class_docstr: Since tfd.Sample uses transposes, it requires a custom event bijector.
class_docstr_tok: ["Since","tfd.Sample","uses","transposes",",","it","requires","a","custom","event","bijector","."]
code: def _inverse_event_shape(self, shape):
      return self.bijector.inverse_event_shape(shape)
  
imports: import functools
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import log_prob_ratio
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import auto_composite_tensor
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.math import generic
label_desc: Use image node_id 4 for calling the _NonCompositeTensorDefaultSampleBijector obj's underlying member method code with example usage: obj._inverse_event_shape(shape) and returns: self