Files
pytorch/.circleci/docker
Jane Xu a90a3acbee Use JIT Plug-in for coverage to cover JIT'd functions and methods (#56310)
Summary:
This PR is step 2 (after https://github.com/pytorch/pytorch/issues/56708) to having JIT coverage--it actually uses the plug-in in CI!

Disclaimer: note that this will mark the entire JIT'd function/method as covered without seeking proof that the
compiled code has been executed. This means that even if the code chunk is merely compiled and not run, it will get
marked as covered.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/56310

Test Plan:
We should see coverage improvements in CI after. A file to look out for would be `torch/jit/quantized.py`, which should have more coverage after this PR, which it does!
d3283ccd8c/torch/jit/quantized.py vs https://codecov.io/gh/pytorch/pytorch/src/master/torch/jit/quantized.py

More generally, the whole jit folder got ~3% increase in coverage, I believe.

Reviewed By: walterddr

Differential Revision: D28000672

Pulled By: janeyx99

fbshipit-source-id: 6712979d63a5e1224a92ee9bd9679ec62cf1cbba
2021-04-26 09:19:32 -07:00
..
2021-04-12 09:20:57 -07:00

Docker images for Jenkins

This directory contains everything needed to build the Docker images that are used in our CI

The Dockerfiles located in subdirectories are parameterized to conditionally run build stages depending on build arguments passed to docker build. This lets us use only a few Dockerfiles for many images. The different configurations are identified by a freeform string that we call a build environment. This string is persisted in 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

# 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 'BREAKPAD=1 ./build.sh pytorch-linux-bionic-py3.8-gcc9 -t myimage:latest