class_docstr: Base class of Crosstalk.
  Please refer to crosstalk unittests for examples of how to exchange/compare values between different toolkits.
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docstr: Set value to var, with option to load from working directory
  
  Args:
      name (`str`): Name of the variable to assign
      value : Numpy ndarray of dict of numpy ndarray data to assign to the variable
      load (`bool`): True to Load the data from working directory with the matching name, instead of using value. value has to be None when load=True
      load_name (`str`): None to load data with the same name, otherwise load with overrided load_name
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code: def assign(self, name, value=None, load=False, load_name=None):
      """
      Set value to var, with option to load from working directory
  
      Args:
          name (`str`): Name of the variable to assign
          value : Numpy ndarray of dict of numpy ndarray data to assign to the variable
          load (`bool`): True to Load the data from working directory with the matching name, instead of using value. value has to be None when load=True
          load_name (`str`): None to load data with the same name, otherwise load with overrided load_name
      """
      if load and value:
          raise Exception("assign can only have one source")
      var, var_type, attr = self.vars[name]
      if load:
          value = self.load_raw_value(load_name if load_name else name)
      else:
          old_value = self.fetch(name)
          if type(old_value) != type(value):
              raise Exception(
                  "cannot assign with different types: original {}, new {}".format(
                      type(old_value), type(value)
                  )
              )
      self.funcs[var_type].setter(var, value, attr)
  
imports: import os
  import pickle
  import numpy
  from collections import namedtuple
label_desc: Use image node_id 8 for calling the Crosstalk obj's underlying member method code with example usage: obj.assign(name, value, load, load_name) without return types