class_docstr: Has a sample transform that mixes dtypes, making it un-flattenable.
class_docstr_tok: ["Has","a","sample","transform","that","mixes","dtypes",",","making","it","un-flattenable","."]
code: def __init__(self):
      self._model = tfd.CholeskyLKJ(dimension=3, concentration=1.0)
  
      super(TestBadSampleTransformationModel, self).__init__(
          default_event_space_bijector=tfb.CorrelationCholesky(),
          event_shape=self._model.event_shape,
          dtype=self._model.dtype,
          name="test_bad_sample_transformation_model",
          pretty_name="TestBadSampleTransformationModel",
          sample_transformations=dict(
              bad=targets.Model.SampleTransformation(
                  fn=lambda x: (x, tf.cast(x, tf.float64)),
                  pretty_name="Bad",
                  dtype=(tf.float32, tf.float64),
              ),
          ),
      )
  
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 TestBadSampleTransformationModel object from inherited base classes: targets with example: obj = TestBadSampleTransformationModel()