return nullptr;
}

}  // end namespace tracing
}  // end namespace tensorflow

// =============================================================================
// Public C API entry points
//
// These are only the generic entry points for the C API. This file does not
// have any visibility into the graph/eager implementation and is only providing
// C bindings to the abstract classes defined in the

  if (enable) {
    optimizer_options->set_global_jit_level(tensorflow::OptimizerOptions::ON_1);

    // These XLA flags are needed to trigger XLA properly from C (more generally
    // non-Python) clients. If this API is called again with `enable` set to
    // false, it is safe to keep these flag values as is.
    tensorflow::MarkForCompilationPassFlags* flags =
        tensorflow::GetMarkForCompilationPassFlags();

namespace {

#if !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)

// Creates a placeholder representing an input to the cond or body graph.
// TODO(skyewm): remove these from final graph
bool CreateInput(const TF_Output& parent_input, TF_Graph* g, const char* name,
                 TF_Output* input, TF_Status* status) {
  TF_OperationDescription* desc = TF_NewOperation(g, "Placeholder", name);

  return absl::OkStatus();
}

// Helper functions which delegate to `AbstractOperation`, update
// the state of the ForwardOperation and call the tape as appropriate.
// These APIs are mainly to facilitate testing and are subject to change.
namespace internal {
Status Reset(AbstractOperation* op_, const char* op,
             const char* raw_device_name, ForwardOperation* forward_op_) {

  }
  for (int i = ndim - 2; i >= 0; --i) {
    (*stride_arr)[i] = (*shape_arr)[i + 1] * (*stride_arr)[i + 1];
  }

  dlm_tensor->dl_tensor.shape = shape_arr->data();
  // There are two ways to represent compact row-major data
  // 1) nullptr indicates tensor is compact and row-majored.
  // 2) fill in the strides array as the real case for compact row-major data.

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,
// multiple DeviceThreads should always be accessed in the same order to avoid
// deadlocks.
class DeviceThread {
 public:

  std::vector<std::pair<string, string>> grads = GetGradDefs(gdef);
  ASSERT_EQ(1, grads.size());
  ASSERT_EQ(func_name_, grads[0].first);
  ASSERT_EQ("MyGrad", grads[0].second);

  // These calls must be noops
  TF_GraphCopyFunction(host_graph_, func_, grad_func, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  TF_GraphCopyFunction(host_graph_, func_, nullptr, s_);

void DeleteDir(const TF_Filesystem* filesystem, const char* path,
               TF_Status* status) {
  // A directory is considered empty either if there are no matching objects
  // with the corresponding name prefix or if there is exactly one matching
  // object and it is the directory marker. Therefore we need to retrieve
  // at most two children for the prefix to detect if a directory is empty.

  server_def_0.mutable_default_session_config()->set_isolate_session_state(
      false);
  tensorflow::ServerDef server_def_1 =
      ReplaceTaskInServerDef(server_def_0, /*task_index=*/0);

  // These server defs have task index set to 0.
  string serialized_server_def_0 = server_def_0.SerializeAsString();
  string serialized_server_def_1 = server_def_1.SerializeAsString();

  // Create two worker tasks.

  server_def_0.mutable_default_session_config()->set_isolate_session_state(
      false);
  tensorflow::ServerDef server_def_1 =
      ReplaceTaskInServerDef(server_def_0, /*task_index=*/0);

  // These server defs have task index set to 0.
  string serialized_server_def_0 = server_def_0.SerializeAsString();
  string serialized_server_def_1 = server_def_1.SerializeAsString();

  // Create two worker tasks.