TFE_TensorHandle* h = TFE_NewTensorHandle(t, status);
    ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
    TF_DeleteTensor(t);

    TFE_Op* op = TFE_NewOp(ctx, "ident", status);
    ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
    TFE_OpAddInput(op, h, status);
    ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);

    std::vector<TFE_TensorHandle*> result;

      return TF_SetStatus(status, TF_INTERNAL,
                          "Block cache contents are inconsistent.");
    }
  }

  Trim();

  return TF_SetStatus(status, TF_OK, "");
}

void RamFileBlockCache::MaybeFetch(const Key& key,
                                   const std::shared_ptr<Block>& block,
                                   TF_Status* status) {
  bool downloaded_block = false;

    out->resize(bytes_transferred, n);
  }
  return status.status;
}

TEST(RamFileBlockCacheTest, IsCacheEnabled) {
  auto fetcher = [](const string& filename, size_t offset, size_t n,
                    char* buffer, TF_Status* status) -> int64_t {
    // Do nothing.
    TF_SetStatus(status, TF_OK, "");
    return 0;
  };
  tf_gcs_filesystem::RamFileBlockCache cache1(0, 0, 0, fetcher);

    CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
    TFE_OpAddInput(matmul, m, status);
    CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
    TFE_OpAddInput(matmul, m, status);
    CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
    TFE_Execute(matmul, &retvals[0], &num_retvals, status);
    CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  TF_OutputListSetNumOutputs(mm_outputs, 1, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  TF_ExecuteOperation(fn_op, 1, &input_t, mm_outputs, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  return StatusFromTF_Status(plugin_status.get());
}

Status ModularWritableFile::Sync() {
  if (ops_->sync == nullptr) return Flush();

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);
  ops_->sync(file_.get(), plugin_status.get());
  return StatusFromTF_Status(plugin_status.get());
}

Status ModularWritableFile::Name(StringPiece* result) const {
  *result = filename_;
  return OkStatus();
}

  if (!status.ok()) GTEST_SKIP() << "Append() not supported: " << status;
  status = new_file->Flush();
  if (!status.ok()) GTEST_SKIP() << "Flush() not supported: " << status;
  status = new_file->Close();
  if (!status.ok()) GTEST_SKIP() << "Close() not supported: " << status;

  std::unique_ptr<ReadOnlyMemoryRegion> region;
  status = env_->NewReadOnlyMemoryRegionFromFile(filepath, &region);

 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());
    TF_SetTracingImplementation(std::get<0>(GetParam()), status.get());
    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);

  TF_EXPECT_OK(status.status);
  EXPECT_EQ(value, 1);
  EXPECT_EQ(num_compute_calls, 2);
  cache2.LookupOrCompute("c", &value, compute_func, &status);
  TF_EXPECT_OK(status.status);
  EXPECT_EQ(value, 2);
  EXPECT_EQ(num_compute_calls, 3);
  cache2.LookupOrCompute("d", &value, compute_func, &status);
  TF_EXPECT_OK(status.status);
  EXPECT_EQ(value, 3);
  EXPECT_EQ(num_compute_calls, 4);

    TF_Status* out_status) const {
  Status status;
  if (reader_ != nullptr) {
    status = reader_->GetTensor(name, out_tensor);
  } else {
    tensorflow::DataType dtype;
    tensorflow::TensorShape shape;
    status = v2_reader_->LookupDtypeAndShape(name, &dtype, &shape);
    if (status.ok()) {
      out_tensor->reset(new Tensor(dtype, shape));
      status = v2_reader_->Lookup(name, out_tensor->get());