class_docstr: Pipeline built by a list of Transform instance.
class_docstr_tok: ["Pipeline","built","by","a","list","of","Transform","instance","."]
docstr: Apply transform pipe to `example`.
  
  Args:
      example (dict): a dict of field value, ex. src, tgt.
docstr_tok: ["Apply","transform","pipe","to","`","example","`",".","Args",":","example","(","dict",")",":","a","dict","of","field","value",",","ex",".","src",",","tgt","."]
code: def batch_apply(self, batch, is_train=False, **kwargs):
      """Apply transform pipe to `example`.
  
      Args:
          example (dict): a dict of field value, ex. src, tgt.
  
      """
      for transform in self.transforms:
          batch = transform.batch_apply(
              batch, is_train=is_train, stats=self.statistics, **kwargs
          )
          if batch is None:
              break
      return batch
  
imports: import torch
  from onmt.utils.logging import logger
  from onmt.utils.misc import check_path
label_desc: Use image node_id 6 for calling the TransformPipe obj's underlying member method code with example usage: obj.batch_apply(batch, is_train) and returns: batch