
 chgrp -R jenkins /var/lib/jenkins/gradledeps
 
-sudo -H -u jenkins $GRADLE_HOME/bin/gradle -Pandroid.useAndroidX=true -p /var/lib/jenkins/gradledeps -g /var/lib/jenkins/.gradle --refresh-dependencies --debug --stacktrace assemble
+sudo -H -u jenkins $GRADLE_HOME/bin/gradle -p /var/lib/jenkins/gradledeps -g /var/lib/jenkins/.gradle --refresh-dependencies --debug --stacktrace assemble
 
 chown -R jenkins /var/lib/jenkins/.gradle
 chgrp -R jenkins /var/lib/jenkins/.gradle

.circleci/docker/common/install_base.sh

@@ -11,41 +11,19 @@ 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
+  # TODO: libiomp also gets installed by conda, aka there's a conflict
   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 \
@@ -56,36 +34,25 @@ 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} \
+    python \
+    python-dev \
+    python-setuptools \
+    python-wheel \
     software-properties-common \
-    wget \
     sudo \
-    vim \
-    jq \
-    libtool
+    wget \
+    vim
 
-  # 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
+  # TODO: THIS IS A HACK!!!
+  # distributed nccl(2) tests are a bit busted, see https://github.com/pytorch/pytorch/issues/5877
+  if dpkg -s libnccl-dev; then
+    apt-get remove -y libnccl-dev libnccl2 --allow-change-held-packages
   fi
 
   # Cleanup package manager
@@ -121,7 +88,6 @@ install_centos() {
     glog-devel \
     hiredis-devel \
     libstdc++-devel \
-    libsndfile-devel \
     make \
     opencv-devel \
     sudo \
@@ -153,11 +119,14 @@ 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

@@ -2,30 +2,6 @@
 
 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
-  echo "Checking out sccache repo"
-  git clone https://github.com/pytorch/sccache
-  cd sccache
-  echo "Building sccache"
-  cargo build --release
-  cp target/release/sccache /opt/cache/bin
-  echo "Cleaning up"
-  cd ..
-  rm -rf sccache
-  apt-get remove -y cargo rustc
-  apt-get autoclean && apt-get clean
-}
-
-install_binary() {
-  echo "Downloading sccache binary from S3 repo"
-  curl --retry 3 https://s3.amazonaws.com/ossci-linux/sccache -o /opt/cache/bin/sccache
-}
-
 mkdir -p /opt/cache/bin
 mkdir -p /opt/cache/lib
 sed -e 's|PATH="\(.*\)"|PATH="/opt/cache/bin:\1"|g' -i /etc/environment
@@ -35,22 +11,12 @@ export PATH="/opt/cache/bin:$PATH"
 if [ -n "$ROCM_VERSION" ]; then
   curl --retry 3 http://repo.radeon.com/misc/.sccache_amd/sccache -o /opt/cache/bin/sccache
 else
-  ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
-  case "$ID" in
-    ubuntu)
-      install_ubuntu
-      ;;
-    *)
-      install_binary
-      ;;
-  esac
+  curl --retry 3 https://s3.amazonaws.com/ossci-linux/sccache -o /opt/cache/bin/sccache
 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\nexec sccache $(which $1) \$*" > "/opt/cache/bin/$1"
   chmod a+x "/opt/cache/bin/$1"
 }
 
@@ -72,8 +38,8 @@ if [ -n "$CUDA_VERSION" ]; then
   # where CUDA is installed.  Instead, we install an nvcc symlink outside
   # of the PATH, and set CUDA_NVCC_EXECUTABLE so that we make use of it.
 
-  write_sccache_stub nvcc
-  mv /opt/cache/bin/nvcc /opt/cache/lib/
+  printf "#!/bin/sh\nexec sccache $(which nvcc) \"\$@\"" > /opt/cache/lib/nvcc
+  chmod a+x /opt/cache/lib/nvcc
 fi
 
 if [ -n "$ROCM_VERSION" ]; then
@@ -91,8 +57,8 @@ if [ -n "$ROCM_VERSION" ]; then
     TOPDIR=$(dirname $OLDCOMP)
     WRAPPED="$TOPDIR/original/$COMPNAME"
     mv "$OLDCOMP" "$WRAPPED"
-    printf "#!/bin/sh\nexec sccache $WRAPPED \"\$@\"" > "$OLDCOMP"
-    chmod a+x "$OLDCOMP"
+    printf "#!/bin/sh\nexec sccache $WRAPPED \$*" > "$OLDCOMP"
+    chmod a+x "$1"
   }
 
   if [[ -e "/opt/rocm/hcc/bin/hcc" ]]; then

.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_cmake.sh

@@ -4,9 +4,6 @@ set -ex
 
 [ -n "$CMAKE_VERSION" ]
 
-# Remove system cmake install so it won't get used instead
-apt-get remove cmake -y
-
 # Turn 3.6.3 into v3.6
 path=$(echo "${CMAKE_VERSION}" | sed -e 's/\([0-9].[0-9]\+\).*/v\1/')
 file="cmake-${CMAKE_VERSION}-Linux-x86_64.tar.gz"

.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="$ANACONDA_PYTHON_VERSION"
@@ -70,47 +68,38 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
     as_jenkins conda install -q -y python="$ANACONDA_PYTHON_VERSION" $*
   }
 
-  pip_install() {
-    as_jenkins pip install --progress-bar off $*
-  }
-
   # Install PyTorch conda deps, as per https://github.com/pytorch/pytorch README
-  # DO NOT install cmake here as it would install a version newer than 3.13, but
-  # we want to pin to version 3.13.
-  CONDA_COMMON_DEPS="astunparse pyyaml mkl=2022.0.1 mkl-include=2022.0.1 setuptools cffi future six"
-  if [ "$ANACONDA_PYTHON_VERSION" = "3.10" ]; then
+  # DO NOT install cmake here as it would install a version newer than 3.5, but
+  # we want to pin to version 3.5.
+  if [ "$ANACONDA_PYTHON_VERSION" = "3.8" ]; then
+    # DO NOT install typing if installing python-3.8, since its part of python-3.8 core packages
     # 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 ${CONDA_COMMON_DEPS} llvmdev=8.0.0
-  elif [ "$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 pyyaml mkl mkl-include setuptools cffi future six llvmdev=8.0.0 dataclasses
   else
-    # Install `typing_extensions` for 3.7
-    conda_install numpy=1.18.5 ${CONDA_COMMON_DEPS} typing_extensions
+    conda_install numpy=1.18.5 pyyaml mkl mkl-include setuptools cffi typing future six dataclasses
   fi
-
-  # Magma package names are concatenation of CUDA major and minor ignoring revision
-  # I.e. magma-cuda102 package corresponds to CUDA_VERSION=10.2 and CUDA_VERSION=10.2.89
-  if [ -n "$CUDA_VERSION" ]; then
-    conda_install magma-cuda$(TMP=${CUDA_VERSION/./};echo ${TMP%.*[0-9]}) -c pytorch
+  if [[ "$CUDA_VERSION" == 9.2* ]]; then
+    conda_install magma-cuda92 -c pytorch
+  elif [[ "$CUDA_VERSION" == 10.0* ]]; then
+    conda_install magma-cuda100 -c pytorch
+  elif [[ "$CUDA_VERSION" == 10.1* ]]; then
+    conda_install magma-cuda101 -c pytorch
+  elif [[ "$CUDA_VERSION" == 10.2* ]]; then
+    conda_install magma-cuda102 -c pytorch
+  elif [[ "$CUDA_VERSION" == 11.0* ]]; then
+    conda_install magma-cuda110 -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
-
-  # 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
-  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
-  fi
+  # Install some other packages
+  # TODO: Why is scipy pinned
+  # numba & llvmlite is pinned because of https://github.com/numba/numba/issues/4368
+  # scikit-learn is pinned because of
+  # https://github.com/scikit-learn/scikit-learn/issues/14485 (affects gcc 5.5
+  # only)
+  as_jenkins pip install --progress-bar off pytest scipy==1.1.0 scikit-learn==0.20.3 scikit-image librosa>=0.6.2 psutil numba==0.46.0 llvmlite==0.30.0
 
   popd
 fi

.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 [[ ${CUDA_VERSION:0:4} == "11.7" ]]; then
-        CUDNN_NAME="cudnn-linux-x86_64-8.5.0.96_cuda11-archive"
-        curl -OLs https://ossci-linux.s3.amazonaws.com/${CUDNN_NAME}.tar.xz
-    else
-        curl -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_db.sh

@@ -2,6 +2,23 @@
 
 set -ex
 
+# This function installs protobuf 2.6
+install_protobuf_26() {
+  pb_dir="/usr/temp_pb_install_dir"
+  mkdir -p $pb_dir
+
+  # On the nvidia/cuda:9-cudnn7-devel-centos7 image we need this symlink or
+  # else it will fail with
+  #   g++: error: ./../lib64/crti.o: No such file or directory
+  ln -s /usr/lib64 "$pb_dir/lib64"
+
+  curl -LO "https://github.com/google/protobuf/releases/download/v2.6.1/protobuf-2.6.1.tar.gz"
+  tar -xvz -C "$pb_dir" --strip-components 1 -f protobuf-2.6.1.tar.gz
+  pushd "$pb_dir" && ./configure && make && make check && sudo make install && sudo ldconfig
+  popd
+  rm -rf $pb_dir
+}
+
 install_ubuntu() {
   apt-get update
   apt-get install -y --no-install-recommends \

.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 -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
-
-  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 +7,14 @@ 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
 
   # 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_lcov.sh

@@ -1,8 +0,0 @@
-#!/bin/bash
-
-set -ex
-
-git clone --branch v1.15 https://github.com/linux-test-project/lcov.git
-pushd lcov
-sudo make install   # will be installed in /usr/local/bin/lcov
-popd

.circleci/docker/common/install_openmpi.sh

@@ -1,10 +0,0 @@
-#!/bin/bash
-
-sudo apt-get update
-# also install ssh to avoid error of:
-# --------------------------------------------------------------------------
-# The value of the MCA parameter "plm_rsh_agent" was set to a path
-# that could not be found:
-#   plm_rsh_agent: ssh : rsh
-sudo apt-get install -y ssh
-sudo apt-get install -y --allow-downgrades --allow-change-held-packages openmpi-bin libopenmpi-dev

.circleci/docker/common/install_openssl.sh

@@ -1,16 +0,0 @@
-#!/bin/bash
-
-set -ex
-
-OPENSSL=openssl-1.1.1k
-
-wget -q -O "${OPENSSL}.tar.gz" "https://ossci-linux.s3.amazonaws.com/${OPENSSL}.tar.gz"
-tar xf "${OPENSSL}.tar.gz"
-cd "${OPENSSL}"
-./config --prefix=/opt/openssl -d '-Wl,--enable-new-dtags,-rpath,$(LIBRPATH)'
-# NOTE: openssl install errors out when built with the -j option
-make -j6; make install_sw
-# Link the ssl libraries to the /usr/lib folder.
-sudo ln -s /opt/openssl/lib/lib* /usr/lib
-cd ..
-rm -rf "${OPENSSL}"

.circleci/docker/common/install_protobuf.sh

@@ -2,8 +2,8 @@
 
 set -ex
 
-# This function installs protobuf 3.17
-install_protobuf_317() {
+# This function installs protobuf 2.6
+install_protobuf_26() {
   pb_dir="/usr/temp_pb_install_dir"
   mkdir -p $pb_dir
 
@@ -12,32 +12,37 @@ 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"
-  tar -xvz -C "$pb_dir" --strip-components 1 -f protobuf-all-3.17.3.tar.gz
-  # -j6 to balance memory usage and speed.
-  # naked `-j` seems to use too much memory.
-  pushd "$pb_dir" && ./configure && make -j6 && make -j6 check && sudo make -j6 install && sudo ldconfig
+  curl -LO "https://github.com/google/protobuf/releases/download/v2.6.1/protobuf-2.6.1.tar.gz"
+  tar -xvz -C "$pb_dir" --strip-components 1 -f protobuf-2.6.1.tar.gz
+  pushd "$pb_dir" && ./configure && make && make check && sudo make install && sudo ldconfig
   popd
   rm -rf $pb_dir
 }
 
 install_ubuntu() {
-  # Ubuntu 14.04 has cmake 2.8.12 as the default option, so we will
+  # Ubuntu 14.04 ships with protobuf 2.5, but ONNX needs protobuf >= 2.6
+  # so we install that here if on 14.04
+  # Ubuntu 14.04 also has cmake 2.8.12 as the default option, so we will
   # install cmake3 here and use cmake3.
   apt-get update
   if [[ "$UBUNTU_VERSION" == 14.04 ]]; then
     apt-get install -y --no-install-recommends cmake3
+    install_protobuf_26
+  else
+    apt-get install -y --no-install-recommends \
+            libprotobuf-dev \
+            protobuf-compiler
   fi
 
   # Cleanup
   apt-get autoclean && apt-get clean
   rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
-
-  install_protobuf_317
 }
 
 install_centos() {
-  install_protobuf_317
+  # Centos7 ships with protobuf 2.5, but ONNX needs protobuf >= 2.6
+  # so we always install install that here
+  install_protobuf_26
 }
 
 # Install base packages depending on the base OS

.circleci/docker/common/install_rocm.sh

@@ -2,52 +2,36 @@
 
 set -ex
 
-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
+    apt-get install -y libopenblas-dev
 
     # Need the libc++1 and libc++abi1 libraries to allow torch._C to load at runtime
     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 $2}'`
-        local amdgpu_baseurl="https://repo.radeon.com/amdgpu/${AMDGPU_VERSIONS[$ROCM_VERSION]}/ubuntu"
-        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 $(ver 4.2) ]]; then
-        ROCM_REPO="xenial"
-    fi
-
+    DEB_ROCM_REPO=http://repo.radeon.com/rocm/apt/${ROCM_VERSION}
     # 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
+    wget -qO - $DEB_ROCM_REPO/rocm.gpg.key | apt-key add -
+    echo "deb [arch=amd64] $DEB_ROCM_REPO xenial main" > /etc/apt/sources.list.d/rocm.list
     apt-get update --allow-insecure-repositories
 
     DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated \
                    rocm-dev \
                    rocm-utils \
-                   rocm-libs \
+                   rocfft \
+                   miopen-hip \
+                   rocblas \
+                   hipsparse \
+                   rocrand \
+                   hipcub \
+                   rocthrust \
                    rccl \
                    rocprofiler-dev \
                    roctracer-dev
@@ -61,9 +45,9 @@ install_ubuntu() {
       DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ${MIOPENKERNELS}
     fi
 
