class_docstr: This class is used in cases when the parameter should not be initialized by
  the initializer, but rather provided in the workspace when param_init_net is
  executed.
  
  Current version is not doing any real sanity checks to the parameter.
class_docstr_tok: ["This","class","is","used","in","cases","when","the","parameter","should","not","be","initialized","by","the","initializer",",","but","rather","provided","in","the","workspace","when","param_init_net","is","executed",".","Current","version","is","not","doing","any","real","sanity","checks","to","the","parameter","."]
code: def create_param(self, param_name, init_net, shape):
      if isinstance(param_name, BlobReference):
          param = BlobReference(str(param_name), init_net)
      elif isinstance(param_name, str):
          param = ScopedBlobReference(param_name, init_net)
      else:
          raise TypeError("Unsupported type for param_name")
      # TODO(amalevich): Add operator that will check param in the workspace
      return ParameterInfo(
          param_id=None,
          param=param,
          shape=shape,
      )
  
file_path: pytorch/caffe2/python/modeling/initializers.py
imports: from caffe2.python.core import DataType, BlobReference, ScopedBlobReference
  from caffe2.python.modeling.parameter_info import ParameterInfo
label_desc: Use image node_id 1 for calling the ExternalInitializer obj's underlying member method code with example usage: obj.create_param(param_name, init_net, shape) and returns: ParameterInfo