class_docstr: Only used for op_ndims manipulation.
code: def __init__(
      self, forward_min_event_ndims=0, inverse_min_event_ndims=3
  ):
      super(ShapeChanging, self).__init__(
          forward_min_event_ndims=forward_min_event_ndims,
          inverse_min_event_ndims=inverse_min_event_ndims,
          validate_args=False,
          name="shape_changer",
      )
  
imports: import mock
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import chain
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import inline
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import joint_map
  from tensorflow_probability.python.bijectors import restructure
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import scale_matvec_diag
  from tensorflow_probability.python.bijectors import softmax_centered
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.bijectors import split
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 1 to create a new ShapeChanging object from inherited base classes: bijector_lib with example: obj = ShapeChanging(forward_min_event_ndims, inverse_min_event_ndims)