code: def __init__(
      self,
      param_specs,
      non_tensor_params=None,
      omit_kwargs=(),
      prefer_static_value=(),
      non_identifying_kwargs=(),
      callable_params=None,
  ):
      non_tensor_params = (
          {} if non_tensor_params is None else non_tensor_params
      )
      super(_TestTypeSpec, self).__init__(
          param_specs,
          non_tensor_params=non_tensor_params,
          omit_kwargs=omit_kwargs,
          prefer_static_value=prefer_static_value,
          non_identifying_kwargs=non_identifying_kwargs,
          callable_params=callable_params,
      )
  
imports: import functools
  import os
  from absl import flags
  from absl.testing import parameterized
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.bijectors import reshape
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import shift
  from tensorflow_probability.python.bijectors import transform_diagonal
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.experimental.distributions import mvn_precision_factor_linop
  from tensorflow_probability.python.internal import auto_composite_tensor
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.internal import test_util
  from absl.testing import absltest
label_desc: Use image node_id 1 to create a new _TestTypeSpec object from inherited base classes: auto_composite_tensor with example: obj = _TestTypeSpec(param_specs, non_tensor_params, omit_kwargs, prefer_static_value, non_identifying_kwargs, callable_params)