EXPECT_EQ(DT_FLOAT, out_props.dtype());
      EXPECT_FALSE(out_props.shape().unknown_rank());
      EXPECT_EQ(2, out_props.shape().dim_size());
      EXPECT_EQ(10, out_props.shape().dim(0).size());
      EXPECT_EQ(1, out_props.shape().dim(1).size());

      for (int i = 0; i < out_props_buf.size(); i++)
        TF_DeleteBuffer(out_props_buf[i]);
    }
  }
  TF_DeleteStatus(status);

  tensorflow::Tensor tensor(allocator.get(), DT_FLOAT, {1});
  TF_ASSERT_OK_AND_ASSIGN(
      auto pjrt_client,
      xla::GetTfrtCpuClient(/*asynchronous=*/true, /*cpu_device_count=*/1));
  std::vector<int32_t> data(1, 0);
  xla::Shape shape = xla::ShapeUtil::MakeShape(xla::S32, {1});
  TF_ASSERT_OK_AND_ASSIGN(
      auto buffer,
      pjrt_client->BufferFromHostBuffer(

  ASSERT_TRUE(CompareSubString(0, 4, result, read));

  read = tf_random_access_file::Read(file, content_view.length() - 2, 4, result,
                                     status_);
  ASSERT_EQ(TF_GetCode(status_), TF_OUT_OF_RANGE) << TF_Message(status_);
  ASSERT_TRUE(CompareSubString(content_view.length() - 2, 2, result, read));

  delete[] result;
  tf_random_access_file::Cleanup(file);
  delete file;
}

  TFE_DeleteExecutor(executor);
  TFE_ContextRemoveFunction(ctx, "AddVariablesFunction", status);
  TFE_DeleteContext(ctx);

  TF_DeleteStatus(status);

  // TODO(b/136478427): Figure out how to correctly shut the server down.
  worker_server1.release();
  worker_server2.release();
}

TEST(CAPI, TestLocalFunctionWithPackedInput) {
  TestFunctionWithPackedInput(/*remote=*/false);
}

                                              TF_Status* status,
                                              void* device_info) {
  TF_SetStatus(status, TF_INTERNAL,
               "Trying to copy a tensor out of a logging device.");
  return nullptr;
}

void LoggingDeviceExecute(const TFE_Op* original_op, int* num_outputs,
                          TFE_TensorHandle** outputs, TF_Status* s,

                                             status);
  } else {
    TF_SetStatus(
        status, TF_UNIMPLEMENTED,
        absl::StrCat(
            "Trying to copy a tensor out of a parallel device. Since there "
            "are multiple components to parallel tensors, they must be "
            "unpacked explicitly.\n",
            tensorflow::unwrap(tensor)->DebugString())
            .c_str());

      tensorflow::Flag("tmp_dir", tensorflow::SetTmpDir, "",
                       "Temporary directory to store test data.")};
  if (!tensorflow::Flags::Parse(&argc, argv, flag_list)) {
    std::cout << tensorflow::Flags::Usage(argv[0], flag_list);
    return -1;
  }

  tensorflow::testing::InstallStacktraceHandler();
  tensorflow::ModularFileSystemTest::InitializeTestRNG();

  std::vector<std::string> result;
  uint64_t count = 0;
  std::string delimiter = recursive ? "" : "/";

  for (auto&& item : gcs_file->gcs_client.ListObjectsAndPrefixes(
           bucket, gcs::Prefix(prefix), gcs::Delimiter(delimiter),
           gcs::Fields("items(name),prefixes"))) {
    if (count == max_results) {
      TF_SetStatus(status, TF_OK, "");
      return result;
    }

    for (int i = 0; i < expected_results.size(); ++i) {
      TF_Tensor* out = csession.output_tensor(i);
      ASSERT_TRUE(out != nullptr);
      EXPECT_EQ(TF_INT32, TF_TensorType(out));
      EXPECT_EQ(0, TF_NumDims(out));  // scalar
      ASSERT_EQ(sizeof(int32_t), TF_TensorByteSize(out));
      int32_t* output_contents = static_cast<int32_t*>(TF_TensorData(out));
      EXPECT_EQ(expected_results[i], *output_contents);
    }
  }

                                                           int bucket_count) {
  return new TFE_MonitoringBuckets([scale, growth_factor, bucket_count]() {
    return tensorflow::monitoring::Buckets::Exponential(scale, growth_factor,
                                                        bucket_count);
  });
}

void TFE_MonitoringDeleteBuckets(TFE_MonitoringBuckets* buckets) {
  delete buckets;