// --------------------------------------------------------------------------
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; }

      TFE_NewContextOptions(), TFE_DeleteContextOptions);
  std::unique_ptr<TF_Buffer, decltype(&TF_DeleteBuffer)> config(
      TF_CreateConfig(
          /*xla*/ false,
          /* gpu_memory_allow_growth */ true, /* num_cpu_devices */
          2),
      TF_DeleteBuffer);
  TFE_ContextOptionsSetConfig(opts.get(), config->data, config->length,
                              status.get());

  } 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

    return errors::FailedPrecondition(
        "Filesystem allows creation of random access files but no "
        "operations on them have been supplied.");

  if ((ops->filesystem_ops->new_writable_file != nullptr ||
       ops->filesystem_ops->new_appendable_file != nullptr) &&
      ops->writable_file_ops == nullptr)
    return errors::FailedPrecondition(
        "Filesystem allows creation of writable files but no "

      if (operation_name == std::string("_EagerConst")) {
        // Non-parallel tensors from _EagerConst/tf.constant are implicitly
        // broadcast, i.e. set as the input to each parallel operation. This
        // allows code like "tf.constant(1.)" or "tf.reduce_sum(..., axis=1)"
        // (where the value starts on the host), without allowing other implicit
        // copies/broadcasts. Other implicit copies may be supported eventually,

 public:
  void operator()(TFE_Executor* to_delete) const {
    TFE_DeleteExecutor(to_delete);
  }
};

using ExecutorPtr = std::unique_ptr<TFE_Executor, ExecutorDeleter>;

}  // namespace

// Allows a single op at a time to be launched without blocking.
//
// DeviceThread itself is thread-safe, in that StartExecute will block if there
// is a pending execution. Since StartExecute is equivalent to grabbing a lock,

      TFE_NewContextOptions(), TFE_DeleteContextOptions);
  std::unique_ptr<TF_Buffer, decltype(&TF_DeleteBuffer)> config(
      TF_CreateConfig(
          /*enable_xla_compilation=*/false,
          /*gpu_memory_allow_growth=*/true, /*num_cpu_devices=*/2),
      TF_DeleteBuffer);
  TFE_ContextOptionsSetConfig(opts.get(), config->data, config->length,
                              status.get());

      memcpy(buffer + copy_size, gcs_file->buffer.data(), remaining_copy);
      copy_size += remaining_copy;
    }
    if (copy_size < n) {
      // Forget the end-of-file flag to allow for clients that poll on the
      // same file.
      gcs_file->buffer_end_is_past_eof = false;
      TF_SetStatus(status, TF_OUT_OF_RANGE, "Read less bytes than requested");
      return copy_size;
    }

  if (GetParam().empty()) {
    EXPECT_EQ(fs->TranslateName(""), "");
    EXPECT_EQ(fs->TranslateName("/"), "/");
    EXPECT_EQ(fs->TranslateName("//"), "/");
    // Empty scheme also allows relative paths
    EXPECT_EQ(fs->TranslateName("a_file"), "a_file");
    EXPECT_EQ(fs->TranslateName("a_dir/.."), ".");
  } else {
    EXPECT_EQ(fs->TranslateName(tensorflow::strings::StrCat(GetParam(), "://")),

  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();