// Step 3: Call `TF_InitPlugin`
  TF_FilesystemPluginInfo info;
  memset(&info, 0, sizeof(info));
  auto TF_InitPlugin =
      reinterpret_cast<int (*)(TF_FilesystemPluginInfo*)>(dso_symbol);
  TF_InitPlugin(&info);

  // Step 4: Do the actual registration
  return filesystem_registration::RegisterFilesystemPluginImpl(&info);
}

  Status status;
  for (int i = 0; i < info->num_schemes; i++) {
    status.Update(ValidateAndRegisterFilesystems(info, i));
    info->plugin_memory_free(info->ops[i].scheme);
    info->plugin_memory_free(info->ops[i].filesystem_ops);
    info->plugin_memory_free(info->ops[i].random_access_file_ops);
    info->plugin_memory_free(info->ops[i].writable_file_ops);
    info->plugin_memory_free(info->ops[i].read_only_memory_region_ops);
  }

  void (*execute)(const TFE_Op* op, int* num_outputs,
                  TFE_TensorHandle** outputs, TF_Status* s, void* device_info);

  // Method to delete a device.
  void (*delete_device)(void* device_info);

  // Implements TFE_CreatePackedTensorHandle when one of `handles` is on this
  // custom device.
  //

namespace {
class CustomDeviceAPI : public tensorflow::CustomDevice {
 public:
  CustomDeviceAPI(TFE_Context* context, TFE_CustomDevice device, void* info,
                  string name)
      : context_(context), device_(device), info_(info), name_(name) {}

  ~CustomDeviceAPI() override { device_.delete_device(info_); }

  const string& name() override { return name_; }

  tensorflow::Status CopyTensorToDevice(

TF_CAPI_EXPORT extern TFE_TensorDebugInfo* TFE_TensorHandleTensorDebugInfo(
    TFE_TensorHandle* h, TF_Status* status);

// Deletes `debug_info`.
TF_CAPI_EXPORT extern void TFE_DeleteTensorDebugInfo(
    TFE_TensorDebugInfo* debug_info);

// Returns the number of dimensions used to represent the tensor on its device.
// The number of dimensions used to represent the tensor on device can be

}

void TF_InitPlugin(TF_FilesystemPluginInfo* info) {
  info->plugin_memory_allocate = plugin_memory_allocate;
  info->plugin_memory_free = plugin_memory_free;
  info->num_schemes = 1;
  info->ops = static_cast<TF_FilesystemPluginOps*>(
      plugin_memory_allocate(info->num_schemes * sizeof(info->ops[0])));
  ProvideFilesystemSupportFor(&info->ops[0], "gs");

}

void TF_InitPlugin(TF_FilesystemPluginInfo* info) {
  info->plugin_memory_allocate = plugin_memory_allocate;
  info->plugin_memory_free = plugin_memory_free;
  info->num_schemes = 2;
  info->ops = static_cast<TF_FilesystemPluginOps*>(
      plugin_memory_allocate(info->num_schemes * sizeof(info->ops[0])));
  ProvideFilesystemSupportFor(&info->ops[0], "");
  ProvideFilesystemSupportFor(&info->ops[1], "file");

    ],
    deps = [
        ":immediate_execution_operation",
        "//tensorflow/c:conversion_macros",
    ],
)

cc_library(
    name = "tfe_tensor_debug_info_internal",
    hdrs = ["tfe_tensor_debug_info_internal.h"],
    visibility = ["//visibility:private"],
    deps = [
        "//tensorflow/core:lib",
    ],
)

cc_library(
    name = "tfe_tensorhandle_internal",

        "Unable to find function with name: ", function_name);
    return;
  }

  tensorflow::GraphDebugInfo debug_info =
      tensorflow::StackTracesMapToGraphDebugInfo(
          function_record->stack_traces());

  string str = debug_info.SerializeAsString();
  void* data = tensorflow::port::Malloc(str.length());
  str.copy(static_cast<char*>(data), str.length(), 0);
  buf->data = data;

//
// Since this function is used to satisfy the TFE_CustomDevice C API,
// device_info is passed in using a C-style generic. It must always be a
// ParallelDevice.
void DeleteParallelDevice(void* device_info) {
  delete reinterpret_cast<NamedParallelDevice*>(device_info);
}

}  // namespace

void AllocateParallelDevice(const char* device_name,