TF_Graph::TF_Graph()
    : graph(tensorflow::OpRegistry::Global()),
      refiner(graph.versions().producer(), graph.op_registry()),
      delete_requested(false),
      parent(nullptr),
      parent_inputs(nullptr) {
  // Tell the shape refiner to also run shape inference on functions.
  refiner.set_function_library_for_shape_inference(&graph.flib_def());
}

TF_Graph* TF_NewGraph() { return new TF_Graph; }

  TF_DeleteStatus(status);
  return counter;
}

void IncrementCounter0(TFE_MonitoringCounter0* counter, int64_t delta) {
  auto* cell = TFE_MonitoringGetCellCounter0(counter);
  TFE_MonitoringCounterCellIncrementBy(cell, delta);
}

TFE_MonitoringCounter1* CreateCounter1(const char* counter_name,
                                       const char* label) {
  TF_Status* status = TF_NewStatus();

  length = tf_writable_file::Tell(file, status_);
  ASSERT_EQ(length, 4);
  ASSERT_TF_OK(status_);
  tf_writable_file::Flush(file, status_);
  ASSERT_TF_OK(status_);
  ASSERT_TRUE(
      CompareWithServer(filepath, 0, 4, &gcs_file->gcs_client, status_));

  tf_writable_file::Append(file, content + 4, 4, status_);
  ASSERT_TF_OK(status_);
  length = tf_writable_file::Tell(file, status_);
  ASSERT_EQ(length, 8);

#include "tensorflow/core/platform/test.h"

// NOTE(allenl): These tests currently go through TFE_Execute and so are
// integration testing rather than purely testing the parallel device. They
// correspond fairly well to the implementation, but testing the C++ directly is
// another option.

namespace tensorflow {
namespace parallel_device {

Variable* Variable::Create(TFE_Context* context, TF_DataType type,

#include "tensorflow/core/platform/test.h"

// NOTE(allenl): These tests currently go through TFE_Execute and so are
// integration testing rather than purely testing the parallel device. They
// correspond fairly well to the implementation, but testing the C++ directly is
// another option.

namespace tensorflow {
namespace parallel_device {

using ::testing::HasSubstr;

TEST(PARALLEL_DEVICE, TestBasicCPU) {

      plugin_memory_allocate(TF_WRITABLE_FILE_OPS_SIZE));
  ops->writable_file_ops->cleanup = tf_writable_file::Cleanup;
  ops->writable_file_ops->append = tf_writable_file::Append;
  ops->writable_file_ops->tell = tf_writable_file::Tell;
  ops->writable_file_ops->flush = tf_writable_file::Flush;
  ops->writable_file_ops->sync = tf_writable_file::Sync;
  ops->writable_file_ops->close = tf_writable_file::Close;

      immediate_execution_ctx_.get(), {x.get()}, UseFunction()));
}

TEST_P(CppGradients, TestMatMulGrad) {
  // TODO(vnvo2409): Figure out why `gradient_checker` does not work very
  // well with `MatMul` and remove `TestMatMul*` in
  // `mnist_gradients_test` when done.
  GTEST_SKIP();

  float A_vals[] = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f};
  int64_t A_dims[] = {3, 3};

  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_DeleteStatus(status);
  auto* cell = TFE_MonitoringGetCellCounter0(counter);
  TFE_MonitoringCounterCellIncrementBy(cell, 1);
  EXPECT_EQ(TFE_MonitoringCounterCellValue(cell), 1);
  auto* collection_registry = monitoring::CollectionRegistry::Default();
  monitoring::CollectionRegistry::CollectMetricsOptions options;

  *result = filename_;
  return OkStatus();
}

Status ModularWritableFile::Tell(int64_t* position) {
  if (ops_->tell == nullptr)
    return errors::Unimplemented(
        tensorflow::strings::StrCat("Tell() not implemented for ", filename_));

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);
  *position = ops_->tell(file_.get(), plugin_status.get());
  return StatusFromTF_Status(plugin_status.get());
}

  if (!status.ok())
    GTEST_SKIP() << "NewWritableFile() not supported: " << status;

  int64_t position;
  status = file->Tell(&position);
  EXPECT_PRED2(UnimplementedOrReturnsCode, status, Code::OK);
  if (!status.ok()) GTEST_SKIP() << "Tell() not supported: " << status;
  EXPECT_EQ(position, 0);

  const std::string test_data("asdf");
  status = file->Append(test_data);