Squash docker images (#7501)

Our previous image setup was trying to keep things separate in a defined
hierarchy and use multi-stage builds. This was for a few reasons:
1. It followed Docker's recommended
   [best practices](https://docs.docker.com/develop/develop-images/dockerfile_best-practices/).
2. It ensured that builds only had exactly the things we thought they
   needed and didn't grow any weird extra dependencies.
3. It separated concerns, so each image was doing a single specific
   thing.
4. It avoided monolithic architectures.
5. It aimed to keep images as small as possible for each transmission
   over the wire.

These were all great in theory. In practice, it meant we had 20 docker
images and it was confusing to keep track of them all. The major failing
here is that Dockerfile is just really not a composable format. The only
mechanism of composability is fetching specific files from another
image, which requires enumerating all such files: not easy for installs
that scatter files across the filesystem. This meant that we ended up
repeating ourselves anyway and duplicated expensive work. Dockerfile
commands that create layers in the image also don't have explicit
dependencies. If any layer underneath it is changed, the whole cache is
invalidated. This means rebuilds are far more frequent than you'd want
for this sort of architecture. Additionally, we've ended up at a place
where things like Python and its basic modules like numpy and yaml are
needed in pretty much every build, so trying to separate them out is
much less useful.

So instead, this PR squashes things down to 12 images: a base image that
has what we need for basic builds and all the non-conflicting
dependencies and child images that add specific conflicting toolchain
things. This makes all of the images that remain bigger because they
have stuff they absolutely don't need. In particular, the frontends
image now inherits from the android image, which I need for
https://github.com/google/iree/pull/7494. I don't really understand why
the Android NDK has to be so massive (over 4GB). Here's a
[comparison](https://gist.github.com/GMNGeoffrey/949ebb31748421c1922d1c874add46c5)
of the old and new images and their sizes. Note that some images weren't
shipped anywhere and were purely for intermediate images. The only such
remaining image is "frontends" which is specialized into swiftshader and
nvidia flavors.

Tested: Triggered all the non-default builds. I was going to do a
oneshot of the gradle build, but it looks like that workflow has
never been run?

![Build TFLite Android Library screenshot](https://user-images.githubusercontent.com/5732088/139757332-05d7f11c-eb8d-4cea-9183-d77c976859ab.png)
40 files changed
tree: e8035505722a8b637b4c37196fdb642c6196248d
  1. .github/
  2. benchmarks/
  3. bindings/
  4. build_tools/
  5. colab/
  6. docs/
  7. experimental/
  8. integrations/
  9. iree/
  10. llvm-external-projects/
  11. scripts/
  12. third_party/
  13. .bazelignore
  14. .bazelrc
  15. .bazelversion
  16. .clang-format
  17. .gitignore
  18. .gitmodules
  19. .style.yapf
  20. .yamllint.yml
  21. AUTHORS
  22. BUILD.bazel
  23. CMakeLists.txt
  24. configure_bazel.py
  25. CONTRIBUTING.md
  26. LICENSE
  27. README.md
  28. SUBMODULE_VERSIONS.txt
  29. WORKSPACE
README.md

IREE: Intermediate Representation Execution Environment

IREE (Intermediate Representation Execution Environment, pronounced as “eerie”) is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the datacenter and down to satisfy the constraints and special considerations of mobile and edge deployments.

See our website for project details, user guides, and instructions on building from source.

Project Status

IREE is still in its early phase. We have settled down on the overarching infrastructure and are actively improving various software components as well as project logistics. It is still quite far from ready for everyday use and is made available without any support at the moment. With that said, we welcome any kind of feedback on any communication channels!

Communication Channels

Related Project Channels

  • MLIR topic within LLVM Discourse: IREE is enabled by and heavily relies on MLIR. IREE sometimes is referred to in certain MLIR discussions. Useful if you are also interested in MLIR evolution.

Build Status

CI SystemBuild SystemPlatformArchitectureConfiguration / ComponentStatus
KokoroBazelLinuxx86-64kokoro status bazel/linux/x86-swiftshader/core
KokoroCMake & BazelLinuxx86-64 (swiftshader)Integrationskokoro status cmake-bazel/linux/x86-swiftshader
KokoroCMake & BazelLinuxx86-64 (turing)Integrationskokoro status cmake-bazel/linux/x86-turing
KokoroCMakeLinuxx86-64 (swiftshader)kokoro status cmake/linux/x86-swiftshader
KokoroCMakeLinuxx86-64 (swiftshader)asankokoro status cmake/linux/x86-swiftshader-asan
KokoroCMakeLinuxx86-64 (turing)kokoro status cmake/linux/x86-turing
KokoroCMakeAndroidarm64-v8aRuntime (build only)kokoro status cmake/android/arm64-v8a
KokoroCMakeBare Metalrisc-v-32Runtimekokoro status cmake/baremetal/riscv32
KokoroCMakeLinuxrisc-v-64Runtimekokoro status cmake/linux/riscv64
BuildkiteCMakeAndroidarm64-v8aRuntimebuildkite status iree-android-arm64-v8a
BuildKiteCMakeAndroidarm64-v8aRuntime Benchmarksbuildkite status iree-benchmark
BuildKiteCMakeLinuxx86-64Tracing + Standalone Runtimebuildkite status iree-build-configurations

Architecture Overview

IREE Architecture

See our website for more information.

Presentations and Talks

  • 2021-06-09: IREE Runtime Design Tech Talk (recording and slides)
  • 2020-08-20: IREE CodeGen: MLIR Open Design Meeting Presentation (recording and slides)
  • 2020-03-18: Interactive HAL IR Walkthrough (recording)
  • 2020-01-31: End-to-end MLIR Workflow in IREE: MLIR Open Design Meeting Presentation (recording and slides)

License

IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.