class_docstr: This model mixes dtypes, making it un-flattenable.
class_docstr_tok: ["This","model","mixes","dtypes",",","making","it","un-flattenable","."]
code: def __init__(self):
      self._model = tfd.JointDistributionSequential(
          [
              tfd.Sample(tfd.Normal(0.0, 1.0), 3),
              tfd.Categorical([0.0, 0.0]),
          ]
      )
  
      super(TestBadModel, self).__init__(
          default_event_space_bijector=[tfb.Identity(), tfb.Identity()],
          event_shape=self._model.event_shape,
          dtype=self._model.dtype,
          name="test_bad_model",
          pretty_name="TestBadModel",
          sample_transformations={},
      )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  import tensorflow_probability
  from tensorflow_probability.python.internal import test_util
  from inference_gym import targets
  from inference_gym.internal import test_util
label_desc: Use image node_id 1 to create a new TestBadModel object from inherited base classes: targets with example: obj = TestBadModel()