compile_pip_requirements_3_9(
    name = "requirements_3_9",
    extra_args = ["--allow-unsafe"],
    requirements_in = REQUIREMENTS_FILE_NAME,
    requirements_txt = "requirements_lock_3_9.txt",
)

compile_pip_requirements_3_10(
    name = "requirements_3_10",
    extra_args = ["--allow-unsafe"],
    requirements_in = REQUIREMENTS_FILE_NAME,
    requirements_txt = "requirements_lock_3_10.txt",
)

setup_file() {
    bazel version  # Start the bazel server

    # Fixes "fatal: detected dubious ownership in repository" for Docker.
    git config --system --add safe.directory '*'
    git config --system protocol.file.allow always

    # 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

  TF_Operation* plusB = Add(plus2, b, graph, s, "plusB");
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Setup a session and a partial run handle.  The partial run will allow
  // computation of A + 2 + B in two phases (calls to TF_SessionPRun):
  // 1. Feed A and get (A+2)
  // 2. Feed B and get (A+2)+B
  TF_SessionOptions* opts = TF_NewSessionOptions();

// --------------------------------------------------------------------------
TF_SessionOptions* TF_NewSessionOptions() {
  TF_SessionOptions* out = new TF_SessionOptions;
  // Disable optimizations for static graph to allow calls to Session::Extend.
  out->options.config.mutable_experimental()
      ->set_disable_optimize_for_static_graph(true);
  return out;
}
void TF_DeleteSessionOptions(TF_SessionOptions* opt) { delete opt; }

export DOCKER_BUILDKIT=1
for target in jax tf; do
  IMAGE="gcr.io/tensorflow-sigs/build-arm64:$target-$TAG"
  docker pull "$IMAGE" || true
  # Due to some flakiness of resources pulled in the build, allow the docker
  # command to reattempt build a few times in the case of failure (b/302558736)
  set +e
  for i in $(seq 1 5)
  do
    docker build \
    --build-arg REQUIREMENTS_FILE=jax.requirements.txt \

//   are not optimizing for convenience.
// * We make assumption that one session has one graph.  This should be
//   fine since we have the ability to run sub-graphs.
// * We could allow NULL for some arguments (e.g., NULL options arg).
//   However since convenience is not a primary goal, we don't do this.
// * Devices are not in this API.  Instead, they are created/used internally

  } else {
    optimizer_options->set_global_jit_level(tensorflow::OptimizerOptions::OFF);
  }

  auto* gpu_options = config.mutable_gpu_options();
  gpu_options->set_allow_growth(gpu_memory_allow_growth);

  (*config.mutable_device_count())["CPU"] = num_cpu_devices;

  // TODO(b/113217601): This is needed for EagerContext::runner_ to use a

def write_action_env_to_bazelrc(var_name, var):
  write_to_bazelrc('build --action_env {}="{}"'.format(var_name, str(var)))


def run_shell(cmd, allow_non_zero=False, stderr=None):
  if stderr is None:
    stderr = sys.stdout
  if allow_non_zero:
    try:
      output = subprocess.check_output(cmd, stderr=stderr)
    except subprocess.CalledProcessError as e:
      output = e.output
  else:

//
// Gradient is the type returned by gradient functions. In Python TF it's either
// Tensor or IndexedSlices or None, which here we map to nullptr. Gradients need
// to allow their size to be computed and they need to be passable to a backward
// function and deleted (as the backprop code creates lots of gradients the user
// is not interested in).
//

# opts in to modular op registration support by default.
build --define framework_shared_object=true
build --define tsl_protobuf_header_only=true

build --define=use_fast_cpp_protos=true
build --define=allow_oversize_protos=true

build --spawn_strategy=standalone
build -c opt

# Make Bazel print out all options from rc files.
build --announce_rc

# TODO(mihaimaruseac): Document this option or remove if no longer needed