(self)
Validates the input pipeline.

    Perform some sanity checks to log user friendly information. We should
    error out to give users better error message. But, if
    _WRAP_INPUT_FN_INTO_WHILE_LOOP is False (legacy behavior), we cannot break
    user code, so, log a warning.

    Raises:
      RuntimeError: If the validation failed.
Validates the input pipeline.
Validates the input pipeline .
def _validate_input_pipeline(self):
    """Validates the input pipeline.

    Perform some sanity checks to log user friendly information. We should
    error out to give users better error message. But, if
    _WRAP_INPUT_FN_INTO_WHILE_LOOP is False (legacy behavior), we cannot break
    user code, so, log a warning.

    Raises:
      RuntimeError: If the validation failed.
    """
    if ops.get_default_graph().get_collection(ops.GraphKeys.QUEUE_RUNNERS):
      err_msg = ('Input pipeline contains one or more QueueRunners. '
                 'It could be slow and not scalable. Please consider '
                 'converting your input pipeline to use `tf.data` instead (see '
                 'https://www.tensorflow.org/guide/datasets for '
                 'instructions.')
      if _WRAP_INPUT_FN_INTO_WHILE_LOOP:
        raise RuntimeError(err_msg)
      else:
        logging.warn(err_msg)
def _validate_input_pipeline ( self ) : if ops . get_default_graph ( ) . get_collection ( ops . GraphKeys . QUEUE_RUNNERS ) : err_msg = ( 'Input pipeline contains one or more QueueRunners. ' 'It could be slow and not scalable. Please consider ' 'converting your input pipeline to use `tf.data` instead (see ' 'https://www.tensorflow.org/guide/datasets for ' 'instructions.' ) if _WRAP_INPUT_FN_INTO_WHILE_LOOP : raise RuntimeError ( err_msg ) else : logging . warn ( err_msg )