static void RenameFile(const TF_Filesystem* filesystem, const char* src,
                       const char* dst, TF_Status* status) {
  // If target is a directory return TF_FAILED_PRECONDITION.
  // Target might be missing, so don't error in that case.
  struct stat st;
  if (stat(dst, &st) != 0) {
    if (errno != ENOENT) {
      TF_SetStatusFromIOError(status, errno, dst);
      return;
    }
  } else if (S_ISDIR(st.st_mode)) {

  }
  registry_.insert({op_name, gradient_function_factory});
  return absl::OkStatus();
}
Status GradientRegistry::Lookup(
    const ForwardOperation& op,
    std::unique_ptr<GradientFunction>* gradient_function) const {
  auto iter = registry_.find(op.op_name);
  if (iter == registry_.end()) {
    const string error_msg = "No gradient defined for op: " + op.op_name + ".";
    return errors::NotFound(error_msg);

    status_ = StatusFromTF_Status(status.get());
    ASSERT_EQ(errors::OK, status_.code()) << status_.message();

    {
      AbstractContext* ctx_raw = nullptr;
      status_ =
          BuildImmediateExecutionContext(std::get<1>(GetParam()), &ctx_raw);
      ASSERT_EQ(errors::OK, status_.code()) << status_.message();
      immediate_execution_ctx_.reset(ctx_raw);
    }

  if (h == nullptr) {
    status->status = tensorflow::errors::InvalidArgument("Invalid handle");
    return nullptr;
  }
  tensorflow::TensorHandle* handle =
      tensorflow::TensorHandleFromInterface(tensorflow::unwrap(h));
  if (handle->Type() != TensorHandle::LOCAL) {
    status->status = tensorflow::errors::InvalidArgument(
        "DLPack doesn't support ", handle->TypeString(), " tensor");

    shape_string = shape.DebugString();
  } else {
    shape_string = "<error computing shape>";
  }
  std::string value_string;
  if (!SummarizeValue(value_string).ok()) {
    value_string = "<error computing value>";
  }
  if (value_string.length() > 100) {
    // The default NumPy-style output can be distractingly long in error
    // messages.
    value_string = absl::StrCat(value_string.substr(0, 100), " [...]");
  }

    status_ = StatusFromTF_Status(status.get());
    ASSERT_EQ(errors::OK, status_.code()) << status_.message();

    {
      AbstractContext* ctx_raw = nullptr;
      status_ =
          BuildImmediateExecutionContext(std::get<1>(GetParam()), &ctx_raw);
      ASSERT_EQ(errors::OK, status_.code()) << status_.message();
      immediate_execution_ctx_.reset(ctx_raw);
    }

                               TransactionToken* token, FileStatistics* stat) {
  if (ops_->stat == nullptr)
    return errors::Unimplemented(tensorflow::strings::StrCat(
        "Filesystem for ", fname, " does not support Stat()"));

  if (stat == nullptr)
    return errors::InvalidArgument("FileStatistics pointer must not be NULL");

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);

        } else {
          block->state = FetchState::ERROR;
        }
        block->cond_var.SignalAll();
        return;
      case FetchState::FETCHING:
        block->cond_var.WaitWithTimeout(&block->mu, absl::Minutes(1));
        if (block->state == FetchState::FINISHED) {
          return TF_SetStatus(status, TF_OK, "");
        }
        // Re-loop in case of errors.
        break;
      case FetchState::FINISHED:

  EXPECT_EQ(TF_ALREADY_EXISTS,
            static_cast<TF_Code>(tensorflow::error::ALREADY_EXISTS));
  EXPECT_EQ(TF_PERMISSION_DENIED,
            static_cast<TF_Code>(tensorflow::error::PERMISSION_DENIED));
  EXPECT_EQ(TF_UNAUTHENTICATED,
            static_cast<TF_Code>(tensorflow::error::UNAUTHENTICATED));
  EXPECT_EQ(TF_RESOURCE_EXHAUSTED,

  TFE_DeleteContext(ctx);
  TF_DeleteStatus(status);
}
TEST(CAPI, Execute_MatMul_CPU_Runtime_Error) {
  Execute_MatMul_CPU_Runtime_Error(false);
}
TEST(CAPI, Execute_MatMul_CPU_Runtime_ErrorAsync) {
  Execute_MatMul_CPU_Runtime_Error(true);
}

void Execute_MatMul_CPU_Type_Error(bool async) {
  TF_Status* status = TF_NewStatus();
  TFE_ContextOptions* opts = TFE_NewContextOptions();