ops_->new_read_only_memory_region_from_file(
      filesystem_.get(), translated_name.c_str(), region.get(),
      plugin_status.get());

  if (TF_GetCode(plugin_status.get()) == TF_OK)
    *result = std::make_unique<ModularReadOnlyMemoryRegion>(
        std::move(region), read_only_memory_region_ops_.get());

  return StatusFromTF_Status(plugin_status.get());
}

    const std::vector<std::string>& device_names = ListDeviceNames(ctx_0);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());
  }

  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_1);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());
  }

// completed. The memory returned might alias the internal memory used by
// TensorFlow. Hence, callers should not mutate this memory (for example by
// modifying the memory region pointed to by TF_TensorData() on the returned
// TF_Tensor).
TF_CAPI_EXPORT extern TF_Tensor* TFE_TensorHandleResolve(TFE_TensorHandle* h,
                                                         TF_Status* status);

                                TF_WRITABLE_FILE_OPS_ABI, "writable file"));

  if (ops->read_only_memory_region_ops != nullptr)
    TF_RETURN_IF_ERROR(CheckABI(ops->read_only_memory_region_ops_abi,
                                TF_READ_ONLY_MEMORY_REGION_OPS_ABI,
                                "read only memory region"));

  return OkStatus();
}

// Checks if the plugin and core API numbers match, logging mismatches.

  TapeVSpace vspace(ctx);
  std::vector<int64_t> target_tensor_ids = MakeTensorIDList(targets);
  std::vector<int64_t> source_tensor_ids = MakeTensorIDList(sources);
  tensorflow::gtl::FlatSet<int64_t> sources_set(source_tensor_ids.begin(),
                                                source_tensor_ids.end());
  std::unordered_map<int64_t, TapeTensor> sources_that_are_targets;
  for (int i = 0; i < target_tensor_ids.size(); ++i) {

  ops->read_only_memory_region_ops = static_cast<TF_ReadOnlyMemoryRegionOps*>(
      plugin_memory_allocate(TF_READ_ONLY_MEMORY_REGION_OPS_SIZE));
  ops->read_only_memory_region_ops->cleanup =
      tf_read_only_memory_region::Cleanup;
  ops->read_only_memory_region_ops->data = tf_read_only_memory_region::Data;
  ops->read_only_memory_region_ops->length = tf_read_only_memory_region::Length;

    ],
    visibility = [
        "//tensorflow/c:__subpackages__",
        "//tensorflow/cc/experimental/libtf:__pkg__",
        "//tensorflow/cc/experimental/libtf:__subpackages__",
        # copybara:uncomment_begin(google-only)
        # "//tensorflow/cc/experimental/tf2:__pkg__",
        # "//tensorflow/cc/experimental/tf2:__subpackages__",
        # copybara:uncomment_end

      tensorflow::DeviceFactory::AddCpuDevices(sess_options, prefix, &devices);

  // Remove the device that has the host device name since host device is alreay
  // in an initialized context.
  for (auto d = devices.begin(); d != devices.end();) {
    if (absl::StrContains(d->get()->name(), "CPU:0")) {
      d = devices.erase(d);
    } else {
      ++d;
    }
  }

  ops->read_only_memory_region_ops = static_cast<TF_ReadOnlyMemoryRegionOps*>(
      plugin_memory_allocate(TF_READ_ONLY_MEMORY_REGION_OPS_SIZE));
  ops->read_only_memory_region_ops->cleanup =
      tf_read_only_memory_region::Cleanup;
  ops->read_only_memory_region_ops->data = tf_read_only_memory_region::Data;
  ops->read_only_memory_region_ops->length = tf_read_only_memory_region::Length;

    TF_DeleteCheckpointReader(reader);
    return nullptr;
  }
  const auto& m = reader->GetVariableToDataTypeMap();
  for (auto it = m.begin(); it != m.end(); ++it)
    reader->variable_list.push_back(it->first);
  std::sort(reader->variable_list.begin(), reader->variable_list.end());
  return reader;
}

void TF_DeleteCheckpointReader(TF_CheckpointReader* reader) { delete reader; }