-    # Cleanup
-    apt-get autoclean && apt-get clean
-    rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
+  # Cleanup
+  apt-get autoclean && apt-get clean
+  rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
 }
 
 install_centos() {
@@ -76,32 +60,25 @@ install_centos() {
   yum install -y epel-release
   yum install -y dkms kernel-headers-`uname -r` kernel-devel-`uname -r`
 
-  if [[ $(ver $ROCM_VERSION) -ge $(ver 4.5) ]]; then
-      # Add amdgpu repository
-      local amdgpu_baseurl="https://repo.radeon.com/amdgpu/${AMDGPU_VERSIONS[$ROCM_VERSION]}/rhel/7.9/main/x86_64"
-      echo "[AMDGPU]" > /etc/yum.repos.d/amdgpu.repo
-      echo "name=AMDGPU" >> /etc/yum.repos.d/amdgpu.repo
-      echo "baseurl=${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
 
   yum install -y \
                    rocm-dev \
                    rocm-utils \
-                   rocm-libs \
+                   rocfft \
+                   miopen-hip \
+                   rocblas \
+                   hipsparse \
+                   rocrand \
                    rccl \
+                   hipcub \
+                   rocthrust \
                    rocprofiler-dev \
                    roctracer-dev
 

.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_travis_python.sh

@@ -0,0 +1,79 @@
+#!/bin/bash
+
+set -ex
+
+as_jenkins() {
+  # NB: Preserve PATH and LD_LIBRARY_PATH changes
+  sudo -H -u jenkins env "PATH=$PATH" "LD_LIBRARY_PATH=$LD_LIBRARY_PATH" $*
+}
+
+if [ -n "$TRAVIS_PYTHON_VERSION" ]; then
+
+  mkdir -p /opt/python
+  chown jenkins:jenkins /opt/python
+
+  # Download Python binary from Travis
+  pushd tmp
+  as_jenkins wget --quiet ${TRAVIS_DL_URL_PREFIX}/python-$TRAVIS_PYTHON_VERSION.tar.bz2
+  # NB: The tarball also comes with /home/travis virtualenv that we
+  # don't care about.  (Maybe we should, but we've worked around the
+  # "how do I install to python" issue by making this entire directory
+  # user-writable "lol")
+  # NB: Relative ordering of opt/python and flags matters
+  as_jenkins tar xjf python-$TRAVIS_PYTHON_VERSION.tar.bz2 --strip-components=2 --directory /opt/python opt/python
+  popd
+
+  echo "/opt/python/$TRAVIS_PYTHON_VERSION/lib" > /etc/ld.so.conf.d/travis-python.conf
+  ldconfig
+  sed -e 's|PATH="\(.*\)"|PATH="/opt/python/'"$TRAVIS_PYTHON_VERSION"'/bin:\1"|g' -i /etc/environment
+  export PATH="/opt/python/$TRAVIS_PYTHON_VERSION/bin:$PATH"
+
+  python --version
+  pip --version
+
+  # Install pip from source.
+  # The python-pip package on Ubuntu Trusty is old
+  # and upon install numpy doesn't use the binary
+  # distribution, and fails to compile it from source.
+  pushd tmp
+  as_jenkins curl -L -O https://pypi.python.org/packages/11/b6/abcb525026a4be042b486df43905d6893fb04f05aac21c32c638e939e447/pip-9.0.1.tar.gz
+  as_jenkins tar zxf pip-9.0.1.tar.gz
+  pushd pip-9.0.1
+  as_jenkins python setup.py install
+  popd
+  rm -rf pip-9.0.1*
+  popd
+
+  # Install pip packages
+  as_jenkins pip install --upgrade pip
+
+  pip --version
+
+  as_jenkins pip install numpy pyyaml
+
+  as_jenkins pip install \
+      future \
+      hypothesis \
+      protobuf \
+      pytest \
+      pillow \
+      typing \
+      dataclasses
+
+  as_jenkins pip install mkl mkl-devel
+
+  # SciPy does not support Python 3.7 or Python 2.7.9
+  if [[ "$TRAVIS_PYTHON_VERSION" != nightly ]] && [[ "$TRAVIS_PYTHON_VERSION" != "2.7.9" ]]; then
+      as_jenkins pip install scipy==1.1.0 scikit-image librosa>=0.6.2
+  fi
+
+  # Install psutil for dataloader tests
+  as_jenkins pip install psutil
+
+  # Install dill for serialization tests
+  as_jenkins pip install "dill>=0.3.1"
+
+  # Cleanup package manager
+  apt-get autoclean && apt-get clean
+  rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
+fi

.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/common/install_vision.sh

@@ -2,6 +2,23 @@
 
 set -ex
 
+# This function installs protobuf 2.6
+install_protobuf_26() {
+  pb_dir="/usr/temp_pb_install_dir"
+  mkdir -p $pb_dir
+
+  # On the nvidia/cuda:9-cudnn7-devel-centos7 image we need this symlink or
+  # else it will fail with
+  #   g++: error: ./../lib64/crti.o: No such file or directory
+  ln -s /usr/lib64 "$pb_dir/lib64"
+
+  curl -LO "https://github.com/google/protobuf/releases/download/v2.6.1/protobuf-2.6.1.tar.gz"
+  tar -xvz -C "$pb_dir" --strip-components 1 -f protobuf-2.6.1.tar.gz
+  pushd "$pb_dir" && ./configure && make && make check && sudo make install && sudo ldconfig
+  popd
+  rm -rf $pb_dir
+}
+
 install_ubuntu() {
   apt-get update
   apt-get install -y --no-install-recommends \

.circleci/docker/common/install_vulkan_sdk.sh

@@ -8,17 +8,16 @@ retry () {
     $*  || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
 }
 
+_https_amazon_aws=https://ossci-android.s3.amazonaws.com
+
 _vulkansdk_dir=/var/lib/jenkins/vulkansdk
+mkdir -p $_vulkansdk_dir
 _tmp_vulkansdk_targz=/tmp/vulkansdk.tar.gz
+curl --silent --show-error --location --fail --retry 3 \
+  --output "$_tmp_vulkansdk_targz" "$_https_amazon_aws/vulkansdk-linux-x86_64-${VULKAN_SDK_VERSION}.tar.gz"
 
-curl \
-  --silent \
-  --show-error \
-  --location \
-  --fail \
-  --retry 3 \
-  --output "${_tmp_vulkansdk_targz}" "https://ossci-android.s3.amazonaws.com/vulkansdk-linux-x86_64-${VULKAN_SDK_VERSION}.tar.gz"
+tar -C "$_vulkansdk_dir" -xzf "$_tmp_vulkansdk_targz" --strip-components 1
 
-mkdir -p "${_vulkansdk_dir}"
-tar -C "${_vulkansdk_dir}" -xzf "${_tmp_vulkansdk_targz}" --strip-components 1
-rm -rf "${_tmp_vulkansdk_targz}"
+export VULKAN_SDK="$_vulkansdk_dir/"
+
+rm "$_tmp_vulkansdk_targz"

.circleci/docker/requirements-ci.txt

@@ -1,244 +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-rerunfailures
-#Description: plugin for rerunning 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

@@ -1,109 +1,83 @@
 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
 ENV PATH /opt/conda/bin:$PATH
 ARG ANACONDA_PYTHON_VERSION
-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
 
+# Install non-standard Python versions (via Travis binaries)
+ARG TRAVIS_PYTHON_VERSION
+ENV PATH /opt/python/$TRAVIS_PYTHON_VERSION/bin:$PATH
+ADD ./common/install_travis_python.sh install_travis_python.sh
+RUN bash ./install_travis_python.sh && rm install_travis_python.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 "${UCC_COMMIT}" ]; then bash ./install_ucc.sh; fi
-RUN rm install_ucc.sh
-
-COPY ./common/install_openssl.sh install_openssl.sh
-ENV OPENSSL_ROOT_DIR /opt/openssl
-RUN bash ./install_openssl.sh
-ENV OPENSSL_DIR /opt/openssl
-
-# (optional) Install non-default CMake version
-ARG CMAKE_VERSION
-COPY ./common/install_cmake.sh install_cmake.sh
-RUN if [ -n "${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
-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}
@@ -111,21 +85,9 @@ 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

@@ -6,90 +6,76 @@ 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
 ENV PATH /opt/conda/bin:$PATH
 ARG ANACONDA_PYTHON_VERSION
-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
-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:$PATH
 ENV PATH /opt/rocm/opencl/bin:$PATH
 ENV PATH /opt/rocm/llvm/bin:$PATH
-ENV MAGMA_HOME /opt/rocm/magma
+ENV HIP_PLATFORM hcc
 ENV LANG C.UTF-8
 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

@@ -6,86 +6,68 @@ 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
 ENV PATH /opt/conda/bin:$PATH
 ARG ANACONDA_PYTHON_VERSION
-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
-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 "${UCC_COMMIT}" ]; then bash ./install_ucc.sh; fi
-RUN rm install_ucc.sh
+# Install non-standard Python versions (via Travis binaries)
+ARG TRAVIS_PYTHON_VERSION
+ARG TRAVIS_DL_URL_PREFIX
+ENV PATH /opt/python/$TRAVIS_PYTHON_VERSION/bin:$PATH
+ADD ./common/install_travis_python.sh install_travis_python.sh
+RUN bash ./install_travis_python.sh && rm install_travis_python.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}
@@ -94,9 +76,9 @@ 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
@@ -105,53 +87,38 @@ 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
-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}
@@ -159,10 +126,5 @@ 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:16.04
+
+RUN apt-get update && apt-get install -y python-pip git && rm -rf /var/lib/apt/lists/* /var/log/dpkg.log
+
+ADD requirements.txt /requirements.txt
+
+RUN pip 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 python
+
+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 +1,214 @@
+#!/usr/bin/env python
+
+import argparse
+import datetime
+import boto3
+import pytz
+import sys
+import re
+
+
+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

@@ -10,13 +10,20 @@ 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.bazel_definitions
+import cimodel.data.simple.binary_smoketest
 import cimodel.data.simple.docker_definitions
+import cimodel.data.simple.ge_config_tests
+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.macos_definitions
-import cimodel.data.simple.upload_test_stats_definition
-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
 
@@ -74,102 +81,40 @@ class Header(object):
             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):
-        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
-
-    master_deps = set()
-
-    def _save_requires_if_master(item_type, item):
-        requires = item.get('requires', None)
-        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:
-            master_deps.update([n.strip('"') for n in requires])
-
-    def _do_filtering(items):
-        if isinstance(items, list):
-            rc = [_do_filtering(item) for item in items]
-            return [item for item in rc if len(item if item is not None else []) > 0]
-        assert isinstance(items, dict) and len(items) == 1
-        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:
-            return None
-        if 'filters' in item:
-            item = item.copy()
-            item.pop('filters')
-        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
-    _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.macos_definitions.get_new_workflow_jobs,
-        cimodel.data.simple.upload_test_stats_definition.get_workflow_job,
+        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.ge_config_tests.get_workflow_jobs,
+        cimodel.data.simple.bazel_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,
+    ]
+
+    return {
         "workflows": {
-            "build": {
-                "when": r"<< pipeline.parameters.run_build >>",
-                "jobs": build_jobs,
+            "binary_builds": {
+                "when": r"<< pipeline.parameters.run_binary_tests >>",
+                "jobs": [f() for f in binary_build_functions],
             },
+            "build": {"jobs": [f() for f in build_workflows_functions]},
         }
     }
-    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.
@@ -180,14 +125,19 @@ 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-ecr-gc.yml"),
+    File("workflows/workflows-promote.yml"),
 ]
 
 

.circleci/regenerate.ps1

@@ -1,5 +0,0 @@
-cd $PSScriptRoot;
-$NewFile = New-TemporaryFile;
-python generate_config_yml.py > $NewFile.name
-(Get-Content $NewFile.name -Raw).TrimEnd().Replace("`r`n","`n") | Set-Content config.yml -Force
-Remove-Item $NewFile.name

.circleci/regenerate.sh

@@ -1,17 +1,8 @@
-#!/bin/bash -e
+#!/bin/bash -xe
 
 # Allows this script to be invoked from any directory:
-cd "$(dirname "$0")"
-
-UNCOMMIT_CHANGE=$(git status -s | grep " config.yml" | wc -l | xargs)
-if [[ $UNCOMMIT_CHANGE != 0 ]]; then
-    OLD_FILE=$(mktemp)
-    cp config.yml "$OLD_FILE"
-    echo "Uncommitted change detected in .circleci/config.yml"
-    echo "It has been backed up to $OLD_FILE"
-fi
+cd $(dirname "$0")
 
 NEW_FILE=$(mktemp)
-./generate_config_yml.py > "$NEW_FILE"
-cp "$NEW_FILE" config.yml
-echo "New config generated in .circleci/config.yml"
+./generate_config_yml.py > $NEW_FILE
+cp $NEW_FILE config.yml

.circleci/scripts/binary_checkout.sh

@@ -33,11 +33,6 @@ else
   export BUILDER_ROOT="$workdir/builder"
 fi
 
-# Try to extract PR number from branch if not already set
-if [[ -z "${CIRCLE_PR_NUMBER:-}" ]]; then
-  CIRCLE_PR_NUMBER="$(echo ${CIRCLE_BRANCH} | sed -E -n 's/pull\/([0-9]*).*/\1/p')"
-fi
-
 # Clone the Pytorch branch
 retry git clone https://github.com/pytorch/pytorch.git "$PYTORCH_ROOT"
 pushd "$PYTORCH_ROOT"
@@ -49,20 +44,19 @@ if [[ -n "${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
 fi
-retry git submodule update --init --recursive --jobs 0
+retry git submodule update --init --recursive
 echo "Using Pytorch from "
 git --no-pager log --max-count 1
 popd
 
 # Clone the Builder master repo
-retry git clone -q https://github.com/pytorch/builder.git -b release/1.13 "$BUILDER_ROOT"
+retry git clone -q https://github.com/pytorch/builder.git "$BUILDER_ROOT"
 pushd "$BUILDER_ROOT"
 echo "Using builder from "
 git --no-pager log --max-count 1

.circleci/scripts/binary_ios_build.sh

@@ -15,14 +15,14 @@ export PATH="~/anaconda/bin:${PATH}"
 source ~/anaconda/bin/activate
 
