class_docstr: Helper class to transform torch function into torch nn module.
  This helps to keep the testing interface same for torch functional api.
class_docstr_tok: ["Helper","class","to","transform","torch","function","into","torch","nn","module",".","This","helps","to","keep","the","testing","interface","same","for","torch","functional","api","."]
code: def __init__(self, function, kwargs=None):
      super(ModuleWrapper, self).__init__()
      self.function = function
      self.kwargs = kwargs if kwargs else {}
  
imports: import numpy
  import torch
  import torch.nn
  from six import string_types
  from coremltools import TensorType
  from coremltools.converters.mil.testing_reqs import _converter
  from coremltools.models import MLModel
  from coremltools._deps import _IS_MACOS
label_desc: Use image node_id 1 to create a new ModuleWrapper object from inherited base classes: nn with example: obj = ModuleWrapper(function, kwargs)