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                                                             TF_DeleteGraph);

  TF_SessionOptions* opts = TF_NewSessionOptions();
  TF_Session* sess = TF_NewSession(graph.get(), opts, s);
  TF_DeleteSessionOptions(opts);

  const string gpu_device_name = GPUDeviceName(sess);
  TF_DeleteSession(sess, s);
  CHECK_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  return gpu_device_name;
}

    AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs,
    absl::Span<AbstractTensorHandle*> outputs) {
  AbstractTensorHandle* loss;
  AbstractTensorHandle* backprop;
  TF_RETURN_IF_ERROR(ops::SparseSoftmaxCrossEntropyWithLogits(
      ctx, inputs[0], inputs[1], &loss, &backprop,
      "SparseSoftmaxCrossEntropyWithLogits"));
  // `gradient_checker` only works with model that returns only 1 tensor.

filegroup(
    name = "tensorflow_def_file",
    srcs = [":tf_custom_op_library_additional_deps.dll"],
    output_group = "def_file",
)

# Filter the DEF file to reduce the number of symbols to 64K or less.
# Note that we also write the name of the pyd file into DEF file so that
# the dynamic libraries of custom ops can find it at runtime.
genrule(
    name = "tensorflow_filtered_def_file",

  // there isn't an intervening PushState. This is useful for ordering
  // ForwardAccumulators, where more deeply nested accumulators should not see
  // computations from less deeply nested accumulators.
  bool BusyAccumulating() const { return call_state_.top().accumulating; }

  // Fetches the current Jacobian-vector product associated with `tensor_id`, or
  // a nullptr if none is available.

      * If you passed a value to the `loss_scale` argument (the second argument) of `Policy`:

                                    const size_t* proto_lens, int num_shapes,
                                    TF_Status* status) {
  std::vector<TensorShapeProto> shapes;
  shapes.resize(num_shapes);
  for (int i = 0; i < num_shapes; ++i) {
    if (proto_lens[i] > std::numeric_limits<int>::max()) {
      status->status = InvalidArgument(
          "length of element ", i, " in the list (", proto_lens[i],

  if (prefix == nullptr || strlen(prefix) == 0)
    prefix = "/job:localhost/replica:0/task:0";

  tensorflow::SessionOptions sess_options;
  (*sess_options.config.mutable_device_count())["CPU"] = num_cpus;
  status->status =
      tensorflow::DeviceFactory::AddCpuDevices(sess_options, prefix, &devices);

  // Remove the device that has the host device name since host device is alreay
  // in an initialized context.