class_docstr: Chooses between Keras v1 and v2 TensorBoard callback class.
code: def __new__(cls, *args, **kwargs):  # pylint: disable=unused-argument
      use_v2 = should_use_v2()
      start_cls = cls
      cls = swap_class(
          start_cls,
          callbacks.TensorBoard,
          callbacks_v1.TensorBoard,
          use_v2,
      )
      if (
          start_cls == callbacks_v1.TensorBoard
          and cls == callbacks.TensorBoard
      ):
          # Since the v2 class is not a subclass of the v1 class, __init__ has to
          # be called manually.
          return cls(*args, **kwargs)
      return super(TensorBoardVersionSelector, cls).__new__(cls)
  
file_path: tensorflow/tensorflow/python/keras/utils/version_utils.py
imports: from tensorflow.python.eager import context
  from tensorflow.python.framework import ops
  from tensorflow.python.keras.utils.generic_utils import LazyLoader
label_desc: Use image node_id 1 for calling the TensorBoardVersionSelector obj's underlying member method code with example usage: obj.__new__(cls) and returns: super, cls