// DT_RESOURCE. The string serialization is converted back to a
// ResourceHandle during Session run where the TF_Tensor is converted to a
// Tensor.
// TFv2 does not depend on this conversion. There is no matching
// TF_TensorFromTensorV1 because the conversion to string is performed by the
// python side of Session.
static Status TF_TensorToTensorV1(const TF_Tensor* src, Tensor* dst) {

  ops->writable_file_ops = static_cast<TF_WritableFileOps*>(
      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;

    control_output_nodes.push_back(&control_outputs[i]->node);
  }

  // Do the actual function creation.
  DCHECK(append_hash_to_fn_name <= 1);
  tensorflow::FunctionDef fdef;
  status->status = tensorflow::GraphToFunctionDef(
      fn_body->graph, fn_name, append_hash_to_fn_name != 0,
      /*set_stateful_from_nodes=*/true,
      /*copy_placeholder_attrs_from_nodes=*/true, body_nodes, input_tensors,

  ASSERT_TF_OK(status_);
  tf_writable_file::Append(file, content, 4, status_);
  ASSERT_TF_OK(status_);
  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_);

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

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

  *result = filename_;
  return OkStatus();
}

Status ModularWritableFile::Append(StringPiece data) {
  if (ops_->append == nullptr)
    return errors::Unimplemented(tensorflow::strings::StrCat(
        "Append() not implemented for ", filename_));

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);
  ops_->append(file_.get(), data.data(), data.size(), plugin_status.get());

  const char* output_name = "y";
  std::unique_ptr<TF_Function, decltype(&TF_DeleteFunction)> function(
      TF_GraphToFunction(
          /* fn_body */ body.get(), /* fn_name */ function_name,
          /* append_hash_to_fn_name */ 0, /* num_opers */ 2,
          /* opers */ operations, /* ninputs */ 1, /* inputs */ &x,
          /* noutputs */ 1, /* outputs */ &y, /* output_names */ &output_name,

                    << TF_Message(s);

    const char* data = "Hello, world!\n";
    TF_AppendWritableFile(handle, data, strlen(data), s);
    ASSERT_TF_OK(s) << "TF_AppendWritableFile failed to append data to file at "
                    << filepath << ": " << TF_Message(s);

    TF_CloseWritableFile(handle, s);
    ASSERT_TF_OK(s) << "TF_CloseWritableFile failed to close handle to "

  auto* cc_file = reinterpret_cast<::tensorflow::WritableFile*>(handle);
  TF_SetStatus(status, TF_OK, "");
  ::tensorflow::Set_TF_Status_from_Status(
      status, cc_file->Append(::tensorflow::StringPiece{data, length}));
}

void TF_DeleteFile(const char* filename, TF_Status* status) {
  TF_SetStatus(status, TF_OK, "");
  ::tensorflow::Set_TF_Status_from_Status(

GCSFile::GCSFile(google::cloud::storage::Client&& gcs_client)
    : gcs_client(gcs_client), block_cache_lock() {
  const char* append_mode = std::getenv(kAppendMode);
  compose = (append_mode != nullptr) && (!strcmp(kAppendMode, append_mode));

  uint64_t value;
  block_size = kDefaultBlockSize;
  size_t max_bytes = kDefaultMaxCacheSize;
  uint64_t max_staleness = kDefaultMaxStaleness;