 # Install dependencies
-conda install numpy ninja pyyaml mkl mkl-include setuptools cmake cffi requests typing_extensions --yes
+conda install numpy ninja pyyaml mkl mkl-include setuptools cmake cffi typing requests --yes
 conda install -c conda-forge valgrind --yes
 export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
 
 # sync submodules
 cd ${PROJ_ROOT}
 git submodule sync
-git submodule update --init --recursive --jobs 0
+git submodule update --init --recursive
 
 # run build script
 chmod a+x ${PROJ_ROOT}/scripts/build_ios.sh
@@ -31,12 +31,8 @@ cat ${PROJ_ROOT}/scripts/build_ios.sh
 echo "########################################################"
 echo "IOS_ARCH: ${IOS_ARCH}"
 echo "IOS_PLATFORM: ${IOS_PLATFORM}"
-echo "USE_PYTORCH_METAL: ${USE_PYTORCH_METAL}"
-echo "USE_COREML_DELEGATE: ${USE_COREML_DELEGATE}"
 export IOS_ARCH=${IOS_ARCH}
 export IOS_PLATFORM=${IOS_PLATFORM}
-export USE_PYTORCH_METAL=${USE_PYTORCH_METAL}
-export USE_COREML_DELEGATE=${USE_COREML_DELEGATE}
 unbuffer ${PROJ_ROOT}/scripts/build_ios.sh 2>&1 | ts
 
 #store the binary

.circleci/scripts/binary_ios_test.sh

@@ -1,19 +1,29 @@
 #!/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}" >> cert.txt
+base64 --decode cert.txt -o Certificates.p12
+rm cert.txt
+bundle exec fastlane install_cert
+# install the provisioning profile
+PROFILE=PyTorch_CI_2021.mobileprovision
+PROVISIONING_PROFILES=~/Library/MobileDevice/Provisioning\ Profiles
+mkdir -pv "${PROVISIONING_PROFILES}"
+cd "${PROVISIONING_PROFILES}"
+echo "${IOS_SIGN_KEY}" >> 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}
+fi 
+PROFILE=PyTorch_CI_2021
+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}

.circleci/scripts/binary_ios_upload.sh

@@ -23,36 +23,18 @@ 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.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="1.13.0.${DATE}"
-if [ "${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
+ZIPFILE=libtorch_ios_nightly_build.zip
 cd ${ZIP_DIR}
 #for testing
 touch version.txt
-echo "${IOS_NIGHTLY_BUILD_VERSION}" > version.txt
+echo $(date +%s) > version.txt
 zip -r ${ZIPFILE} install src version.txt LICENSE
 # upload to aws
-# Install conda then 'conda install' awscli
-curl --retry 3 -o ~/conda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
-chmod +x ~/conda.sh
-/bin/bash ~/conda.sh -b -p ~/anaconda
-export PATH="~/anaconda/bin:${PATH}"
-source ~/anaconda/bin/activate
-conda install -c conda-forge awscli --yes
+brew install awscli
 set +x
 export AWS_ACCESS_KEY_ID=${AWS_S3_ACCESS_KEY_FOR_PYTORCH_BINARY_UPLOAD}
 export AWS_SECRET_ACCESS_KEY=${AWS_S3_ACCESS_SECRET_FOR_PYTORCH_BINARY_UPLOAD}
@@ -60,16 +42,3 @@ set +x
 # echo "AWS KEY: ${AWS_ACCESS_KEY_ID}"
 # 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 ${PROJ_ROOT}/ios/LibTorch-Lite-Nightly.podspec
-
-    # update pod version
-    sed -i '' -e "s/IOS_NIGHTLY_BUILD_VERSION/${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

.circleci/scripts/binary_linux_build.sh

@@ -4,16 +4,8 @@ echo "RUNNING ON $(uname -a) WITH $(nproc) CPUS AND $(free -m)"
 set -eux -o pipefail
 source /env
 
-# 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} : ${NUM_CPUS} ))}
-
-if [[ "${DESIRED_CUDA}" =~ cu11[0-9] ]]; then
-  export BUILD_SPLIT_CUDA="ON"
-fi
+# Defaults here so they can be changed in one place
+export MAX_JOBS=${MAX_JOBS:-$(( $(nproc) - 2 ))}
 
 # Parse the parameters
 if [[ "$PACKAGE_TYPE" == 'conda' ]]; then
@@ -26,9 +18,5 @@ else
   build_script='manywheel/build.sh'
 fi
 
-if [[ "$CIRCLE_BRANCH" == "main" ]] || [[ "$CIRCLE_BRANCH" == "master" ]] || [[ "$CIRCLE_BRANCH" == release/* ]]; then
-  export BUILD_DEBUG_INFO=1
-fi
-
 # Build the package
 SKIP_ALL_TESTS=1 "/builder/$build_script"

.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
@@ -36,70 +22,35 @@ elif [[ "$PACKAGE_TYPE" != libtorch ]]; then
 fi
 
 EXTRA_CONDA_FLAGS=""
-NUMPY_PIN=""
-PROTOBUF_PACKAGE="defaults::protobuf"
-if [[ "\$python_nodot" = *310* ]]; 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=">=1.21.2"
-  PROTOBUF_PACKAGE="protobuf>=3.19.0"
 fi
 
-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
-
-
-
-# Move debug wheels out of the the package dir so they don't get installed
-mkdir -p /tmp/debug_final_pkgs
-mv /final_pkgs/debug-*.zip /tmp/debug_final_pkgs || echo "no debug packages to move"
-
 # Install the package
 # These network calls should not have 'retry's because they are installing
 # locally and aren't actually network calls
 # 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
-    # which means that a deactivate is run and some variables might not exist when that happens,
-    # namely CONDA_MKL_INTERFACE_LAYER_BACKUP from libblas so let's just ignore unbound variables when
-    # it comes to the conda installation commands
-    set +u
-    retry conda install \${EXTRA_CONDA_FLAGS} -yq \
-      "numpy\${NUMPY_PIN}" \
-      future \
-      mkl>=2018 \
-      ninja \
-      dataclasses \
-      typing-extensions \
-      ${PROTOBUF_PACKAGE} \
-      six
-    if [[ "$DESIRED_CUDA" == 'cpu' ]]; then
-      retry conda install -c pytorch -y cpuonly
+  conda install \${EXTRA_CONDA_FLAGS} -y "\$pkg" --offline
+  if [[ "$DESIRED_CUDA" == 'cpu' ]]; then
+    retry conda install \${EXTRA_CONDA_FLAGS} -y cpuonly -c pytorch
+  fi
+  retry conda install \${EXTRA_CONDA_FLAGS} -yq future numpy protobuf six
+  if [[ "$DESIRED_CUDA" != 'cpu' ]]; then
+    # 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}.${DESIRED_CUDA:4}"
-      CUDA_PACKAGE="cudatoolkit"
-      if [[ "$DESIRED_CUDA" == "cu116" || "$DESIRED_CUDA" == "cu117" ]]; then
-        CUDA_PACKAGE="cuda"
-      fi
-
-      retry conda install \${EXTRA_CONDA_FLAGS} -yq -c nvidia -c pytorch "\${CUDA_PACKAGE}=\${cu_ver}"
     fi
-    conda install \${EXTRA_CONDA_FLAGS} -y "\$pkg" --offline
-  )
+    retry conda install \${EXTRA_CONDA_FLAGS} -yq -c nvidia -c pytorch "cudatoolkit=\${cu_ver}"
+  fi
 elif [[ "$PACKAGE_TYPE" != libtorch ]]; then
   pip install "\$pkg"
-  retry pip install -q future numpy protobuf typing-extensions six
+  retry pip install -q future numpy protobuf six
 fi
 if [[ "$PACKAGE_TYPE" == libtorch ]]; then
   pkg="\$(ls /final_pkgs/*-latest.zip)"
@@ -115,4 +66,4 @@ EOL
 echo
 echo
 echo "The script that will run in the next step is:"
-cat "${OUTPUT_SCRIPT}"
+cat /home/circleci/project/ci_test_script.sh

.circleci/scripts/binary_macos_build.sh

@@ -1,19 +1,24 @@
 #!/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:$PATH"
 if [[ "$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 [[ "$PACKAGE_TYPE" == 'libtorch' ]]; then
   export BUILD_PYTHONLESS=1
 fi
@@ -41,25 +62,18 @@ if [[ -z "$DOCKER_IMAGE" ]]; then
   if [[ "$PACKAGE_TYPE" == conda ]]; then
     export DOCKER_IMAGE="pytorch/conda-cuda"
   elif [[ "$DESIRED_CUDA" == cpu ]]; then
-    export DOCKER_IMAGE="pytorch/manylinux-cpu"
+    export DOCKER_IMAGE="pytorch/manylinux-cuda100"
   else
     export DOCKER_IMAGE="pytorch/manylinux-cuda${DESIRED_CUDA:2}"
   fi
 fi
 
-USE_GOLD_LINKER="OFF"
-# GOLD linker can not be used if CUPTI is statically linked into PyTorch, see https://github.com/pytorch/pytorch/issues/57744
-if [[ ${DESIRED_CUDA} == "cpu" ]]; then
-  USE_GOLD_LINKER="ON"
-fi
-
-
 # Default to nightly, since that's where this normally uploads to
 PIP_UPLOAD_FOLDER='nightly/'
 # We put this here so that OVERRIDE_PACKAGE_VERSION below can read from it
 export DATE="$(date -u +%Y%m%d)"
 #TODO: We should be pulling semver version from the base version.txt
-BASE_BUILD_VERSION="1.13.0.dev$DATE"
+BASE_BUILD_VERSION="1.7.0.dev$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
@@ -71,16 +85,11 @@ if tagged_version >/dev/null; then
   # Turns tag v1.6.0-rc1 -> v1.6.0
   BASE_BUILD_VERSION="$(tagged_version | sed -e 's/^v//' -e 's/-.*$//')"
 fi
-if [[ "$(uname)" == 'Darwin' ]] || [[ "$PACKAGE_TYPE" == conda ]]; then
+if [[ "$(uname)" == 'Darwin' ]] || [[ "$DESIRED_CUDA" == "cu102" ]] || [[ "$PACKAGE_TYPE" == conda ]]; then
   export PYTORCH_BUILD_VERSION="${BASE_BUILD_VERSION}"
 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
 
 
@@ -91,14 +100,8 @@ if [[ "$PACKAGE_TYPE" == libtorch ]]; then
   POSSIBLE_JAVA_HOMES+=(/usr/local)
   POSSIBLE_JAVA_HOMES+=(/usr/lib/jvm/java-8-openjdk-amd64)
   POSSIBLE_JAVA_HOMES+=(/Library/Java/JavaVirtualMachines/*.jdk/Contents/Home)
-  # Add the Windows-specific JNI path
-  POSSIBLE_JAVA_HOMES+=("$PWD/.circleci/windows-jni/")
   for JH in "${POSSIBLE_JAVA_HOMES[@]}" ; do
     if [[ -e "$JH/include/jni.h" ]] ; then
-      # Skip if we're not on Windows but haven't found a JAVA_HOME
-      if [[ "$JH" == "$PWD/.circleci/windows-jni/" && "$OSTYPE" != "msys" ]] ; then
-        break
-      fi
       echo "Found jni.h under $JH"
       JAVA_HOME="$JH"
       BUILD_JNI=ON
@@ -110,28 +113,24 @@ 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="$DATE"
-export NIGHTLIES_DATE_PREAMBLE=1.13.0.dev
+export NIGHTLIES_DATE_PREAMBLE=1.7.0.dev
 export PYTORCH_BUILD_VERSION="$PYTORCH_BUILD_VERSION"
 export PYTORCH_BUILD_NUMBER="$PYTORCH_BUILD_NUMBER"
 export OVERRIDE_PACKAGE_VERSION="$PYTORCH_BUILD_VERSION"
@@ -139,7 +138,6 @@ 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=$JAVA_HOME
@@ -147,48 +145,25 @@ export BUILD_JNI=$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 USE_GOLD_LINKER="${USE_GOLD_LINKER}"
-export USE_GLOO_WITH_OPENSSL="ON"
+export CIRCLE_TAG="${CIRCLE_TAG:-}"
+export CIRCLE_SHA1="$CIRCLE_SHA1"
+export CIRCLE_PR_NUMBER="${CIRCLE_PR_NUMBER:-}"
+export CIRCLE_BRANCH="$CIRCLE_BRANCH"
 # =================== 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

@@ -1,68 +1,30 @@
 #!/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="${DESIRED_CUDA/cu/}"
 export USE_SCCACHE=1
-export SCCACHE_BUCKET=ossci-compiler-cache
-export SCCACHE_IGNORE_SERVER_IO_ERROR=1
-export VC_YEAR=2019
+export SCCACHE_BUCKET=ossci-compiler-cache-windows
+export NIGHTLIES_PYTORCH_ROOT="$PYTORCH_ROOT"
 
-if [[ "${DESIRED_CUDA}" == *"cu11"* ]]; then
-    export BUILD_SPLIT_CUDA=ON
+if [[ "$CUDA_VERSION" == "92" || "$CUDA_VERSION" == "100" ]]; then
+  export VC_YEAR=2017
+else
+  export VC_YEAR=2019
 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
 
-echo "Free Space for CUDA DEBUG BUILD"
-if [[ "${CIRCLECI:-}" == 'true' ]]; then
-    export NIGHTLIES_PYTORCH_ROOT="$PYTORCH_ROOT"
-    if [[ -d "C:\\Program Files (x86)\\Microsoft Visual Studio\\2019\\Community" ]]; then
-        rm -rf "C:\\Program Files (x86)\\Microsoft Visual Studio\\2019\\Community"
-    fi
-
-    if [[ -d "C:\\Program Files (x86)\\Microsoft Visual Studio 14.0" ]]; then
-        rm -rf "C:\\Program Files (x86)\\Microsoft Visual Studio 14.0"
-    fi
-
-    if [[ -d "C:\\Program Files (x86)\\Microsoft.NET" ]]; then
-        rm -rf "C:\\Program Files (x86)\\Microsoft.NET"
-    fi
-
-    if [[ -d "C:\\Program Files\\dotnet" ]]; then
-        rm -rf "C:\\Program Files\\dotnet"
-    fi
-
-    if [[ -d "C:\\Program Files (x86)\\dotnet" ]]; then
-        rm -rf "C:\\Program Files (x86)\\dotnet"
-    fi
-
-    if [[ -d "C:\\Program Files (x86)\\Microsoft SQL Server" ]]; then
-        rm -rf "C:\\Program Files (x86)\\Microsoft SQL Server"
-    fi
-
-    if [[ -d "C:\\Program Files (x86)\\Xamarin" ]]; then
-        rm -rf "C:\\Program Files (x86)\\Xamarin"
-    fi
-
-    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
+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
 
 echo "Free space on filesystem before build:"
@@ -70,10 +32,9 @@ 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

