code: def build_input(self, use_dataloader):
      self.feature_input = []
      for name, dim in zip(self.feature_names, self.feature_dims):
          self.feature_input.append(
              fluid.data(
                  shape=[None, dim],
                  lod_level=1,
                  dtype="float32",
                  name=name,
              )
          )
      if use_dataloader:
          assert (
              self.mode != "infer"
          ), "dataloader is not recommendated when infer, please set use_dataloader to be false."
          self.dataloader = fluid.io.DataLoader.from_generator(
              feed_list=self.feature_input,  # + [self.label_input],
              capacity=8,
              iterable=True,
          )
  
file_path: PaddleHub/modules/video/classification/videotag_tsn_lstm/resource/models/attention_lstm/attention_lstm.py
imports: import logging
  import paddle.fluid
  from paddle.fluid import ParamAttr
  from ..model import ModelBase
  from .lstm_attention import LSTMAttentionModel
label_desc: Use image node_id 3 for calling the AttentionLSTM obj's underlying member method code with example usage: obj.build_input(use_dataloader) without return types