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);

  size_t r = fwrite(buffer, 1, n, posix_file->handle);
  if (r != n)

  EXPECT_NE(TF_GetCode(status.get()), TF_CANCELLED);
  EXPECT_EQ(TF_GetCode(status.get()), TF_INVALID_ARGUMENT);
  EXPECT_THAT(TF_Message(status.get()), HasSubstr("assertion failed"));

  // Note that future collectives with the same context do not work at the
  // moment; once canceled, the collective executor requires the program to be
  // restarted / context to be reset.
}

  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.

  if (enable) {
    optimizer_options->set_global_jit_level(tensorflow::OptimizerOptions::ON_1);

    // These XLA flags are needed to trigger XLA properly from C (more generally
    // non-Python) clients. If this API is called again with `enable` set to
    // false, it is safe to keep these flag values as is.
    tensorflow::MarkForCompilationPassFlags* flags =
        tensorflow::GetMarkForCompilationPassFlags();

  TensorHandlePtr cpu_value(FloatTensorHandle(3., status.get()));
  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());

  // Copying on to a parallel device must be explicit.
  TensorHandlePtr failed_copy_on_result(TFE_TensorHandleCopyToDevice(
      cpu_value.get(), context.get(), device_name, status.get()));
  EXPECT_EQ(TF_GetCode(status.get()), TF_UNIMPLEMENTED);

  auto gcs_file = static_cast<GCSFile*>(file->plugin_file);
  if (!gcs_file->outfile.is_open()) {
    TF_SetStatus(status, TF_FAILED_PRECONDITION,
                 "The internal temporary file is not writable.");
    return;
  }
  TF_VLog(3, "Append: gs://%s/%s size %u", gcs_file->bucket.c_str(),
          gcs_file->object.c_str(), n);
  gcs_file->sync_need = true;
  gcs_file->outfile.write(buffer, n);
  if (!gcs_file->outfile)

  //
  // `cancellation_manager` must live until after `Join` finishes and pending
  // `is_async` operations finish. In addition to allowing the caller to cancel
  // the operation, its `StartCancel` method will be called if op execution
  // fails on any device in order to cancel the others.
  void StartExecute(TFE_Context* context, const char* operation_name,
                    std::vector<TFE_TensorHandle*> inputs,

// be thrown in the registered graph optimization pass.
TEST(CAPI, DistributedFunctionGraphPassOnlyOnce) {
  // Register graph pass that will raise error if called more than once.
  tensorflow::optimization_registration::OptimizationPassRegistration
      register_test_pass(tensorflow::OptimizationPassRegistry::PRE_PLACEMENT, 0,

  if (ops->random_access_file_ops != nullptr)
    CheckAPI(ops->random_access_file_ops_api, TF_RANDOM_ACCESS_FILE_OPS_API,
             "random access file");

  if (ops->writable_file_ops != nullptr)
    CheckAPI(ops->writable_file_ops_api, TF_WRITABLE_FILE_OPS_API,
             "writable file");

  if (ops->read_only_memory_region_ops != nullptr)

  EXPECT_TRUE(first_block);
  EXPECT_EQ(out.size(), block_size);
  // Reading at offset file_size + 4 will read the second block (since the read
  // at file_size + 4 = 28 will be aligned to an offset of 16) but will return
  // OutOfRange because the offset is past the end of the 24-byte file.
  Status status = ReadCache(&cache, "", file_size + 4, 4, &out);
  EXPECT_EQ(status.code(), error::OUT_OF_RANGE);
  EXPECT_TRUE(second_block);