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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def reinit_nested_vars(variables, indices=None):
 """Reset all variables in a nested tuple to zeros. Args: variables: Nested tuple or list of variables. indices: Batch indices to reset, defaults to all. Returns: Operation. """

  if isinstance(variables, (tuple, list)):
    return tf.group(*[
        reinit_nested_vars(variable, indices) for variable in variables])
  if indices is None:
    return variables.assign(tf.zeros_like(variables))
  else:
    zeros = tf.zeros([tf.shape(indices)[0]] + variables.shape[1:].as_list())
    return tf.scatter_update(variables, indices, zeros)