class_docstr: Raise error when layer argument is not yet supported in TFE.
  
  Args:
    arg: TFE layer argument
    arg_name: TFE layer argument name (string)
    tf_layer_name: Tensorflow keras layer name (string)
class_docstr_tok: ["Raise","error","when","layer","argument","is","not","yet","supported","in","TFE",".","Args",":","arg",":","TFE","layer","argument","arg_name",":","TFE","layer","argument","name","(","string",")","tf_layer_name",":","Tensorflow","keras","layer","name","(","string",")"]
code: def __init__(self, arg_name, tf_layer_name, tf_default_arg):
      super(LayerArgNotImplementedError, self).__init__()
      self.arg_name = arg_name
      self.tf_layer_name = tf_layer_name
      self.tf_default_arg = tf_default_arg
  
file_path: tf-encrypted/tf_encrypted/keras/layers/layers_utils.py
imports: import inspect
  import tensorflow
label_desc: Use image node_id 1 to create a new LayerArgNotImplementedError object from inherited base classes: NotImplementedError with example: obj = LayerArgNotImplementedError(arg_name, tf_layer_name, tf_default_arg)