class_docstr: ModuleV1 is an old version of the PaddleHub Module format, which is no longer in use. In order to maintain
  compatibility, users can still load the corresponding Module for prediction. User should call `hub.Module`
  to initialize the corresponding object, rather than `ModuleV1`.
docstr: Call the specified signature function for prediction.
docstr_tok: ["Call","the","specified","signature","function","for","prediction","."]
code: def __call__(
      self,
      sign_name: str,
      data: dict,
      use_gpu: bool = False,
      batch_size: int = 1,
      **kwargs,
  ):
      """Call the specified signature function for prediction."""
  
      def _get_reader_and_feeder(data_format, data, place):
          def _reader(process_data):
              for item in zip(*process_data):
                  yield item
  
          nonlocal feed_dict
          process_data = []
          feed_name_list = []
          feed_list = []
          for key in data_format:
              process_data.append(
                  [value["processed"] for value in data[key]]
              )
              feed_name_list.append(data_format[key]["feed_key"])
              feed_list.append(feed_dict[key])
          loader = paddle.io.DataLoader.from_generator(
              feed_list=feed_list, capacity=1
          )
          return (
              functools.partial(_reader, process_data=process_data),
              loader,
          )
  
      feed_dict, fetch_dict, program = self.context(
          signature=sign_name, for_test=True
      )
      fetch_list = list([value for key, value in fetch_dict.items()])
      with paddle.static.program_guard(program):
          result = []
          index = 0
          place = paddle.CUDAPlace(0) if use_gpu else paddle.CPUPlace()
  
          exe = paddle.static.Executor(place=place)
          data = self.processor.preprocess(
              sign_name=sign_name, data_dict=data
          )
          data_format = self.processor.data_format(sign_name=sign_name)
          reader, loader = _get_reader_and_feeder(
              data_format, data, place
          )
          reader = paddle.batch(reader, batch_size=batch_size)
          loader.set_sample_list_generator(reader, places=place)
          for batch in loader():
              data_out = exe.run(
                  feed=batch, fetch_list=fetch_list, return_numpy=False
              )
              sub_data = {
                  key: value[index : index + len(batch)]
                  for key, value in data.items()
              }
              result += self.processor.postprocess(
                  sign_name, data_out, sub_data, **kwargs
              )
              index += len(batch)
  
      return result
  
imports: import functools
  import os
  from typing import List
  from typing import Tuple
  import paddle.io
  import paddle2onnx
  from easydict import EasyDict
  from paddlehub.compat import paddle_utils
  from paddlehub.compat.module import module_v1_utils
  from paddlehub.utils import log
  from paddlehub.utils import utils
label_desc: Use image node_id 10 for calling the ModuleV1 obj's underlying member method code with example usage: obj.__call__(sign_name, data, use_gpu, batch_size) and returns: result, functools,  loader