@@ -1,10 +1,16 @@
 #!/bin/bash
 set -eux -o pipefail
 
-source "${BINARY_ENV_FILE:-/c/w/env}"
+source "/c/w/env"
 
 export CUDA_VERSION="${DESIRED_CUDA/cu/}"
-export VC_YEAR=2019
+export VC_YEAR=2017
+
+if [[ "$CUDA_VERSION" == "92" || "$CUDA_VERSION" == "100" ]]; then
+  export VC_YEAR=2017
+else
+  export VC_YEAR=2019
+fi
 
 pushd "$BUILDER_ROOT"
 

.circleci/scripts/build_android_gradle.sh

@@ -10,7 +10,7 @@ export ANDROID_HOME=/opt/android/sdk
 
 # Must be in sync with GRADLE_VERSION in docker image for android
 # https://github.com/pietern/pytorch-dockerfiles/blob/master/build.sh#L155
-export GRADLE_VERSION=6.8.3
+export GRADLE_VERSION=4.10.3
 export GRADLE_HOME=/opt/gradle/gradle-$GRADLE_VERSION
 export GRADLE_PATH=$GRADLE_HOME/bin/gradle
 
@@ -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

@@ -10,33 +10,24 @@ pt_checkout="/var/lib/jenkins/workspace"
 # Since we're cat-ing this file, we need to escape all $'s
 echo "cpp_doc_push_script.sh: Invoked with $*"
 
-# for statements like ${1:-${DOCS_INSTALL_PATH:-docs/}}
-# the order of operations goes:
-#   1. Check if there's an argument $1
-#   2. If no argument check for environment var DOCS_INSTALL_PATH
-#   3. If no environment var fall back to default 'docs/'
-
-# NOTE: It might seem weird to gather the second argument before gathering the first argument
-#       but since DOCS_INSTALL_PATH can be derived from DOCS_VERSION it's probably better to
-#       try and gather it first, just so we don't potentially break people who rely on this script
-# Argument 2: What version of the Python API docs we are building.
-version="${2:-${DOCS_VERSION:-master}}"
-if [ -z "$version" ]; then
-echo "error: cpp_doc_push_script.sh: version (arg2) not specified"
-  exit 1
-fi
-
 # Argument 1: Where to copy the built documentation for Python API to
 # (pytorch.github.io/$install_path)
-install_path="${1:-${DOCS_INSTALL_PATH:-docs/${DOCS_VERSION}}}"
+install_path="$1"
 if [ -z "$install_path" ]; then
 echo "error: cpp_doc_push_script.sh: install_path (arg1) not specified"
   exit 1
 fi
 
-is_main_doc=false
+# Argument 2: What version of the Python API docs we are building.
+version="$2"
+if [ -z "$version" ]; then
+echo "error: cpp_doc_push_script.sh: version (arg2) not specified"
+  exit 1
+fi
+
+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 +42,12 @@ 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 +56,8 @@ cp torch/_utils_internal.py tools/shared
 
 # Generate PyTorch files
 time python tools/setup_helpers/generate_code.py \
-  --native-functions-path aten/src/ATen/native/native_functions.yaml \
-  --tags-path aten/src/ATen/native/tags.yaml
+  --declarations-path build/aten/src/ATen/Declarations.yaml \
+  --nn-path aten/src/
 
 # Build the docs
 pushd docs/cpp
@@ -94,15 +87,8 @@ 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 "Automatic sync on $(date)" || 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-cpp -f
-  sleep 30
-  git push -u origin
-fi
-
 popd
 # =================== The above code **should** be executed inside Docker container ===================

.circleci/scripts/driver_update.bat

@@ -1,8 +1,8 @@
-set "DRIVER_DOWNLOAD_LINK=https://s3.amazonaws.com/ossci-windows/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
+set "DRIVER_DOWNLOAD_LINK=https://s3.amazonaws.com/ossci-windows/451.82-tesla-desktop-winserver-2019-2016-international.exe"
+curl --retry 3 -kL %DRIVER_DOWNLOAD_LINK% --output 451.82-tesla-desktop-winserver-2019-2016-international.exe
 if errorlevel 1 exit /b 1
 
-start /wait 452.39-data-center-tesla-desktop-win10-64bit-international.exe -s -noreboot
+start /wait 451.82-tesla-desktop-winserver-2019-2016-international.exe -s -noreboot
 if errorlevel 1 exit /b 1
 
-del 452.39-data-center-tesla-desktop-win10-64bit-international.exe || ver > NUL
+del 451.82-tesla-desktop-winserver-2019-2016-international.exe || ver > NUL

.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/publish_android_snapshot.sh

@@ -5,7 +5,7 @@ set -eu -o pipefail
 export ANDROID_NDK_HOME=/opt/ndk
 export ANDROID_HOME=/opt/android/sdk
 
-export GRADLE_VERSION=6.8.3
+export GRADLE_VERSION=4.10.3
 export GRADLE_HOME=/opt/gradle/gradle-$GRADLE_VERSION
 export GRADLE_PATH=$GRADLE_HOME/bin/gradle
 
@@ -35,9 +35,7 @@ else
   echo "ndk.dir=/opt/ndk" >> $GRADLE_LOCAL_PROPERTIES
 
   echo "SONATYPE_NEXUS_USERNAME=${SONATYPE_NEXUS_USERNAME}" >> $GRADLE_PROPERTIES
-  echo "mavenCentralRepositoryUsername=${SONATYPE_NEXUS_USERNAME}" >> $GRADLE_PROPERTIES
   echo "SONATYPE_NEXUS_PASSWORD=${SONATYPE_NEXUS_PASSWORD}" >> $GRADLE_PROPERTIES
-  echo "mavenCentralRepositoryPassword=${SONATYPE_NEXUS_PASSWORD}" >> $GRADLE_PROPERTIES
 
   echo "signing.keyId=${ANDROID_SIGN_KEY}" >> $GRADLE_PROPERTIES
   echo "signing.password=${ANDROID_SIGN_PASS}" >> $GRADLE_PROPERTIES

.circleci/scripts/python_doc_push_script.sh

@@ -13,37 +13,28 @@ echo "python_doc_push_script.sh: Invoked with $*"
 
 set -ex
 
-# for statements like ${1:-${DOCS_INSTALL_PATH:-docs/}}
-# the order of operations goes:
-#   1. Check if there's an argument $1
-#   2. If no argument check for environment var DOCS_INSTALL_PATH
-#   3. If no environment var fall back to default 'docs/'
-
-# NOTE: It might seem weird to gather the second argument before gathering the first argument
-#       but since DOCS_INSTALL_PATH can be derived from DOCS_VERSION it's probably better to
-#       try and gather it first, just so we don't potentially break people who rely on this script
-# Argument 2: What version of the docs we are building.
-version="${2:-${DOCS_VERSION:-master}}"
-if [ -z "$version" ]; then
-echo "error: python_doc_push_script.sh: version (arg2) not specified"
-  exit 1
-fi
-
 # Argument 1: Where to copy the built documentation to
 # (pytorch.github.io/$install_path)
-install_path="${1:-${DOCS_INSTALL_PATH:-docs/${DOCS_VERSION}}}"
+install_path="$1"
 if [ -z "$install_path" ]; then
 echo "error: python_doc_push_script.sh: install_path (arg1) not specified"
   exit 1
 fi
 
-is_main_doc=false
+# Argument 2: What version of the docs we are building.
+version="$2"
+if [ -z "$version" ]; then
+echo "error: python_doc_push_script.sh: version (arg2) not specified"
+  exit 1
+fi
+
+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"
-branch="${3:-${DOCS_BRANCH:-site}}"
+branch="$3"
 if [ -z "$branch" ]; then
 echo "error: python_doc_push_script.sh: branch (arg3) not specified"
   exit 1
@@ -51,28 +42,7 @@ fi
 
 echo "install_path: $install_path  version: $version"
 
-
-build_docs () {
-  set +e
-  set -o pipefail
-  make $1 2>&1 | tee /tmp/docs_build.txt
-  code=$?
-  if [ $code -ne 0 ]; then
-    set +x
-    echo =========================
-    grep "WARNING:" /tmp/docs_build.txt
-    echo =========================
-    echo Docs build failed. If the failure is not clear, scan back in the log
-    echo for any WARNINGS or for the line "build finished with problems"
-    echo "(tried to echo the WARNINGS above the ==== line)"
-    echo =========================
-  fi
-  set -ex
-  return $code
-}
-
-
-git clone https://github.com/pytorch/pytorch.github.io -b $branch --depth 1
+git clone https://github.com/pytorch/pytorch.github.io -b $branch
 pushd pytorch.github.io
 
 export LC_ALL=C
@@ -82,13 +52,15 @@ rm -rf pytorch || true
 
 # Get all the documentation sources, put them in one place
 pushd "$pt_checkout"
+checkout_install_torchvision
 pushd docs
+rm -rf source/torchvision
+cp -a ../vision/docs/source source/torchvision
 
 # Build the docs
 pip -q install -r requirements.txt
-if [ "$is_main_doc" = true ]; then
-  build_docs html
-  [ $? -eq 0 ] || exit $?
+if [ "$is_master_doc" = true ]; then
+  make html
   make coverage
   # Now we have the coverage report, we need to make sure it is empty.
   # Count the number of lines in the file and turn that number into a variable
@@ -109,9 +81,8 @@ if [ "$is_main_doc" = true ]; then
     exit 1
   fi
 else
-  # skip coverage, format for stable or tags
-  build_docs html-stable
-  [ $? -eq 0 ] || exit $?
+  # Don't fail the build on coverage problems
+  make html-stable
 fi
 
 # Move them into the docs repo
@@ -120,6 +91,14 @@ popd
 git rm -rf "$install_path" || true
 mv "$pt_checkout/docs/build/html" "$install_path"
 
+# Add the version handler by search and replace.
+# XXX: Consider moving this to the docs Makefile or site build
+if [ "$is_master_doc" = true ]; then
+  find "$install_path" -name "*.html" -print0 | xargs -0 perl -pi -w -e "s@master\s+\((\d\.\d\.[A-Fa-f0-9]+\+[A-Fa-f0-9]+)\s+\)@<a href='http://pytorch.org/docs/versions.html'>\1 \&#x25BC</a>@g"
+else
+  find "$install_path" -name "*.html" -print0 | xargs -0 perl -pi -w -e "s@master\s+\((\d\.\d\.[A-Fa-f0-9]+\+[A-Fa-f0-9]+)\s+\)@<a href='http://pytorch.org/docs/versions.html'>$version \&#x25BC</a>@g"
+fi
+
 # Prevent Google from indexing $install_path/_modules. This folder contains
 # generated source files.
 # NB: the following only works on gnu sed. The sed shipped with mac os is different.
@@ -131,15 +110,8 @@ git status
 git config user.email "soumith+bot@pytorch.org"
 git config user.name "pytorchbot"
 # If there aren't changes, don't make a commit; push is no-op
-git commit -m "Generate Python docs from pytorch/pytorch@${GITHUB_SHA}" || true
+git commit -m "auto-generating sphinx docs" || 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

@@ -7,9 +7,6 @@ sudo rm -f /etc/apt/heroku.list
 sudo rm -f /etc/apt/openjdk-r-ubuntu-ppa-xenial.list
 sudo rm -f /etc/apt/partner.list
 
-# To increase the network reliability, let apt decide which mirror is best to use
-sudo sed -i -e 's/http:\/\/.*archive/mirror:\/\/mirrors/' -e 's/\/ubuntu\//\/mirrors.txt/' /etc/apt/sources.list
-
 retry () {
   $*  || $* || $* || $* || $*
 }
@@ -27,12 +24,10 @@ retry sudo apt-get -y install \
 echo "== DOCKER VERSION =="
 docker version
 
-if ! command -v aws >/dev/null; then
-  retry sudo pip3 -q install awscli==1.19.64
-fi
+retry sudo pip -q install awscli==1.16.35
 
 if [ -n "${USE_CUDA_DOCKER_RUNTIME:-}" ]; then
-  DRIVER_FN="NVIDIA-Linux-x86_64-515.57.run"
+  DRIVER_FN="NVIDIA-Linux-x86_64-450.51.06.run"
   wget "https://s3.amazonaws.com/ossci-linux/nvidia_driver/$DRIVER_FN"
   sudo /bin/bash "$DRIVER_FN" -s --no-drm || (sudo cat /var/log/nvidia-installer.log && false)
   nvidia-smi
@@ -43,9 +38,9 @@ if [ -n "${USE_CUDA_DOCKER_RUNTIME:-}" ]; then
   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
+  sudo apt-get update -qq
   # Necessary to get the `--gpus` flag to function within docker
-  retry sudo apt-get install -y nvidia-container-toolkit
+  sudo apt-get install -y nvidia-container-toolkit
   sudo systemctl restart docker
 else
   # Explicitly remove nvidia docker apt repositories if not building for cuda
@@ -53,50 +48,43 @@ else
 fi
 
 add_to_env_file() {
-  local name=$1
-  local value=$2
-  case "$value" in
-    *\ *)
-      # BASH_ENV should be set by CircleCI
-      echo "${name}='${value}'" >> "${BASH_ENV:-/tmp/env}"
-      ;;
-    *)
-      echo "${name}=${value}" >> "${BASH_ENV:-/tmp/env}"
-      ;;
-  esac
+  local content
+  content=$1
+  # BASH_ENV should be set by CircleCI
+  echo "${content}" >> "${BASH_ENV:-/tmp/env}"
 }
 
-add_to_env_file CI_MASTER "${CI_MASTER:-}"
-add_to_env_file COMMIT_SOURCE "${CIRCLE_BRANCH:-}"
-add_to_env_file BUILD_ENVIRONMENT "${BUILD_ENVIRONMENT}"
-add_to_env_file CIRCLE_PULL_REQUEST "${CIRCLE_PULL_REQUEST}"
+add_to_env_file "IN_CIRCLECI=1"
+add_to_env_file "COMMIT_SOURCE=${CIRCLE_BRANCH:-}"
+add_to_env_file "BUILD_ENVIRONMENT=${BUILD_ENVIRONMENT}"
+add_to_env_file "CIRCLE_PULL_REQUEST=${CIRCLE_PULL_REQUEST}"
 
 
 if [[ "${BUILD_ENVIRONMENT}" == *-build ]]; then
-  add_to_env_file SCCACHE_BUCKET ossci-compiler-cache-circleci-v2
+  add_to_env_file "SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2"
 
