docstr: Returns a `_JointDistributionSequential` if `model` has non-CT dists.
docstr_tok: ["Returns","a","`","_JointDistributionSequential","`","if","`","model","`","has","non-CT","dists","."]
code: def __new__(cls, *args, **kwargs):
      """Returns a `_JointDistributionSequential` if `model` has non-CT dists."""
      if cls is JointDistributionSequential:
          if args:
              model = args[0]
          else:
              model = kwargs.get("model")
  
          if not all(
              auto_composite_tensor.is_composite_tensor(d)
              or callable(d)
              for d in model
          ):
              return _JointDistributionSequential(*args, **kwargs)
      return super(JointDistributionSequential, cls).__new__(cls)
  
imports: import collections
  import functools
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import joint_distribution
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import auto_composite_tensor
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow.python.util import tf_inspect
label_desc: Use image node_id 1 for calling the JointDistributionSequential obj's underlying member method code with example usage: obj.__new__(cls) and returns: super, _JointDistributionSequential