class_docstr: A way to represent a set of dot chained operations on an object without actually running them.
      
class_docstr_tok: ["A","way","to","represent","a","set","of","dot","chained","operations","on","an","object","without","actually","running","them","."]
docstr: Update the args for the previous operation.
          
docstr_tok: ["Update","the","args","for","the","previous","operation","."]
code: def __call__(self, *args, **kwargs):
      """Update the args for the previous operation."""
      new_self = OpChain(self._root_name)
      new_self._ops = copy.copy(self._ops)
      new_self._ops[-1][1] = args
      new_self._ops[-1][2] = kwargs
      return new_self
  
imports: import copy
  import os
  import re
  import sys
  from contextlib import contextmanager
  import numpy
  import pandas
  import scipy.special
  import sklearn
label_desc: Use image node_id 3 for calling the OpChain obj's underlying member method code with example usage: obj.__call__() and returns: new_self