   SCCACHE_MAX_JOBS=$(( $(nproc) - 1 ))
   MEMORY_LIMIT_MAX_JOBS=8  # the "large" resource class on CircleCI has 32 CPU cores, if we use all of them we'll OOM
   MAX_JOBS=$(( ${SCCACHE_MAX_JOBS} > ${MEMORY_LIMIT_MAX_JOBS} ? ${MEMORY_LIMIT_MAX_JOBS} : ${SCCACHE_MAX_JOBS} ))
-  add_to_env_file MAX_JOBS "${MAX_JOBS}"
+  add_to_env_file "MAX_JOBS=${MAX_JOBS}"
 
   if [ -n "${USE_CUDA_DOCKER_RUNTIME:-}" ]; then
-    add_to_env_file TORCH_CUDA_ARCH_LIST 5.2
+    add_to_env_file "TORCH_CUDA_ARCH_LIST=5.2"
   fi
 
   if [[ "${BUILD_ENVIRONMENT}" == *xla* ]]; then
     # This IAM user allows write access to S3 bucket for sccache & bazels3cache
     set +x
-    add_to_env_file XLA_CLANG_CACHE_S3_BUCKET_NAME "${XLA_CLANG_CACHE_S3_BUCKET_NAME:-}"
-    add_to_env_file AWS_ACCESS_KEY_ID "${CIRCLECI_AWS_ACCESS_KEY_FOR_SCCACHE_AND_XLA_BAZEL_S3_BUCKET_V2:-}"
-    add_to_env_file AWS_SECRET_ACCESS_KEY "${CIRCLECI_AWS_SECRET_KEY_FOR_SCCACHE_AND_XLA_BAZEL_S3_BUCKET_V2:-}"
+    add_to_env_file "XLA_CLANG_CACHE_S3_BUCKET_NAME=${XLA_CLANG_CACHE_S3_BUCKET_NAME:-}"
+    add_to_env_file "AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_SCCACHE_AND_XLA_BAZEL_S3_BUCKET_V2:-}"
+    add_to_env_file "AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_SCCACHE_AND_XLA_BAZEL_S3_BUCKET_V2:-}"
     set -x
   else
     # This IAM user allows write access to S3 bucket for sccache
     set +x
-    add_to_env_file XLA_CLANG_CACHE_S3_BUCKET_NAME "${XLA_CLANG_CACHE_S3_BUCKET_NAME:-}"
-    add_to_env_file AWS_ACCESS_KEY_ID "${CIRCLECI_AWS_ACCESS_KEY_FOR_SCCACHE_S3_BUCKET_V4:-}"
-    add_to_env_file AWS_SECRET_ACCESS_KEY "${CIRCLECI_AWS_SECRET_KEY_FOR_SCCACHE_S3_BUCKET_V4:-}"
+    add_to_env_file "XLA_CLANG_CACHE_S3_BUCKET_NAME=${XLA_CLANG_CACHE_S3_BUCKET_NAME:-}"
+    add_to_env_file "AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_SCCACHE_S3_BUCKET_V4:-}"
+    add_to_env_file "AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_SCCACHE_S3_BUCKET_V4:-}"
     set -x
   fi
 fi
@@ -105,7 +93,5 @@ fi
 set +x
 export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_ECR_READ_WRITE_V4:-}
 export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_ECR_READ_WRITE_V4:-}
-export AWS_ACCOUNT_ID=$(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
+eval "$(aws ecr get-login --region us-east-1 --no-include-email)"
 set -x

.circleci/scripts/trigger_azure_pipeline.py

@@ -1,140 +0,0 @@
-# Documentation: https://docs.microsoft.com/en-us/rest/api/azure/devops/build/?view=azure-devops-rest-6.0
-
-import re
-import json
-import os
-import sys
-import requests
-import time
-
-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_COMMIT = os.environ.get("CIRCLE_SHA1", "")
-
-build_base_url = AZURE_PIPELINE_BASE_URL + "_apis/build/builds?api-version=6.0"
-
-s = requests.Session()
-s.headers.update({"Authorization": "Basic " + AZURE_DEVOPS_PAT_BASE64})
-
-def submit_build(pipeline_id, project_id, source_branch, source_version):
-    print("Submitting build for branch: " + source_branch)
-    print("Commit SHA1: ", source_version)
-
-    run_build_raw = s.post(build_base_url, json={
-        "definition": {"id": pipeline_id},
-        "project": {"id": project_id},
-        "sourceBranch": source_branch,
-        "sourceVersion": source_version
-    })
-
-    try:
-        run_build_json = run_build_raw.json()
-    except json.decoder.JSONDecodeError as e:
-        print(e)
-        print("Failed to parse the response. Check if the Azure DevOps PAT is incorrect or expired.")
-        sys.exit(-1)
-
-    build_id = run_build_json['id']
-
-    print("Submitted bulid: " + str(build_id))
-    print("Bulid URL: " + run_build_json['url'])
-    return build_id
-
-def get_build(_id):
-    get_build_url = AZURE_PIPELINE_BASE_URL + f"/_apis/build/builds/{_id}?api-version=6.0"
-    get_build_raw = s.get(get_build_url)
-    return get_build_raw.json()
-
-def get_build_logs(_id):
-    get_build_logs_url = AZURE_PIPELINE_BASE_URL + f"/_apis/build/builds/{_id}/logs?api-version=6.0"
-    get_build_logs_raw = s.get(get_build_logs_url)
-    return get_build_logs_raw.json()
-
-def get_log_content(url):
-    resp = s.get(url)
-    return resp.text
-
-def wait_for_build(_id):
-    build_detail = get_build(_id)
-    build_status = build_detail['status']
-
-    while build_status == 'notStarted':
-        print('Waiting for run to start: ' + str(_id))
-        sys.stdout.flush()
-        try:
-            build_detail = get_build(_id)
-            build_status = build_detail['status']
-        except Exception as e:
-            print("Error getting build")
-            print(e)
-
-        time.sleep(30)
-
-    print("Bulid started: ", str(_id))
-
-    handled_logs = set()
-    while build_status == 'inProgress':
-        try:
-            print("Waiting for log: " + str(_id))
-            logs = get_build_logs(_id)
-        except Exception as e:
-            print("Error fetching logs")
-            print(e)
-            time.sleep(30)
-            continue
-
-        for log in logs['value']:
-            log_id = log['id']
-            if log_id in handled_logs:
-                continue
-            handled_logs.add(log_id)
-            print('Fetching log: \n' + log['url'])
-            try:
-                log_content = get_log_content(log['url'])
-                print(log_content)
-            except Exception as e:
-                print("Error getting log content")
-                print(e)
-            sys.stdout.flush()
-        build_detail = get_build(_id)
-        build_status = build_detail['status']
-        time.sleep(30)
-
-    build_result = build_detail['result']
-
-    print("Bulid status: " + build_status)
-    print("Bulid result: " + build_result)
-
-    return build_status, build_result
-
-if __name__ == '__main__':
-    # Convert the branch name for Azure DevOps
-    match = re.search(r'pull/(\d+)', TARGET_BRANCH)
-    if match is not None:
-        pr_num = match.group(1)
-        SOURCE_BRANCH = f'refs/pull/{pr_num}/head'
-    else:
-        SOURCE_BRANCH = f'refs/heads/{TARGET_BRANCH}'
-
-    MAX_RETRY = 2
-    retry = MAX_RETRY
-
-    while retry > 0:
-        build_id = submit_build(PIPELINE_ID, PROJECT_ID, SOURCE_BRANCH, TARGET_COMMIT)
-        build_status, build_result = wait_for_build(build_id)
-
-        if build_result != 'succeeded':
-            retry = retry - 1
-            if retry > 0:
-                print("Retrying... remaining attempt: " + str(retry))
-                # Wait a bit before retrying
-                time.sleep((MAX_RETRY - retry) * 120)
-                continue
-            else:
-                print("No more chance to retry. Giving up.")
-                sys.exit(-1)
-        else:
-            break

.circleci/scripts/upload_binary_size_to_scuba.py

@@ -0,0 +1,147 @@
+import glob
+import json
+import logging
+import os
+import os.path
+import pathlib
+import re
+import sys
+import time
+import zipfile
+
+import requests
+
+
+def get_size(file_dir):
+    try:
+        # we should only expect one file, if no, something is wrong
+        file_name = glob.glob(os.path.join(file_dir, "*"))[0]
+        return os.stat(file_name).st_size
+    except:
+        logging.exception(f"error getting file from: {file_dir}")
+        return 0
+
+
+def build_message(size):
+    pkg_type, py_ver, cu_ver, *_ = os.environ.get("BUILD_ENVIRONMENT", "").split() + [
+        None,
+        None,
+        None,
+    ]
+    os_name = os.uname()[0].lower()
+    if os_name == "darwin":
+        os_name = "macos"
+    return {
+        "normal": {
+            "os": os_name,
+            "pkg_type": pkg_type,
+            "py_ver": py_ver,
+            "cu_ver": cu_ver,
+            "pr": os.environ.get("CIRCLE_PR_NUMBER"),
+            "build_num": os.environ.get("CIRCLE_BUILD_NUM"),
+            "sha1": os.environ.get("CIRCLE_SHA1"),
+            "branch": os.environ.get("CIRCLE_BRANCH"),
+        },
+        "int": {
+            "time": int(time.time()),
+            "size": size,
+            "commit_time": int(os.environ.get("COMMIT_TIME", "0")),
+            "run_duration": int(time.time() - os.path.getmtime(os.path.realpath(__file__))),
+        },
+    }
+
+
+def send_message(messages):
+    access_token = os.environ.get("SCRIBE_GRAPHQL_ACCESS_TOKEN")
+    if not access_token:
+        raise ValueError("Can't find access token from environment variable")
+    url = "https://graph.facebook.com/scribe_logs"
+    r = requests.post(
+        url,
+        data={
+            "access_token": access_token,
+            "logs": json.dumps(
+                [
+                    {
+                        "category": "perfpipe_pytorch_binary_size",
+                        "message": json.dumps(message),
+                        "line_escape": False,
+                    }
+                    for message in messages
+                ]
+            ),
+        },
+    )
+    print(r.text)
+    r.raise_for_status()
+
+
+def report_android_sizes(file_dir):
+    def gen_sizes():
+        # we should only expect one file, if no, something is wrong
+        aar_files = list(pathlib.Path(file_dir).rglob("pytorch_android-*.aar"))
+        if len(aar_files) != 1:
+            logging.exception(f"error getting aar files from: {file_dir} / {aar_files}")
+            return
+
+        aar_file = aar_files[0]
+        zf = zipfile.ZipFile(aar_file)
+        for info in zf.infolist():
+            # Scan ".so" libs in `jni` folder. Examples:
+            # jni/arm64-v8a/libfbjni.so
+            # jni/arm64-v8a/libpytorch_jni.so
+            m = re.match(r"^jni/([^/]+)/(.*\.so)$", info.filename)
+            if not m:
+                continue
+            arch, lib = m.groups()
+            # report per architecture library size
+            yield [arch, lib, info.compress_size, info.file_size]
+
+        # report whole package size
+        yield ["aar", aar_file.name, os.stat(aar_file).st_size, 0]
+
+    def gen_messages():
+        android_build_type = os.environ.get("ANDROID_BUILD_TYPE")
+        for arch, lib, comp_size, uncomp_size in gen_sizes():
+            print(android_build_type, arch, lib, comp_size, uncomp_size)
+            yield {
+                "normal": {
+                    "os": "android",
+                    # TODO: create dedicated columns
+                    "pkg_type": "{}/{}/{}".format(android_build_type, arch, lib),
+                    "cu_ver": "",  # dummy value for derived field `build_name`
+                    "py_ver": "",  # dummy value for derived field `build_name`
+                    "pr": os.environ.get("CIRCLE_PR_NUMBER"),
+                    "build_num": os.environ.get("CIRCLE_BUILD_NUM"),
+                    "sha1": os.environ.get("CIRCLE_SHA1"),
+                    "branch": os.environ.get("CIRCLE_BRANCH"),
+                },
+                "int": {
+                    "time": int(time.time()),
+                    "commit_time": int(os.environ.get("COMMIT_TIME", "0")),
+                    "run_duration": int(time.time() - os.path.getmtime(os.path.realpath(__file__))),
+                    "size": comp_size,
+                    "raw_size": uncomp_size,
+                },
+            }
+
+    send_message(list(gen_messages()))
+
+
+if __name__ == "__main__":
+    file_dir = os.environ.get(
+        "PYTORCH_FINAL_PACKAGE_DIR", "/home/circleci/project/final_pkgs"
+    )
+    if len(sys.argv) == 2:
+        file_dir = sys.argv[1]
+    print("checking dir: " + file_dir)
+
+    if "-android" in os.environ.get("BUILD_ENVIRONMENT", ""):
+        report_android_sizes(file_dir)
+    else:
+        size = get_size(file_dir)
+        if size != 0:
+            try:
+                send_message([build_message(size)])
+            except:
+                logging.exception("can't send message")

.circleci/scripts/vs_install.ps1

@@ -1,10 +1,7 @@
-# https://developercommunity.visualstudio.com/t/install-specific-version-of-vs-component/1142479
-# Where to find the links: https://docs.microsoft.com/en-us/visualstudio/releases/2019/history#release-dates-and-build-numbers
-
-# BuildTools from S3
-$VS_DOWNLOAD_LINK = "https://s3.amazonaws.com/ossci-windows/vs${env:VS_VERSION}_BuildTools.exe"
+$VS_DOWNLOAD_LINK = "https://aka.ms/vs/15/release/vs_buildtools.exe"
 $COLLECT_DOWNLOAD_LINK = "https://aka.ms/vscollect.exe"
 $VS_INSTALL_ARGS = @("--nocache","--quiet","--wait", "--add Microsoft.VisualStudio.Workload.VCTools",
+                                                     "--add Microsoft.VisualStudio.Component.VC.Tools.14.13",
                                                      "--add Microsoft.Component.MSBuild",
                                                      "--add Microsoft.VisualStudio.Component.Roslyn.Compiler",
                                                      "--add Microsoft.VisualStudio.Component.TextTemplating",
@@ -14,45 +11,17 @@ $VS_INSTALL_ARGS = @("--nocache","--quiet","--wait", "--add Microsoft.VisualStud
                                                      "--add Microsoft.VisualStudio.Component.VC.Tools.x86.x64",
                                                      "--add Microsoft.VisualStudio.ComponentGroup.NativeDesktop.Win81")
 
