Traceback (most recent call last):


 "/usr/local/bin/onmt-main", line 10, in <module>

sys.exit(main())


 "/usr/local/lib/python3.5/dist-packages/opennmt/bin/main.py", line 172, in main

runner.train_and_evaluate(checkpoint_path=args.checkpoint_path)


 "/usr/local/lib/python3.5/dist-packages/opennmt/runner.py", line 297, in train_and_evaluate

result = tf.estimator.train_and_evaluate(estimator, train_spec, eval_spec)


 "/usr/local/lib/python3.5/dist-packages/tensorflow_estimator/python/estimator/training.py", line 473, in train_and_evaluate

return executor.run()


 "/usr/local/lib/python3.5/dist-packages/tensorflow_estimator/python/estimator/training.py", line 613, in run

return self.run_local()


 "/usr/local/lib/python3.5/dist-packages/tensorflow_estimator/python/estimator/training.py", line 714, in run_local

saving_listeners=saving_listeners)


 "/usr/local/lib/python3.5/dist-packages/tensorflow_estimator/python/estimator/estimator.py", line 360, in train

loss = self._train_model(input_fn, hooks, saving_listeners)


 "/usr/local/lib/python3.5/dist-packages/tensorflow_estimator/python/estimator/estimator.py", line 1140, in _train_model

return self._train_model_default(input_fn, hooks, saving_listeners)


 "/usr/local/lib/python3.5/dist-packages/tensorflow_estimator/python/estimator/estimator.py", line 1167, in _train_model_default

input_fn, ModeKeys.TRAIN))


 "/usr/local/lib/python3.5/dist-packages/tensorflow_estimator/python/estimator/estimator.py", line 1004, in _get_features_and_labels_from_input_fn

self._call_input_fn(input_fn, mode))


 "/usr/local/lib/python3.5/dist-packages/tensorflow_estimator/python/estimator/estimator.py", line 1095, in _call_input_fn

return input_fn(**kwargs)


 "/usr/local/lib/python3.5/dist-packages/opennmt/estimator.py", line 124, in _fn

prefetch_buffer_size=prefetch_buffer_size)


 "/usr/local/lib/python3.5/dist-packages/opennmt/inputters/inputter.py", line 685, in make_training_dataset

shard_index=shard_index)


 "/usr/local/lib/python3.5/dist-packages/opennmt/utils/data.py", line 311, in training_pipeline

batch_size_multiple=batch_size_multiple))


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 1746, in apply

return DatasetV1Adapter(super(DatasetV1, self).apply(transformation_func))


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 1190, in apply

dataset = transformation_func(self)


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/data/experimental/ops/grouping.py", line 121, in _apply_fn

window_size_func)


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/data/experimental/ops/grouping.py", line 377, in __init__

self._make_reduce_func(reduce_func, input_dataset)


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/data/experimental/ops/grouping.py", line 424, in _make_reduce_func

input_structure=input_structure)


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 2400, in __init__

self._function = wrapper_fn._get_concrete_function_internal()


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/eager/function.py", line 1330, in _get_concrete_function_internal

*args, **kwargs)


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/eager/function.py", line 1324, in _get_concrete_function_internal_garbage_collected

graph_function, _, _ = self._maybe_define_function(args, kwargs)


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/eager/function.py", line 1587, in _maybe_define_function

graph_function = self._create_graph_function(args, kwargs)


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/eager/function.py", line 1520, in _create_graph_function

capture_by_value=self._capture_by_value),


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/func_graph.py", line 701, in func_graph_from_py_func

func_outputs = python_func(*func_args, **func_kwargs)


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 2394, in wrapper_fn

ret = _wrapper_helper(*args)


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 2334, in _wrapper_helper

ret = func(*nested_args)


 "/usr/local/lib/python3.5/dist-packages/opennmt/utils/data.py", line 203, in _reduce_func

return dataset.apply(batch_dataset(batch_size, padded_shapes=padded_shapes))


 "/usr/local/lib/python3.5/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 1190, in apply

dataset = transformation_func(self)


 "/usr/local/lib/python3.5/dist-packages/opennmt/utils/data.py", line 143, in <lambda>

batch_size, padded_shapes=padded_shapes or get_padded_shapes(dataset))


 "/usr/local/lib/python3.5/dist-packages/opennmt/utils/data.py", line 22, in get_padded_shapes

return compat.nest.map_structure(lambda shape: shape.as_list(), dataset.output_shapes)
AttributeError: '_VariantDataset' object has no attribute 'output_shapes'

Traceback (most recent call last):


 "D:\tools\XX-Net-3.7.9\code\default\python27\1.0\lib\threading.py", line 801, in __bootstrap_inner

self.run()


 "D:\tools\XX-Net-3.7.9\code\default\python27\1.0\lib\threading.py", line 754, in run

self.__target(*self.__args, **self.__kwargs)


 "D:\tools\XX-Net-3.7.9\code\default\gae_proxy\local\google_ip.py", line 652, in scan_ip_worker

xlog.exception("google_ip.runJob fail:%r", e)
AttributeError: 'NoneType' object has no attribute 'exception'
