docstr: Returns a `_Blockwise` if any of `bijectors` is not `CompositeTensor.
docstr_tok: ["Returns","a","`","_Blockwise","`","if","any","of","`","bijectors","`","is","not","`","CompositeTensor","."]
code: def __new__(cls, *args, **kwargs):
      """Returns a `_Blockwise` if any of `bijectors` is not `CompositeTensor."""
      if cls is Blockwise:
          if args:
              bijectors = args[0]
          elif "bijectors" in kwargs:
              bijectors = kwargs["bijectors"]
          else:
              raise TypeError(
                  "`Blockwise.__new__()` is missing argument `bijectors`."
              )
  
          if not all(
              auto_composite_tensor.is_composite_tensor(b)
              for b in bijectors
          ):
              return _Blockwise(*args, **kwargs)
      return super(Blockwise, cls).__new__(cls)
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.bijectors import chain
  from tensorflow_probability.python.bijectors import composition
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import joint_map
  from tensorflow_probability.python.bijectors import split
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import auto_composite_tensor
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow.python.util import nest
label_desc: Use image node_id 1 for calling the Blockwise obj's underlying member method code with example usage: obj.__new__(cls) and returns: super, _Blockwise