-if (${env:INSTALL_WINDOWS_SDK} -eq "1") {
-    $VS_INSTALL_ARGS += "--add Microsoft.VisualStudio.Component.Windows10SDK.19041"
-}
-
-if (Test-Path "${env:ProgramFiles(x86)}\Microsoft Visual Studio\Installer\vswhere.exe") {
-    $VS_VERSION_major = [int] ${env:VS_VERSION}.split(".")[0]
-    $existingPath = & "${env:ProgramFiles(x86)}\Microsoft Visual Studio\Installer\vswhere.exe" -products "Microsoft.VisualStudio.Product.BuildTools" -version "[${env:VS_VERSION}, ${env:VS_VERSION_major + 1})" -property installationPath
-    if (($existingPath -ne $null) -and (!${env:CIRCLECI})) {
-        echo "Found correctly versioned existing BuildTools installation in $existingPath"
-        exit 0
-    }
-    $pathToRemove = & "${env:ProgramFiles(x86)}\Microsoft Visual Studio\Installer\vswhere.exe" -products "Microsoft.VisualStudio.Product.BuildTools" -property installationPath
-}
-
-echo "Downloading VS installer from S3."
 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"
+    echo "Download of the VS 2017 installer failed"
     exit 1
 }
 
-if ($pathToRemove -ne $null) {
-    echo "Uninstalling $pathToRemove."
-    $VS_UNINSTALL_ARGS = @("uninstall", "--installPath", "`"$pathToRemove`"", "--quiet","--wait")
-    $process = Start-Process "${PWD}\vs_installer.exe" -ArgumentList $VS_UNINSTALL_ARGS -NoNewWindow -Wait -PassThru
-    $exitCode = $process.ExitCode
-    if (($exitCode -ne 0) -and ($exitCode -ne 3010)) {
-        echo "Original BuildTools uninstall failed with code $exitCode"
-        exit 1
-    }
-    echo "Other versioned BuildTools uninstalled."
-}
-
-echo "Installing Visual Studio version ${env:VS_VERSION}."
 $process = Start-Process "${PWD}\vs_installer.exe" -ArgumentList $VS_INSTALL_ARGS -NoNewWindow -Wait -PassThru
 Remove-Item -Path vs_installer.exe -Force
 $exitCode = $process.ExitCode
 if (($exitCode -ne 0) -and ($exitCode -ne 3010)) {
-    echo "VS 2019 installer exited with code $exitCode, which should be one of [0, 3010]."
+    echo "VS 2017 installer exited with code $exitCode, which should be one of [0, 3010]."
     curl.exe --retry 3 -kL $COLLECT_DOWNLOAD_LINK --output Collect.exe
     if ($LASTEXITCODE -ne 0) {
         echo "Download of the VS Collect tool failed."
@@ -60,6 +29,6 @@ if (($exitCode -ne 0) -and ($exitCode -ne 3010)) {
     }
     Start-Process "${PWD}\Collect.exe" -NoNewWindow -Wait -PassThru
     New-Item -Path "C:\w\build-results" -ItemType "directory" -Force
-    Copy-Item -Path "${env:TEMP}\vslogs.zip" -Destination "C:\w\build-results\"
+    Copy-Item -Path "C:\Users\circleci\AppData\Local\Temp\vslogs.zip" -Destination "C:\w\build-results\"
     exit 1
 }

.circleci/scripts/vs_install_cmath.ps1

@@ -1,5 +0,0 @@
-$CMATH_DOWNLOAD_LINK = "https://raw.githubusercontent.com/microsoft/STL/12c684bba78f9b032050526abdebf14f58ca26a3/stl/inc/cmath"
-$VC14_28_INSTALL_PATH="C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.28.29910\include"
-
-curl.exe --retry 3 -kL $CMATH_DOWNLOAD_LINK --output "$home\cmath"
-Move-Item -Path "$home\cmath" -Destination "$VC14_28_INSTALL_PATH" -Force

.circleci/scripts/windows_cuda_install.sh

@@ -1,75 +1,57 @@
 #!/bin/bash
 set -eux -o pipefail
 
-case ${CUDA_VERSION} in
-    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"
-        ;;
-    11.3)
-        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 $CUDA_VERSION is not supported yet"
-        exit 1
-        ;;
-esac
-
-
-if [[ -f "/c/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v${CUDA_VERSION}/bin/nvcc.exe" ]]; then
-    echo "Existing CUDA v${CUDA_VERSION} installation found, skipping install"
+if [[ "$CUDA_VERSION" == "10" ]]; then
+    cuda_complete_version="10.1"
+    cuda_installer_name="cuda_10.1.243_426.00_win10"
+    msbuild_project_dir="CUDAVisualStudioIntegration/extras/visual_studio_integration/MSBuildExtensions"
+    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"
+elif [[ "$CUDA_VERSION" == "11" ]]; then
+    cuda_complete_version="11.0"
+    cuda_installer_name="cuda_11.0.2_451.48_win10"
+    msbuild_project_dir="visual_studio_integration/CUDAVisualStudioIntegration/extras/visual_studio_integration/MSBuildExtensions"
+    cuda_install_packages="nvcc_11.0 cuobjdump_11.0 nvprune_11.0 nvprof_11.0 cupti_11.0 cublas_11.0 cublas_dev_11.0 cudart_11.0 cufft_11.0 cufft_dev_11.0 curand_11.0 curand_dev_11.0 cusolver_11.0 cusolver_dev_11.0 cusparse_11.0 cusparse_dev_11.0 npp_11.0 npp_dev_11.0 nvrtc_11.0 nvrtc_dev_11.0 nvml_dev_11.0"
 else
-    tmp_dir=$(mktemp -d)
-    (
-        # no need to popd after, the subshell shouldn't affect the parent shell
-        pushd "${tmp_dir}"
-        cuda_installer_link="https://ossci-windows.s3.amazonaws.com/${cuda_installer_name}.exe"
-
-        curl --retry 3 -kLO $cuda_installer_link
-        7z x ${cuda_installer_name}.exe -o${cuda_installer_name}
-        pushd ${cuda_installer_name}
-        mkdir cuda_install_logs
-
-        set +e
-
-        # This breaks for some reason if you quote cuda_install_packages
-        # shellcheck disable=SC2086
-        ./setup.exe -s ${cuda_install_packages} -loglevel:6 -log:"$(pwd -W)/cuda_install_logs"
-
-        set -e
-
-        if [[ ! -f "/c/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v${CUDA_VERSION}/bin/nvcc.exe" ]]; then
-            echo "CUDA installation failed"
-            mkdir -p /c/w/build-results
-            7z a "c:\\w\\build-results\\cuda_install_logs.7z" cuda_install_logs
-            exit 1
-        fi
-    )
-    rm -rf "${tmp_dir}"
+    echo "CUDA_VERSION $CUDA_VERSION is not supported yet"
+    exit 1
 fi
 
-if [[ -f "/c/Program Files/NVIDIA Corporation/NvToolsExt/bin/x64/nvToolsExt64_1.dll" ]]; then
-    echo "Existing nvtools installation found, skipping install"
+cuda_installer_link="https://ossci-windows.s3.amazonaws.com/${cuda_installer_name}.exe"
+
+curl --retry 3 -kLO $cuda_installer_link
+7z x ${cuda_installer_name}.exe -o${cuda_installer_name}
+cd ${cuda_installer_name}
+mkdir cuda_install_logs
+
+set +e
+
+./setup.exe -s ${cuda_install_packages} -loglevel:6 -log:"$(pwd -W)/cuda_install_logs"
+
+set -e
+
+if [[ "${VC_YEAR}" == "2017" ]]; then
+    cp -r ${msbuild_project_dir}/* "C:/Program Files (x86)/Microsoft Visual Studio/2017/${VC_PRODUCT}/Common7/IDE/VC/VCTargets/BuildCustomizations/"
 else
-    # create tmp dir for download
-    tmp_dir=$(mktemp -d)
-    (
-        # no need to popd after, the subshell shouldn't affect the parent shell
-        pushd "${tmp_dir}"
-        curl --retry 3 -kLO https://ossci-windows.s3.amazonaws.com/NvToolsExt.7z
-        7z x NvToolsExt.7z -oNvToolsExt
-        mkdir -p "C:/Program Files/NVIDIA Corporation/NvToolsExt"
-        cp -r NvToolsExt/* "C:/Program Files/NVIDIA Corporation/NvToolsExt/"
-    )
-    rm -rf "${tmp_dir}"
+    cp -r ${msbuild_project_dir}/* "C:/Program Files (x86)/Microsoft Visual Studio/2019/${VC_PRODUCT}/MSBuild/Microsoft/VC/v160/BuildCustomizations/"
 fi
+
+if ! ls "/c/Program Files/NVIDIA Corporation/NvToolsExt/bin/x64/nvToolsExt64_1.dll"
+then
+    curl --retry 3 -kLO https://ossci-windows.s3.amazonaws.com/NvToolsExt.7z
+    7z x NvToolsExt.7z -oNvToolsExt
+    mkdir -p "C:/Program Files/NVIDIA Corporation/NvToolsExt"
+    cp -r NvToolsExt/* "C:/Program Files/NVIDIA Corporation/NvToolsExt/"
+    export NVTOOLSEXT_PATH="C:\\Program Files\\NVIDIA Corporation\\NvToolsExt\\"
+fi
+
+if ! ls "/c/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v${cuda_complete_version}/bin/nvcc.exe"
+then
+    echo "CUDA installation failed"
+    mkdir -p /c/w/build-results
+    7z a "c:\\w\\build-results\\cuda_install_logs.7z" cuda_install_logs
+    exit 1
+fi
+
+cd ..
+rm -rf ./${cuda_installer_name}
+rm -f ./${cuda_installer_name}.exe

.circleci/scripts/windows_cudnn_install.sh

@@ -1,52 +1,21 @@
 #!/bin/bash
 set -eux -o pipefail
 
-
-windows_s3_link="https://ossci-windows.s3.amazonaws.com"
-
-case ${CUDA_VERSION} in
-    10.2)
-        cudnn_file_name="cudnn-${CUDA_VERSION}-windows10-x64-v7.6.5.32"
-        ;;
-    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"
-        ;;
-    *)
-        echo "CUDA_VERSION: ${CUDA_VERSION} not supported yet"
-        exit 1
-        ;;
-esac
-
-cudnn_installer_name="cudnn_installer.zip"
-cudnn_installer_link="${windows_s3_link}/${cudnn_file_name}.zip"
-cudnn_install_folder="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v${CUDA_VERSION}/"
-
-if [[ -f "${cudnn_install_folder}/include/cudnn.h" ]]; then
-    echo "Existing cudnn installation found, skipping install..."
+if [[ "$CUDA_VERSION" == "10" ]]; then
+    cuda_complete_version="10.1"
+    cudnn_installer_name="cudnn-10.1-windows10-x64-v7.6.4.38"
+elif [[ "$CUDA_VERSION" == "11" ]]; then
+    cuda_complete_version="11.0"
+    cudnn_installer_name="cudnn-11.0-windows-x64-v8.0.2.39"
 else
-    tmp_dir=$(mktemp -d)
-    (
-        pushd "${tmp_dir}"
-        curl --retry 3 -o "${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}"
+    echo "CUDNN for CUDA_VERSION $CUDA_VERSION is not supported yet"
+    exit 1
 fi
+
+cudnn_installer_link="https://ossci-windows.s3.amazonaws.com/${cudnn_installer_name}.zip"
+
+curl --retry 3 -O $cudnn_installer_link
+7z x ${cudnn_installer_name}.zip -ocudnn
+cp -r cudnn/cuda/* "C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v${cuda_complete_version}/"
+rm -rf cudnn
+rm -f ${cudnn_installer_name}.zip

.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

@@ -15,15 +15,11 @@ pytorch_params: &pytorch_params
     build_only:
       type: string
       default: ""
-    ci_master:
-      type: string
-      default: ""
   environment:
     BUILD_ENVIRONMENT: << parameters.build_environment >>
     DOCKER_IMAGE: << parameters.docker_image >>
     USE_CUDA_DOCKER_RUNTIME: << parameters.use_cuda_docker_runtime >>
     BUILD_ONLY: << parameters.build_only >>
-    CI_MASTER: << pipeline.parameters.run_master_build >>
   resource_class: << parameters.resource_class >>
 
 pytorch_ios_params: &pytorch_ios_params
@@ -40,23 +36,11 @@ pytorch_ios_params: &pytorch_ios_params
     op_list:
       type: string
       default: ""
-    use_metal:
-      type: string
-      default: "0"
-    lite_interpreter:
-      type: string
-      default: "1"
-    use_coreml:
-      type: string
-      default: "0"
   environment:
     BUILD_ENVIRONMENT: << parameters.build_environment >>
     IOS_ARCH: << parameters.ios_arch >>
     IOS_PLATFORM: << parameters.ios_platform >>
     SELECTED_OP_LIST: << parameters.op_list >>
-    USE_PYTORCH_METAL: << parameters.use_metal >>
-    BUILD_LITE_INTERPRETER: << parameters.lite_interpreter >>
-    USE_COREML_DELEGATE: << parameters.use_coreml >>
 
 pytorch_windows_params: &pytorch_windows_params
   parameters:
@@ -71,13 +55,10 @@ pytorch_windows_params: &pytorch_windows_params
       default: ""
     cuda_version:
       type: string
-      default: "10.1"
+      default: "10"
     python_version:
       type: string
-      default: "3.8"
-    vs_version:
-      type: string
-      default: "16.8.6"
+      default: "3.6"
     vc_version:
       type: string
       default: "14.16"
@@ -95,11 +76,10 @@ pytorch_windows_params: &pytorch_windows_params
     SCCACHE_BUCKET: "ossci-compiler-cache"
     CUDA_VERSION: <<parameters.cuda_version>>
     PYTHON_VERSION: <<parameters.python_version>>
-    VS_VERSION: <<parameters.vs_version>>
     VC_VERSION: <<parameters.vc_version>>
     VC_YEAR: <<parameters.vc_year>>
     VC_PRODUCT: <<parameters.vc_product>>
     USE_CUDA: <<parameters.use_cuda>>
-    TORCH_CUDA_ARCH_LIST: "5.2 7.5"
+    TORCH_CUDA_ARCH_LIST: "7.5"
     JOB_BASE_NAME: <<parameters.test_name>>
     JOB_EXECUTOR: <<parameters.executor>>

