values[i] = TF_NewBuffer();
    status->status = MessageToBuffer(attr->list().shape(i), values[i]);
    if (!status->status.ok()) {
      // Delete everything allocated to far, the operation has failed.
      for (int j = 0; j <= i; ++j) {
        TF_DeleteBuffer(values[j]);
      }
      return;
    }
  }
}

void TF_OperationGetAttrTensor(TF_Operation* oper, const char* attr_name,

  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.

    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 "
                    << filepath << ": " << TF_Message(s);

  GetWriter() {
    std::unique_ptr<TF_WritableFile, void (*)(TF_WritableFile * file)> writer(
        new TF_WritableFile, [](TF_WritableFile* file) {
          if (file != nullptr) {
            if (file->plugin_file != nullptr) tf_writable_file::Cleanup(file);
            delete file;
          }
        });
    writer->plugin_file = nullptr;
    return writer;
  }

  // `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,

  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);

/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,

void Sync(const TF_WritableFile* file, TF_Status* status) {
  auto gcs_file = static_cast<GCSFile*>(file->plugin_file);
  TF_VLog(3, "Sync: gs://%s/%s", gcs_file->bucket.c_str(),
          gcs_file->object.c_str());
  Flush(file, status);
}

void Close(const TF_WritableFile* file, TF_Status* status) {
  auto gcs_file = static_cast<GCSFile*>(file->plugin_file);
  TF_VLog(3, "Close: gs://%s/%s", gcs_file->bucket.c_str(),