# 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

	                       \
	ANDQ rBe, rBa;         \
	XORQ rBu, rBa;         \
	MOVQ rBa, _ku(oState); \
	K_RBA_RCU;             \
	                       \
	/* Result m */         \
	MOVQ _ga(iState), rBe; \
	XORQ rDa, rBe;         \
	MOVQ _ke(iState), rBi; \
	ROLQ $36, rBe;         \
	XORQ rDe, rBi;         \
	MOVQ _bu(iState), rBa; \
	ROLQ $10, rBi;         \
	MOVQ rBe, rT1;         \

#      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:

#     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_win_clang:  Options specific to compiling using Clang.
#
#     rbe_linux_cpu:                  RBE options to build with only CPU support.

# 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 -euxo 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" line, then print the last word in it,
  # and don't print duplicates

#    To use:
#       export TFCI=ci/official/envs/env_goes_here
#       export TF_ANY_SCRIPT=ci/official/wheel.sh
#       ./any.sh
#
# 3. DO THE SAME WITH A LOCAL CACHE OR RBE:
#       export TF_ANY_EXTRA_ENV=ci/official/envs/public_cache,ci/official/envs/disk_cache
#       ...
#       ./any.sh
#     or
#       export TF_ANY_EXTRA_ENV=ci/official/envs/local_rbe
#       ./any.sh
#       ...

  # VMs.
  export CLOUDSDK_PYTHON=$(which python3.11)
  gcloud auth activate-service-account --key-file="${GOOGLE_APPLICATION_CREDENTIALS}"
fi
set -x

# When cross-compiling with RBE, we need to copy the macOS sysroot to be
# inside the TensorFlow root directory. We then define them as a filegroup
# target inside "tensorflow/tools/toolchains/cross_compile/cc" so that Bazel

    if not result_store_line_match:
      continue

    url = result_store_line_match.group(1)
    url_lines = result_store_links.setdefault(url, {})
    # Each bazel RBE invocation should produce two
    # 'Streaming build results to: ...' lines, one at the start, and one at the
    # end of the invocation.
    # If there's a failure message, it will be found in-between these two.