GraphDef graph_def;
      *graph_def.mutable_versions() = graph.versions();
      // Fill graph_def with nodes with ids in the range
      // [session->last_num_graph_nodes, num_nodes), that is the nodes
      // added since the last TF_SessionRun() call.
      for (auto id = session->last_num_graph_nodes; id < num_nodes; ++id) {
        Node* const node = graph.FindNodeId(id);
        if (node != nullptr && node->IsOp()) {

    Status status = tensorflow::PartialTensorShape::MakePartialShape(
        reinterpret_cast<int64_t*>(shape.dim_sizes), shape.num_dims,
        &partial_shape);
    if (!status.ok()) {
      tsl::Set_TF_Status_from_Status(s, status);
      return nullptr;
    }
  }
  tsl::Set_TF_Status_from_Status(
      s, tracing_ctx->AddParameter(static_cast<DataType>(dtype), partial_shape,
                                   &t));

        EXPECT_EQ(dltensor_out->strides[i],
                  dltensor_out->shape[i + 1] * dltensor_out->strides[i + 1]);
      }
    }
  }
  const float* data_in = static_cast<const float*>(dltensor_in->data);
  const float* data_out = static_cast<const float*>(dltensor_out->data);
  for (size_t j = 0; j < num_elements; ++j) {
    EXPECT_EQ(data_out[j], data_in[j]);
  }

  TFE_CallDLManagedTensorDeleter(dlm_out);

}

void TF_InitPlugin(TF_FilesystemPluginInfo* info) {
  info->plugin_memory_allocate = plugin_memory_allocate;
  info->plugin_memory_free = plugin_memory_free;
  info->num_schemes = 2;
  info->ops = static_cast<TF_FilesystemPluginOps*>(
      plugin_memory_allocate(info->num_schemes * sizeof(info->ops[0])));
  ProvideFilesystemSupportFor(&info->ops[0], "");
  ProvideFilesystemSupportFor(&info->ops[1], "file");

  if (!isa<ImmediateExecutionContext>(ctx)) {
    // TODO(b/168850692): Fix this.
    return errors::Unimplemented(
        "BroadcastMul is not supported in tracing mode yet.");
  }
  auto imm_ctx = dyn_cast<ImmediateExecutionContext>(ctx);
  AbstractTensorPtr minus_1(imm_ctx->CreateInt32Scalar(-1));
  ImmediateTensorHandlePtr dim(imm_ctx->CreateLocalHandle(minus_1.get()));
  AbstractTensorHandle* expand_dims_outputs;

  TestRemoteExecuteUpdateServerDefResourceAccess(true);
}

void TestRemoteExecuteUpdateServerDefWithFailures(bool async) {
  // Fail fast on GetStatus requests so we can get errors instead of timeout
  // when updating cluster with non-exsitent worker
  tensorflow::setenv("GRPC_FAIL_FAST", "TRUE", /*overwrite=*/1);

  tensorflow::ServerDef server_def = GetServerDef(2);
  // This server def has the task index set to 0.

static void Cleanup(TF_WritableFile* file) {
  auto posix_file = static_cast<PosixFile*>(file->plugin_file);
  plugin_memory_free(const_cast<char*>(posix_file->filename));
  delete posix_file;
}

static void Append(const TF_WritableFile* file, const char* buffer, size_t n,
                   TF_Status* status) {
  auto posix_file = static_cast<PosixFile*>(file->plugin_file);

  if (TF_GetCode(s) != TF_OK) {
    return nullptr;
  }
  return wrap(static_cast<AbstractContext*>(unwrap(c_ctx)));
}

TF_AbstractTensor* TF_CreateAbstractTensorFromEagerTensor(TFE_TensorHandle* t,
                                                          TF_Status* s) {
  return wrap(static_cast<AbstractTensorHandle*>(unwrap(t)));
}

TFE_TensorHandle* TF_AbstractTensorGetEagerTensor(TF_AbstractTensor* at,

  flags->tf_xla_cpu_global_jit = static_cast<bool>(enable);
  return static_cast<unsigned char>(original);
}

void TF_SetXlaAutoJitMode(const char* mode) {
  tensorflow::SetXlaAutoJitFlagFromFlagString(mode);
}

unsigned char TF_GetXlaAutoJitEnabled() {
  tensorflow::XlaAutoJitFlag flag =
      tensorflow::GetMarkForCompilationPassFlags()->xla_auto_jit_flag;

  ASSERT_EQ(errors::OK, s.code()) << s.message();

  TF_Tensor* result_tensor;
  s = GetValue(outputs[0], &result_tensor);
  ASSERT_EQ(errors::OK, s.code()) << s.message();
  auto result_value = static_cast<float*>(TF_TensorData(result_tensor));
  EXPECT_EQ(*result_value, 1.0);
  outputs[0]->Unref();
  TF_DeleteTensor(result_tensor);
  result_tensor = nullptr;
}

INSTANTIATE_TEST_SUITE_P(