code: def default_collate_fn(batch):
      """
      Default batch collating function for :code:`paddle.io.DataLoader`,
      get input data as a list of sample datas, each element in list
      if the data of a sample, and sample data should composed of list,
      dictionary, string, number, numpy array and paddle.Tensor, this
      function will parse input data recursively and stack number,
      numpy array and paddle.Tensor datas as batch datas. e.g. for
      following input data:
      [{'image': np.array(shape=[3, 224, 224]), 'label': 1},
       {'image': np.array(shape=[3, 224, 224]), 'label': 3},
       {'image': np.array(shape=[3, 224, 224]), 'label': 4},
       {'image': np.array(shape=[3, 224, 224]), 'label': 5},]
  
  
      This default collate function zipped each number and numpy array
      field together and stack each field as the batch field as follows:
      {'image': np.array(shape=[4, 3, 224, 224]), 'label': np.array([1, 3, 4, 5])}
      Args:
          batch(list of sample data): batch should be a list of sample data.
  
      Returns:
          Batched data: batched each number, numpy array and paddle.Tensor
                        in input data.
      """
      sample = batch[0]
      if isinstance(sample, np.ndarray):
          batch = np.stack(batch, axis=0)
          return batch
      elif isinstance(sample, (paddle.Tensor)):
          return paddle.stack(batch, axis=0)
      elif isinstance(sample, numbers.Number):
          batch = np.array(batch)
          return batch
      elif isinstance(sample, (str, bytes)):
          return batch
      elif isinstance(sample, Mapping):
          return {
              key: default_collate_fn([d[key] for d in batch])
              for key in sample
          }
      elif isinstance(sample, Sequence):
          sample_fields_num = len(sample)
          if not all(
              len(sample) == sample_fields_num for sample in iter(batch)
          ):
              raise RuntimeError(
                  "fileds number not same among samples in a batch"
              )
          return [default_collate_fn(fields) for fields in zip(*batch)]
  
      raise TypeError(
          "batch data con only contains: tensor, numpy.ndarray, "
          "dict, list, number, but got {}".format(type(sample))
      )
  
imports: import numbers
  import os
  import sys
  from collections import deque
  from collections.abc import Mapping
  import six
  from ppdet.core.workspace import register, serializable
  from ppdet.utils.logger import setup_logger
  from ppdet.data.reader import BaseDataLoader, Compose
  import cv2
  from imageio import imread, imwrite
  import numpy
  import paddle
  from paddle.framework import core
label_desc: Use image node_id 1 for calling a global function with example usage: default_collate_fn(batch) and returns: batch, paddle, batch, batch, unknown, unknown