srcs = ["c_api_test.cc"],
    data = [
        ":test_op1.so",
        "//tensorflow/cc/saved_model:saved_model_half_plus_two",
    ],
    linkopts = select({
        "//tensorflow:macos": ["-headerpad_max_install_names"],
        "//conditions:default": [],
    }),
    tags = [
        "no_cuda_asan",  # TODO(b/181771536)
        "no_windows",  # TODO(b/155444728)
    ],

          uint64_t block_size, size_t max_bytes, uint64_t max_staleness,
          uint64_t stat_cache_max_age, size_t stat_cache_max_entries);
} GCSFile;

// This function is used to initialize a filesystem without the need of setting
// manually environement variables.
void InitTest(TF_Filesystem* filesystem, bool compose, uint64_t block_size,
              size_t max_bytes, uint64_t max_staleness,

                        const TFE_OpAttrs* attributes, int expected_max_outputs,
                        TF_Status* status) const {
  std::vector<PartialTensorShape> expected_output_shapes(expected_max_outputs);
  StartExecute(context, inputs, operation_name, attributes,
               expected_max_outputs, *default_cancellation_manager_);
  auto result = Join(expected_output_shapes, status);

  while (n > 0) {
    // Some platforms, notably macs, throw `EINVAL` if `pread` is asked to read
    // more than fits in a 32-bit integer.
    size_t requested_read_length;
    if (n > INT32_MAX)
      requested_read_length = INT32_MAX;
    else
      requested_read_length = n;

    // `pread` returns a `ssize_t` on POSIX, but due to interface being
    // cross-platform, return type of `Read` is `int64_t`.

// an array of length at least `max_inputs` (ideally set to
// TF_OperationNumInputs(oper)).  Beware that a concurrent
// modification of the graph can increase the number of inputs of
// an operation.
TF_CAPI_EXPORT extern void TF_OperationAllInputs(TF_Operation* oper,
                                                 TF_Output* inputs,
                                                 int max_inputs);

action_spec {
  action: CHECK_FILE_COUNT
  file_count_params {
    rule_selector {
      rule_kind_regex: "^.*py(type)?(_strict)?_(binary|library|test).*$"
      generator_function_regex: "^(?!boq_header)$"
    }
    max_source_count: 1
  }

        `tf.quantization.fake_quant_with_min_max_args`,
        `tf.quantization.fake_quant_with_min_max_args_gradient`,
        `tf.quantization.fake_quant_with_min_max_vars`,
        `tf.quantization.fake_quant_with_min_max_vars_gradient`,
        `tf.quantization.fake_quant_with_min_max_vars_per_channel`,
        `tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient`.

  absl::optional<std::vector<std::unique_ptr<ParallelTensor>>> Execute(
      TFE_Context* context, const std::vector<ParallelTensor*>& inputs,
      const char* operation_name, const TFE_OpAttrs* attributes,
      int expected_max_outputs, TF_Status* status) const;

  // A non-blocking version of `Execute`. After each call, `Join` must be called
  // before `StartExecute` is called again. Using `StartExecute` with `Join`

  return g->graph.flib_def().num_functions();
}

int TF_GraphGetFunctions(TF_Graph* g, TF_Function** funcs, int max_func,
                         TF_Status* status) {
  tensorflow::FunctionDefLibrary lib;
  {
    tensorflow::mutex_lock l(g->mu);
    lib = g->graph.flib_def().ToProto();
  }
  const auto len = std::min(max_func, static_cast<int>(lib.function_size()));
  for (int i = 0; i < len; ++i) {

    const std::string& parallel_device_name, TFE_Context* context,
    std::vector<MaybeParallelTensorUnowned> inputs, const char* operation_name,
    const TFE_OpAttrs* attributes, int expected_max_outputs,
    TF_Status* status) {
  absl::optional<std::vector<MaybeParallelTensorOwned>> result;
  // TODO(allenl): We should remove "TPU" from these op names at the very least,