code: def test_gen_cloning_with_shape_change(self, datagen):
      gen = pm.generator(datagen)
      gen_r = pt.random.normal(size=gen.shape).T
      X = gen.dot(gen_r)
      res, _ = pytensor.scan(lambda x: x.sum(), X, n_steps=X.shape[0])
      assert res.eval().shape == (50,)
      shared = pytensor.shared(datagen.data.astype(gen.dtype))
      res2 = pytensor.clone_replace(res, {gen: shared**2})
      assert res2.eval().shape == (1000,)
  
imports: import io
  import itertools
  import re
  import cloudpickle
  import numpy
  import pytensor
  import pytensor.tensor
  import pytest
  from pytensor import shared
  from pytensor.tensor.variable import TensorVariable
  import pymc
  from pymc.data import is_minibatch
  from pymc.pytensorf import GeneratorOp, floatX
label_desc: Use image node_id 7 for calling the TestGenerator obj's underlying member method code with example usage: obj.test_gen_cloning_with_shape_change(datagen) without return types