EXPECT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  // Fetch and see that the new value is returned.
  TF_GraphGetTensorShape(graph, feed_out_0, returned_dims, num_dims, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  EXPECT_EQ(2, num_dims);
  EXPECT_EQ(2, returned_dims[0]);
  EXPECT_EQ(3, returned_dims[1]);

  // Try to fetch a shape with the wrong num_dims

        break;
      case FetchState::FINISHED:
        return TF_SetStatus(status, TF_OK, "");
    }
  }
  return TF_SetStatus(
      status, TF_INTERNAL,
      "Control flow should never reach the end of RamFileBlockCache::Fetch.");
}

int64_t RamFileBlockCache::Read(const std::string& filename, size_t offset,
                                size_t n, char* buffer, TF_Status* status) {
  if (n == 0) {

  // fill the cache, and the loop with i = 1 should be all cache hits. The
  // fetcher checks that it is called once and only once for each offset (to
  // fetch the corresponding block).
  for (int i = 0; i < 2; i++) {
    for (int j = 0; j < block_count; j++) {
      TF_EXPECT_OK(ReadCache(&cache, "", block_size * j, block_size, &out));
    }
  }
}

                              size_t* storage_size, TF_Status* status) {
  TF_SetStatus(status, TF_OK, "");
  const std::vector<std::string>& nodes =
      reinterpret_cast<const tensorflow::grappler::GrapplerItem*>(item)->fetch;
  *num_values = nodes.size();
  *storage_size = 0;
  for (const std::string& str : nodes) {
    *storage_size += str.size();
  }
}

void TF_GetFetchNodesList(const TF_GrapplerItem* item, char** values,

  EXPECT_EQ(item.fetch.size(), num_values);
  EXPECT_EQ(list_total_size, storage_size);

  std::unique_ptr<char*[]> values(new char*[item.fetch.size()]);
  std::unique_ptr<size_t[]> lens(new size_t[item.fetch.size()]);
  std::unique_ptr<char[]> storage(new char[storage_size]);
  TF_GetFetchNodesList(c_item, values.get(), lens.get(), item.fetch.size(),