.circleci/verbatim-sources/commands.yml

@@ -103,7 +103,7 @@ commands:
           name: (Optional) Merge target branch
           no_output_timeout: "10m"
           command: |
-            if [[ -n "$CIRCLE_PULL_REQUEST" && "$CIRCLE_BRANCH" != "nightly" ]]; then
+            if [ -n "$CIRCLE_PULL_REQUEST" ]; then
               PR_NUM=$(basename $CIRCLE_PULL_REQUEST)
               CIRCLE_PR_BASE_BRANCH=$(curl -s https://api.github.com/repos/$CIRCLE_PROJECT_USERNAME/$CIRCLE_PROJECT_REPONAME/pulls/$PR_NUM | jq -r '.base.ref')
               if [[ "${BUILD_ENVIRONMENT}" == *"xla"* || "${BUILD_ENVIRONMENT}" == *"gcc5"* ]] ; then
@@ -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 .circleci/scripts/upload_binary_size_to_scuba.py android

.circleci/verbatim-sources/header-section.yml

@@ -11,21 +11,19 @@ parameters:
   run_binary_tests:
     type: boolean
     default: false
-  run_build:
-    type: boolean
-    default: true
-  run_master_build:
-    type: boolean
-    default: false
-  run_slow_gradcheck_build:
-    type: boolean
-    default: false
+
+docker_config_defaults: &docker_config_defaults
+  user: jenkins
+  aws_auth:
+    # This IAM user only allows read-write access to ECR
+    aws_access_key_id: ${CIRCLECI_AWS_ACCESS_KEY_FOR_ECR_READ_WRITE_V4}
+    aws_secret_access_key: ${CIRCLECI_AWS_SECRET_KEY_FOR_ECR_READ_WRITE_V4}
 
 executors:
   windows-with-nvidia-gpu:
     machine:
       resource_class: windows.gpu.nvidia.medium
-      image: windows-server-2019-nvidia:previous
+      image: windows-server-2019-nvidia:stable
       shell: bash.exe
 
   windows-xlarge-cpu-with-nvidia-cuda:

.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

@@ -1,8 +1,207 @@
-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: save binary size
+        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 /pytorch/.circleci/scripts/upload_binary_size_to_scuba.py || 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-1604:202007-01
+    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="${CONDA_PYTORCHBOT_TOKEN}" \
+              .circleci/scripts/binary_upload.sh
+
+  # Nighlty build smoke tests defaults
+  # These are the second-round smoke tests. These make sure that the binaries are
+  # correct from a user perspective, testing that they exist from the cloud are
+  # are runnable. Note that the pytorch repo is never cloned into these jobs
+  ##############################################################################
+  smoke_linux_test:
+    <<: *binary_linux_test_upload_params
+    machine:
+      image: ubuntu-1604:202007-01
+    steps:
+    - checkout
+    - calculate_docker_image_tag
+    - setup_linux_system_environment
+    - setup_ci_environment
+    - run:
+        <<: *binary_checkout
+    - run:
+        <<: *binary_populate_env
+    - run:
+        name: Test
+        no_output_timeout: "1h"
+        command: |
+          set -ex
+          cat >/home/circleci/project/ci_test_script.sh \<<EOL
+          # The following code will be executed inside Docker container
+          set -eux -o pipefail
+          /builder/smoke_test.sh
+          # The above code will be executed inside Docker container
+          EOL
+    - run:
+        <<: *binary_run_in_docker
+
+  smoke_mac_test:
+    <<: *binary_linux_test_upload_params
+    macos:
+      xcode: "11.2.1"
+    steps:
+      - checkout
+      - run:
+          <<: *binary_checkout
+      - run:
+          <<: *binary_populate_env
+      - brew_update
+      - run:
+          <<: *binary_install_miniconda
+      - run:
+          name: Build
+          no_output_timeout: "1h"
+          command: |
+            set -ex
+            source "/Users/distiller/project/env"
+            export "PATH=$workdir/miniconda/bin:$PATH"
+            # TODO unbuffer and ts this, but it breaks cause miniconda overwrites
+            # tclsh. But unbuffer and ts aren't that important so they're just
+            # disabled for now
+            ./builder/smoke_test.sh
+
+  binary_mac_build:
+    <<: *binary_mac_params
+    macos:
+      xcode: "11.2.1"
+    steps:
+    # See Note [Workspace for CircleCI scripts] in job-specs-setup.yml
+    - checkout
+    - run:
+        <<: *binary_checkout
+    - run:
+        <<: *binary_populate_env
+    - brew_update
+    - run:
+        <<: *binary_install_miniconda
+
+    - run:
+        name: Build
+        no_output_timeout: "1h"
+        command: |
+          # Do not set -u here; there is some problem with CircleCI
+          # variable expansion with PROMPT_COMMAND
+          set -ex -o pipefail
+          script="/Users/distiller/project/pytorch/.circleci/scripts/binary_macos_build.sh"
+          cat "$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 "$script"
+
+    - persist_to_workspace:
+        root: /Users/distiller/project
+        paths: final_pkgs
+
   binary_ios_build:
     <<: *pytorch_ios_params
     macos:
-      xcode: "12.5.1"
+      xcode: "12.0"
     steps:
     - attach_workspace:
         at: ~/workspace
@@ -29,7 +228,7 @@ jobs:
   binary_ios_upload:
     <<: *pytorch_ios_params
     macos:
-      xcode: "12.5.1"
+      xcode: "12.0"
     steps:
     - attach_workspace:
         at: ~/workspace
@@ -43,6 +242,88 @@ jobs:
           cat "$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
+
+  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:
@@ -71,3 +352,4 @@ jobs:
           command: |
               ANACONDA_API_TOKEN="${CONDA_PYTORCHBOT_TOKEN}" \
               scripts/release/anaconda-prune/run.sh
+

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

@@ -8,7 +8,7 @@
   # then install the one with the most recent version.
   update_s3_htmls: &update_s3_htmls
     machine:
-      image: ubuntu-2004:202104-01
+      image: ubuntu-1604:202007-01
     resource_class: medium
     steps:
     - checkout

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

@@ -4,7 +4,7 @@
           type: string
           default: ""
       machine:
-        image: ubuntu-2004:202104-01
+        image: ubuntu-1604:202007-01
       resource_class: large
       environment:
         IMAGE_NAME: << parameters.image_name >>
@@ -20,10 +20,7 @@
               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
+              eval $(aws ecr get-login --no-include-email --region us-east-1)
               set -x
               # Check if image already exists, if it does then skip building it
               if docker manifest inspect "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/${IMAGE_NAME}:${DOCKER_TAG}"; then
@@ -54,3 +51,58 @@
               export AWS_SECRET_ACCESS_KEY=${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-1604:202007-01
+      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}
+              eval $(aws ecr get-login --no-include-email --region us-east-1)
+              set -x
+              docker push 308535385114.dkr.ecr.us-east-1.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

@@ -1,11 +1,11 @@
   pytorch_doc_push:
     resource_class: medium
     machine:
-      image: ubuntu-2004:202104-01
+      image: ubuntu-1604:202007-01
     parameters:
       branch:
         type: string
-        default: "main"
+        default: "master"
     steps:
     - attach_workspace:
         at: /tmp/workspace
@@ -24,48 +24,98 @@
           pushd /tmp/workspace
           git push -u origin "<< parameters.branch >>"
 
-  pytorch_macos_10_15_py3_build:
+  pytorch_python_doc_build:
     environment:
-      BUILD_ENVIRONMENT: pytorch-macos-10.15-py3-arm64-build
-    macos:
-      xcode: "12.3.0"
+      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-1604:202007-01
     steps:
-      - checkout
-      - run_brew_for_macos_build
-      - run:
-          name: Build
-          no_output_timeout: "1h"
-          command: |
-            set -e
-            export CROSS_COMPILE_ARM64=1
-            export JOB_BASE_NAME=$CIRCLE_JOB
+    - checkout
+    - calculate_docker_image_tag
+    - setup_linux_system_environment
+    - setup_ci_environment
+    - run:
+        name: Doc Build and Push
+        no_output_timeout: "1h"
+        command: |
+          set -ex
+          export COMMIT_DOCKER_IMAGE=${DOCKER_IMAGE}:${DOCKER_TAG}-${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})
 
-            # Install sccache
-            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
-            export SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2
+          export COMMAND='((echo "sudo chown -R jenkins workspace && cd workspace && . ./.circleci/scripts/python_doc_push_script.sh docs/'$target' '$target' site") | docker exec -u jenkins -i "$id" bash) 2>&1'
 
-            # This IAM user allows write access to S3 bucket for sccache
-            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
+          echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
 
-            chmod a+x .jenkins/pytorch/macos-build.sh
-            unbuffer .jenkins/pytorch/macos-build.sh 2>&1 | 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
 
-      - persist_to_workspace:
-          root: /Users/distiller/workspace/
-          paths:
-            - miniconda3
-      - store_artifacts:
-          path: /Users/distiller/project/dist
+          # 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 ${DEBUG_COMMIT_DOCKER_IMAGE}
+    - persist_to_workspace:
+        root: /tmp/workspace
+        paths:
+          - .
+    - store_artifacts:
+        path: ~/workspace/build_artifacts/master
+        destination: docs
+
+  pytorch_cpp_doc_build:
+    environment:
+      BUILD_ENVIRONMENT: pytorch-cpp-doc-push
+      DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-py3.6-gcc5.4"
+    resource_class: large
+    machine:
+      image: ubuntu-1604:202007-01
+    steps:
+    - checkout
+    - calculate_docker_image_tag
+    - setup_linux_system_environment
+    - setup_ci_environment
+    - run:
+        name: Doc Build and Push
+        no_output_timeout: "1h"
+        command: |
+          set -ex
+          export COMMIT_DOCKER_IMAGE=${DOCKER_IMAGE}:${DOCKER_TAG}-${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 ${COMMIT_DOCKER_IMAGE})
+
+          export COMMAND='((echo "sudo chown -R jenkins workspace && cd workspace && . ./.circleci/scripts/cpp_doc_push_script.sh docs/"$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_13_py3_build:
     environment:
       BUILD_ENVIRONMENT: pytorch-macos-10.13-py3-build
     macos:
-      xcode: "12.0"
+      xcode: "11.2.1"
     steps:
       - checkout
       - run_brew_for_macos_build
@@ -74,10 +124,10 @@
           no_output_timeout: "1h"
           command: |
             set -e
-            export JOB_BASE_NAME=$CIRCLE_JOB
+            export IN_CIRCLECI=1
 
             # Install sccache
-            sudo curl --retry 3 https://s3.amazonaws.com/ossci-macos/sccache_v2.15 --output /usr/local/bin/sccache
+            sudo curl --retry 3 https://s3.amazonaws.com/ossci-macos/sccache --output /usr/local/bin/sccache
             sudo chmod +x /usr/local/bin/sccache
             export SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2
 
@@ -95,203 +145,11 @@
           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
     macos:
-      xcode: "12.0"
+      xcode: "11.2.1"
     steps:
       - checkout
       - attach_workspace:
@@ -302,47 +160,10 @@
           no_output_timeout: "1h"
           command: |
             set -e
-            export JOB_BASE_NAME=$CIRCLE_JOB
+            export IN_CIRCLECI=1
 
             chmod a+x .jenkins/pytorch/macos-test.sh
             unbuffer .jenkins/pytorch/macos-test.sh 2>&1 | ts
-      - run:
-          name: Report results
-          no_output_timeout: "5m"
-          command: |
-            set -ex
-            source /Users/distiller/workspace/miniconda3/bin/activate
-            python3 -m pip install boto3==1.19.12
-
-            export JOB_BASE_NAME=$CIRCLE_JOB
-
-            # Using the same IAM user to write stats to our OSS bucket
-            export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_SCCACHE_S3_BUCKET_V4}
-            export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_SCCACHE_S3_BUCKET_V4}
-            python -m tools.stats.print_test_stats --upload-to-s3 --compare-with-s3 test
-          when: always
-      - store_test_results:
-          path: test/test-reports
-
-  pytorch_macos_10_13_py3_lite_interpreter_build_test:
-    environment:
-      BUILD_ENVIRONMENT: pytorch-macos-10.13-py3-test
-    macos:
-      xcode: "12.0"
-    steps:
-      - checkout
-      - attach_workspace:
-          at: ~/workspace
-      - run_brew_for_macos_build
-      - run:
-          name: Test
-          no_output_timeout: "1h"
-          command: |
-            set -e
-            export BUILD_LITE_INTERPRETER=1
-            export JOB_BASE_NAME=$CIRCLE_JOB
-            chmod a+x ${HOME}/project/.jenkins/pytorch/macos-lite-interpreter-build-test.sh
-            unbuffer ${HOME}/project/.jenkins/pytorch/macos-lite-interpreter-build-test.sh 2>&1 | ts
       - store_test_results:
           path: test/test-reports
 
@@ -350,10 +171,10 @@
     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
+      image: ubuntu-1604:202007-01
     steps:
     - checkout
     - calculate_docker_image_tag
@@ -364,7 +185,7 @@
         no_output_timeout: "1h"
         command: |
           set -eux
-          docker_image_commit=${DOCKER_IMAGE}:build-${DOCKER_TAG}-${CIRCLE_SHA1}
+          docker_image_commit=${DOCKER_IMAGE}:${DOCKER_TAG}-${CIRCLE_SHA1}
 
           docker_image_libtorch_android_x86_32=${docker_image_commit}-android-x86_32
           docker_image_libtorch_android_x86_64=${docker_image_commit}-android-x86_64
@@ -428,6 +249,9 @@
           output_image=$docker_image_libtorch_android_x86_32-gradle
           docker commit "$id_x86_32" ${output_image}
           time docker push ${output_image}
+    - upload_binary_size_for_android_build:
+        build_type: prebuilt
+        artifacts: /home/circleci/workspace/build_android_artifacts/artifacts.tgz
     - store_artifacts:
         path: ~/workspace/build_android_artifacts/artifacts.tgz
         destination: artifacts.tgz
@@ -435,22 +259,22 @@
   pytorch_android_publish_snapshot:
     environment:
       BUILD_ENVIRONMENT: pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-publish-snapshot
-      DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c"
-      PYTHON_VERSION: "3.7"
+      DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c:ab1632df-fa59-40e6-8c23-98e004f61148"
+      PYTHON_VERSION: "3.6"
     resource_class: large
     machine:
-      image: ubuntu-2004:202104-01
+      image: ubuntu-1604:202007-01
     steps:
     - checkout
-    - calculate_docker_image_tag
     - setup_linux_system_environment
+    - checkout
     - setup_ci_environment
     - run:
         name: pytorch android gradle build
         no_output_timeout: "1h"
         command: |
           set -eux
-          docker_image_commit=${DOCKER_IMAGE}:build-${DOCKER_TAG}-${CIRCLE_SHA1}
+          docker_image_commit=${DOCKER_IMAGE}-${CIRCLE_SHA1}
 
           docker_image_libtorch_android_x86_32_gradle=${docker_image_commit}-android-x86_32-gradle
 
