docstr: Creates a test model.
  
  The defaults are 'correct', in that they correspond to the joint
  distribution defined herein. You can adjust them to make the model
  'incorrect' for testing purposes, e.g. an 'incorrect' `bijector` might not
  correctly constrain the values to the domain of the joint distribution. An
  'incorrect' `ground_truth_mean` is different from the true mean of the joint
  distribution.
  
  Args:
    bijector: Default event space bijector to use. Default: `tfb.Exp`.
    ground_truth_mean: What ground truth mean to use for the `'identity'`
      sample transformation.
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code: def __init__(self, bijector=None, ground_truth_mean=np.exp(1.5)):
      """Creates a test model.
  
      The defaults are 'correct', in that they correspond to the joint
      distribution defined herein. You can adjust them to make the model
      'incorrect' for testing purposes, e.g. an 'incorrect' `bijector` might not
      correctly constrain the values to the domain of the joint distribution. An
      'incorrect' `ground_truth_mean` is different from the true mean of the joint
      distribution.
  
      Args:
        bijector: Default event space bijector to use. Default: `tfb.Exp`.
        ground_truth_mean: What ground truth mean to use for the `'identity'`
          sample transformation.
      """
      self._distribution = tfd.LogNormal(1.0, 1.0)
  
      if bijector is None:
          bijector = tfb.Exp()
  
      super(TestModel, self).__init__(
          default_event_space_bijector=bijector,
          event_shape=self._distribution.event_shape,
          dtype=self._distribution.dtype,
          name="test_model",
          pretty_name="TestModel",
          sample_transformations=dict(
              identity=targets.Model.SampleTransformation(
                  fn=lambda x: x,
                  pretty_name="Identity",
                  ground_truth_mean=ground_truth_mean,
              ),
          ),
      )
  
imports: import atexit
  import functools
  from absl import logging
  import jax
  import numpy
  import tensorflow.compat.v2
  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 TestModel object from inherited base classes: targets with example: obj = TestModel(bijector, ground_truth_mean)