# Enables RBE as long as RBE is available for the selected platform.
# The "selected" platform is considered to be
# TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX. "Available" means there is
# an entry in tensorflow/.bazelrc for build:rbe_TFCI_BAZEL_TARGET...
#                                           ^^^^
# This env is only valid when RBE is available on the selected platform, since

# This Workflow updates tensorflow/tools/toolchains/remote_config/configs.bzl
# to reference the most recent versions of the SIG Build Docker images.
name: Update RBE Configs
on:
  workflow_dispatch:

permissions:
  contents: read

jobs:
  rbe:
    name: Update RBE Configs
    runs-on: ubuntu-latest
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    steps:
    - name: Checkout code

#      Ex. 1: TFCI=py311,linux_x86_cuda,nightly_upload  (nightly job)
#      Ex. 2: TFCI=py39,linux_x86,rbe                   (continuous job)
#   Non-Googlers should replace "nightly_upload" or "rbe" with
#   "public_cache,disk_cache".
#   Googlers should replace "nightly_upload" with "public_cache,disk_cache" or
#   "rbe", if you have set up your system to use RBE (see further below).
#
# Here is how to choose your TFCI value:

TFCI_BAZEL_BAZELRC_ARGS="--output_user_root=C:/x"
TFCI_BAZEL_COMMON_ARGS="--repo_env=HERMETIC_PYTHON_VERSION=$TFCI_PYTHON_VERSION --repo_env=USE_PYWRAP_RULES=True --config=windows_x86_cpu_2022"

# For RBE, we explicitly set invalid paths to force the auto-configuration to fail.
TFCI_BAZEL_VC="C:/RBE_ISOLATED_INVALID_PATH"
TFCI_BAZEL_LLVM="C:/RBE_ISOLATED_INVALID_PATH"
TFCI_BAZEL_SH="C:/tools/msys64/usr/bin/bash.exe"

  #    tfci: 'py313,linux_x86,rbe'

  #build-and-test-linux-x86-cuda:
  #  uses: ./.github/workflows/build-reusable.yml
  #  with:
  #    runner: 'linux-x86-n4-32'
  #    tfci: 'py313,linux_x86_cuda'

  #build-and-test-arm64:
  #  uses: ./.github/workflows/build-reusable.yml
  #  with:
  #    runner: 'linux-arm64-c4a-16'
  #    tfci: 'py313,linux_arm64,rbe'

  build-and-test-windows-x86:

#     rbe_base:                       General RBE options shared by all flavors.
#     rbe_linux:                      General RBE options used on all linux builds.
#     rbe_win_base:                   General RBE options used on all Windows builds. Not to be used standalone.
#     rbe_windows_x86_cpu_2022:       Windows-specific RBE options.
#
#     rbe_linux_cpu:                  RBE options to build with only CPU support.

TFCI_BAZEL_BAZELRC_ARGS="--output_user_root=C:/x"
TFCI_BAZEL_COMMON_ARGS="--repo_env=HERMETIC_PYTHON_VERSION=$TFCI_PYTHON_VERSION --repo_env=USE_PYWRAP_RULES=True --config=windows_x86_cpu_2022"

# For RBE, we explicitly set invalid paths to force the auto-configuration to fail.
TFCI_BAZEL_VC="C:/RBE_ISOLATED_INVALID_PATH"
TFCI_BAZEL_LLVM="C:/RBE_ISOLATED_INVALID_PATH"
TFCI_BAZEL_SH="C:/tools/msys64/usr/bin/bash.exe"

# limitations under the License.
# ==============================================================================
# Release jobs are very basic. They don't use any caching or RBE,
# but they do upload logs to resultstore.
# IMPORTANT: trailing slash is required on GCS URIs, as it tells gcloud to
# pretend the path is a directory.
TFCI_ARTIFACT_FINAL_GCS_ENABLE=1

set -exo pipefail

function resultstore_extract_fallback {
  # In case the main script fails somehow.
  cat <<EOF
IMPORTANT: For bazel invocations that uploaded to ResultStore (e.g. RBE), you
can view more detailed results that are probably easier to read than this log.
Try the links below:
EOF
  # Find any "Streaming build results to" lines,
  # de-duplicate,
  # and print the last word from each

# The RBE machine itself has older kernel mode driver, and it requires
# nvidia driver to be installed.
nvidia-driver-580-open
# TODO(b/445248346): The Docker image shouldn't have cuda-compat installed.
# However, hermetic CUDA forward-compatibility mode is still missing some
# libraries.