@@ -472,10 +296,10 @@
     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
+      image: ubuntu-1604:202007-01
     steps:
     - checkout
     - calculate_docker_image_tag
@@ -487,7 +311,7 @@
         no_output_timeout: "1h"
         command: |
           set -e
-          docker_image_libtorch_android_x86_32=${DOCKER_IMAGE}:build-${DOCKER_TAG}-${CIRCLE_SHA1}-android-x86_32
+          docker_image_libtorch_android_x86_32=${DOCKER_IMAGE}:${DOCKER_TAG}-${CIRCLE_SHA1}-android-x86_32
           echo "docker_image_libtorch_android_x86_32: "${docker_image_libtorch_android_x86_32}
 
           # x86
@@ -503,52 +327,62 @@
           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:
+    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"
+    resource_class: large
+    machine:
+      image: ubuntu-1604:202007-01
+    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
+          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 "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"
+      xcode: "12.0"
     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 +390,25 @@
             cd ${PROJ_ROOT}/ios/TestApp
             # install fastlane
             sudo gem install bundler && bundle install
+            # install certificates
+            echo ${IOS_CERT_KEY} >> cert.txt
+            base64 --decode cert.txt -o Certificates.p12
+            rm cert.txt
+            bundle exec fastlane install_cert
+            # install the provisioning profile
+            PROFILE=PyTorch_CI_2021.mobileprovision
+            PROVISIONING_PROFILES=~/Library/MobileDevice/Provisioning\ Profiles
+            mkdir -pv "${PROVISIONING_PROFILES}"
+            cd "${PROVISIONING_PROFILES}"
+            echo ${IOS_SIGN_KEY} >> cert.txt
+            base64 --decode cert.txt -o ${PROFILE}
+            rm cert.txt
       - run:
           name: Build
           no_output_timeout: "1h"
           command: |
             set -e
+            export IN_CIRCLECI=1
             WORKSPACE=/Users/distiller/workspace
             PROJ_ROOT=/Users/distiller/project
             export TCLLIBPATH="/usr/local/lib"
@@ -577,12 +425,12 @@
                 $*  || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
             }
 
-            retry conda install numpy ninja pyyaml mkl mkl-include setuptools cmake cffi requests typing_extensions --yes
+            retry conda install numpy ninja pyyaml mkl mkl-include setuptools cmake cffi typing requests --yes
 
             # sync submodules
             cd ${PROJ_ROOT}
             git submodule sync
-            git submodule update --init --recursive --depth 1 --jobs 0
+            git submodule update --init --recursive
 
             # export
             export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
@@ -591,9 +439,6 @@
             chmod a+x ${PROJ_ROOT}/scripts/build_ios.sh
             echo "IOS_ARCH: ${IOS_ARCH}"
             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: ${SELECTED_OP_LIST}"
@@ -602,10 +447,6 @@
             fi
             export IOS_ARCH=${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
             unbuffer ${PROJ_ROOT}/scripts/build_ios.sh 2>&1 | ts
       - run:
           name: Run Build Test
@@ -613,12 +454,18 @@
           command: |
             set -e
             PROJ_ROOT=/Users/distiller/project
+            PROFILE=PyTorch_CI_2021
             # run the ruby build script
             if ! [ -x "$(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
@@ -635,41 +482,18 @@
             WORKSPACE=/Users/distiller/workspace
             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
-            # generate models for differnet backends
+            pip install torch torchvision --progress-bar off
+            #run unit test
             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"
-            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
-            else
-              fastlane scan --only_testing TestAppTests/TestAppTests/testFullJIT
-            fi
+            python trace_model.py
+            ruby setup.rb
+            cd ${PROJ_ROOT}/ios/TestApp
+            instruments -s -devices
+            fastlane scan
   pytorch_linux_bazel_build:
     <<: *pytorch_params
     machine:
-      image: ubuntu-2004:202104-01
+      image: ubuntu-1604:202007-01
     steps:
     - checkout
     - calculate_docker_image_tag
@@ -685,9 +509,9 @@
           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
+          git submodule sync && git submodule update -q --init --recursive
 
           docker cp /home/circleci/project/. $id:/var/lib/jenkins/workspace
 
@@ -698,7 +522,7 @@
           # Push intermediate Docker image for next phase to use
           if [ -z "${BUILD_ONLY}" ]; then
             # Augment our output image name with bazel to avoid collisions
-            output_image=${DOCKER_IMAGE}:build-${DOCKER_TAG}-bazel-${CIRCLE_SHA1}
+            output_image=${DOCKER_IMAGE}:${DOCKER_TAG}-bazel-${CIRCLE_SHA1}
             export COMMIT_DOCKER_IMAGE=$output_image
             docker commit "$id" ${COMMIT_DOCKER_IMAGE}
             time docker push ${COMMIT_DOCKER_IMAGE}
@@ -707,7 +531,7 @@
   pytorch_linux_bazel_test:
     <<: *pytorch_params
     machine:
-      image: ubuntu-2004:202104-01
+      image: ubuntu-1604:202007-01
     steps:
     - checkout
     - calculate_docker_image_tag
@@ -718,7 +542,7 @@
         no_output_timeout: "90m"
         command: |
           set -e
-          output_image=${DOCKER_IMAGE}:build-${DOCKER_TAG}-bazel-${CIRCLE_SHA1}
+          output_image=${DOCKER_IMAGE}:${DOCKER_TAG}-bazel-${CIRCLE_SHA1}
           export COMMIT_DOCKER_IMAGE=$output_image
           echo "DOCKER_IMAGE: "${COMMIT_DOCKER_IMAGE}
 
@@ -748,15 +572,26 @@
     - store_test_results:
         path: bazel-testlogs
 
-  pytorch_windows_test_multigpu:
+  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
+      image: ubuntu-1604:202007-01
     steps:
-      - checkout
-      - run:
-          name: Test
-          no_output_timeout: "90m"
-          command: |
-            set -e
-            python3 -m pip install requests
-            python3 ./.circleci/scripts/trigger_azure_pipeline.py
+    - 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=${DOCKER_IMAGE}:${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 +1,356 @@
+jobs:
+  pytorch_linux_build:
+    <<: *pytorch_params
+    machine:
+      image: ubuntu-1604:202007-01
+    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
+          # TODO: Remove this after we figure out why rocm tests are failing
+          if [[ "${DOCKER_IMAGE}" == *rocm3.5* ]]; then
+            export DOCKER_TAG="ab1632df-fa59-40e6-8c23-98e004f61148"
+          fi
+          if [[ "${DOCKER_IMAGE}" == *rocm3.7* ]]; then
+            export DOCKER_TAG="1045c7b891104cb4fd23399eab413b6213e48aeb"
+          fi
+          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
+
+          docker cp /home/circleci/project/. $id:/var/lib/jenkins/workspace
+
+          export COMMAND='((echo "sudo chown -R jenkins workspace && 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-trusty-py3.6-gcc5.4-build. In the push step, we have to
+            # distinguish between them so the test can pick up the correct image.
+            output_image=${DOCKER_IMAGE}:${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 ${COMMIT_DOCKER_IMAGE}
+          fi
+    - store_artifacts:
+        path: /home/circleci/project/dist
+
+  pytorch_linux_test:
+    <<: *pytorch_params
+    machine:
+      image: ubuntu-1604:202007-01
+    steps:
+    # See Note [Workspace for CircleCI scripts] in job-specs-setup.yml
+    - checkout
+    - calculate_docker_image_tag
+    - setup_linux_system_environment
+    - setup_ci_environment
+    - run:
+        name: Download Docker image
+        no_output_timeout: "90m"
+        command: |
+          set -e
+          export PYTHONUNBUFFERED=1
+          # TODO: Remove this after we figure out why rocm tests are failing
+          if [[ "${DOCKER_IMAGE}" == *rocm3.5* ]]; then
+            export DOCKER_TAG="ab1632df-fa59-40e6-8c23-98e004f61148"
+          fi
+          if [[ "${DOCKER_IMAGE}" == *rocm3.7* ]]; then
+            export DOCKER_TAG="1045c7b891104cb4fd23399eab413b6213e48aeb"
+          fi
+          # See Note [Special build images]
+          output_image=${DOCKER_IMAGE}:${DOCKER_TAG}-${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 -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 [ "${BUILD_ENVIRONMENT}" == "pytorch-linux-xenial-py3.6-gcc5.4-test" ]; then
+              return 0
+            fi
+            return 1
+          }
+
+          if is_vanilla_build; then
+            echo "apt-get update && apt-get install -y qemu-user gdb" | docker exec -u root -i "$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 ${BUILD_ENVIRONMENT}"
+          fi
+    - run:
+        name: Run tests
+        no_output_timeout: "90m"
+        command: |
+          set -e
+
+          cat >docker_commands.sh \<<EOL
+          # =================== The following code will be executed inside Docker container ===================
+          set -ex
+          export SCRIBE_GRAPHQL_ACCESS_TOKEN="${SCRIBE_GRAPHQL_ACCESS_TOKEN}"
+          ${PARALLEL_FLAGS}
+          cd workspace
+          EOL
+          if [[ ${BUILD_ENVIRONMENT} == *"multigpu"* ]]; then
+            echo ".jenkins/pytorch/multigpu-test.sh" >> docker_commands.sh
+          elif [[ ${BUILD_ENVIRONMENT} == *onnx* ]]; then
+            echo "pip install click mock tabulate networkx==2.0" >> docker_commands.sh
+            echo "pip -q install --user -b /tmp/pip_install_onnx \"file:///var/lib/jenkins/workspace/third_party/onnx#egg=onnx\"" >> docker_commands.sh
+            echo ".jenkins/caffe2/test.sh" >> docker_commands.sh
+          else
+            echo ".jenkins/pytorch/test.sh" >> docker_commands.sh
+          fi
+          echo "(cat docker_commands.sh | docker exec -u jenkins -i "$id" bash) 2>&1" > command.sh
+          unbuffer bash command.sh | ts
+    - run:
+        name: Report results
+        no_output_timeout: "5m"
+        command: |
+          set -e
+          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 CIRCLE_JOB="$CIRCLE_JOB"
+          cd workspace
+          python test/print_test_stats.py test
+          EOL
+          echo "(cat docker_commands.sh | docker exec -u jenkins -i "$id" bash) 2>&1" > command.sh
+          unbuffer bash command.sh | ts
+
+          echo "Retrieving test reports"
+          docker cp $id:/var/lib/jenkins/workspace/test/test-reports ./ || echo 'No test reports found!'
+          if [[ ${BUILD_ENVIRONMENT} == *"coverage"* ]]; then
+              echo "Retrieving coverage report"
+              docker cp $id:/var/lib/jenkins/workspace/test/.coverage ./test
+              docker cp $id:/var/lib/jenkins/workspace/test/coverage.xml ./test
+              python3 -mpip install codecov
+              python3 -mcodecov
+          fi
+        when: always
+    - store_test_results:
+        path: test-reports
+
+  pytorch_windows_build:
+    <<: *pytorch_windows_params
+    parameters:
+      executor:
+        type: string
+        default: "windows-xlarge-cpu-with-nvidia-cuda"
+      build_environment:
+        type: string
+        default: ""
+      test_name:
+        type: string
+        default: ""
+      cuda_version:
+        type: string
+        default: "10"
+      python_version:
+        type: string
+        default: "3.6"
+      vc_version:
+        type: string
+        default: "14.16"
+      vc_year:
+        type: string
+        default: "2019"
+      vc_product:
+        type: string
+        default: "BuildTools"
+      use_cuda:
+        type: string
+        default: ""
+    executor: <<parameters.executor>>
+    steps:
+      - checkout
+      - run:
+          name: Install Cuda
+          no_output_timeout: 30m
+          command: |
+            if [[ "${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=${CIRCLECI_AWS_SECRET_KEY_FOR_WIN_BUILD_V1}
+            set -x
+            .jenkins/pytorch/win-build.sh
+      - persist_to_workspace:
+          root: "C:/w"
+          paths: build-results
+      - store_artifacts:
+          path: C:/w/build-results
+
+  pytorch_windows_test:
+    <<: *pytorch_windows_params
+    parameters:
+      executor:
+        type: string
+        default: "windows-medium-cpu-with-nvidia-cuda"
+      build_environment:
+        type: string
+        default: ""
+      test_name:
+        type: string
+        default: ""
+      cuda_version:
+        type: string
+        default: "10"
+      python_version:
+        type: string
+        default: "3.6"
+      vc_version:
+        type: string
+        default: "14.16"
+      vc_year:
+        type: string
+        default: "2019"
+      vc_product:
+        type: string
+        default: "BuildTools"
+      use_cuda:
+        type: string
+        default: ""
+    executor: <<parameters.executor>>
+    steps:
+      - checkout
+      - attach_workspace:
+          at: c:/users/circleci/workspace
+      - run:
+          name: Install Cuda
+          no_output_timeout: 30m
+          command: |
+            if [[ "${CUDA_VERSION}" != "cpu" ]]; then
+              if [[ "${CUDA_VERSION}" != "10" || "${JOB_EXECUTOR}" != "windows-with-nvidia-gpu" ]]; then
+                .circleci/scripts/windows_cuda_install.sh
+              fi
+              if [[ "${CUDA_VERSION}" != "10" && "${JOB_EXECUTOR}" == "windows-with-nvidia-gpu" ]]; then
+                .circleci/scripts/driver_update.bat
+              fi
+            fi
+      - run:
+          name: Install Cudnn
+          command : |
+            if [[ "${CUDA_VERSION}" != "cpu" ]]; then
+              .circleci/scripts/windows_cudnn_install.sh
+            fi
+      - run:
+          name: Test
+          no_output_timeout: "30m"
+          command: |
+            set -e
+            export IN_CIRCLECI=1
+            set +x
+            export AWS_ACCESS_KEY_ID=${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
+      - store_test_results:
+          path: test/test-reports

.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