| sort -u
}

# Verify that, given a build target and a license-list generator target, all of
# the dependencies of that target which include a license notice file are then
# included when generating that license. Necessary because the license targets
# in TensorFlow are manually enumerated rather than generated automatically.
do_external_licenses_check(){
  BUILD_TARGET="$1"
  LICENSES_TARGET="$2"

  export TFCI="$TFCI,$TF_ANY_EXTRA_ENV"
fi
if [[ -n "${TF_ANY_SCRIPT:-}" ]]; then
  "$TF_ANY_SCRIPT"
elif [[ -n "${TF_ANY_TARGETS:-}" ]]; then
  source "${BASH_SOURCE%/*}/utilities/setup.sh"
  tfrun bazel "${TF_ANY_MODE:-test}" $TFCI_BAZEL_COMMON_ARGS $TF_ANY_TARGETS
else
  echo 'Looks like $TF_ANY_TARGETS are $TF_ANY_SCRIPT are both empty. That is an error.'
  exit 1

    # Without this, git errors if /tf/tensorflow directory owner is different
    git config --global --add safe.directory /tf/tensorflow
    # Note that you could generate a list of all the affected targets with e.g.:
    # bazel query $(paste -sd "+" $BATS_FILE_TMPDIR/changed_files) --keep_going
    # Only shows Added, Changed, Modified, Renamed, and Type-changed files

#
#   export TFCI=...
#   export TF_BISECT_SCRIPT=ci/official/any.sh
#   export TF_BISECT_GOOD=a_good_commit_sha
#   export TF_BISECT_BAD=a_failing_commit_sha
#   export TF_ANY_TARGETS="quoted list of targets, like on the command line"
#   export TF_ANY_MODE=test
set -euxo pipefail
cd "$(dirname "$0")/../../"  # tensorflow/
export TFCI="$(echo $TFCI | sed 's/,nightly_upload/,public_cache,disk_cache/')"

  TF_RETURN_IF_ERROR(ops::Neg(ctx, inputs[0], &neg_output, "Neg"));
  tape.RecordOperation(inputs, {neg_output}, nullptr, "Neg");
  return tape.ComputeGradient(ctx,
                              /*targets=*/{neg_output},
                              /*sources=*/inputs,
                              /*output_gradients=*/{}, outputs);
}

TEST_P(CppGradients, TestRecordOperationWithNullGradientFunctionRaises) {

                       'matching the invocation, inside the log. '
                       'Please look for it in the build log.\n\n')
      failure_msg += (
          f'See the ResultStore link for a detailed view of failed targets:\n'
          f'{url}\n\n')
      failure_msg += (
          f'Here\'s a fragment of the log containing the failure:\n\n'
          f'[ ... TRUNCATED ... ]\n\n'
          f'{invocation_results["log_fragment"]}\n'

  for (int i = 0; i < noutputs; ++i) {
    output_names[i] = c_output_names[i];
  }
  std::vector<string> target_oper_names(ntargets);
  for (int i = 0; i < ntargets; ++i) {
    target_oper_names[i] = c_target_oper_names[i];
  }
  TF_Run_Helper(s->session, nullptr, run_options, input_pairs, output_names,
                c_outputs, target_oper_names, run_metadata, status);
}

void TF_PRunSetup(TF_DeprecatedSession* s,

# limitations under the License.
# ==============================================================================
TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_arm64_linux"
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_arm64
# Note: this is not set to "--cpu", because that changes the package name
# to tensorflow_cpu. These ARM builds are supposed to have the name "tensorflow"
# despite lacking Nvidia CUDA support.

source ci/official/envs/linux_arm64
TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config  cross_compile_linux_arm64"

# > TF's gen_api_init_files has a genrule to run the core TensorFlow code
# > on the host machine. If we don't have --distinct_host_configuration=false,
# > the core TensorFlow code will be built once for the host and once for the
# > target platform.
# See also https://docs.bazel.build/versions/master/guide.html#build-configurations-and-cross-compilation
build --distinct_host_configuration=false