EagerVariableNameReuse初始化错误:断言失败：[0] [Op:Assert]名称: RASA

Question

我是rasa的新手。我在我的windows10，python 3.7.6机器上安装了rasa 2.4.1，没有任何错误。但是当我初始化rasa项目时，我得到了以下错误。我尝试了多个rasa2.x版本和多个tensorflow安装。但没那么走运。任何帮助解决这个问题的人都将不胜感激。

File "D:\NLP\rasa_env\Scripts\rasa.exe\__main__.py", line 7, in <module>
  File "d:\nlp\rasa_env\lib\site-packages\rasa\__main__.py", line 116, in main
    cmdline_arguments.func(cmdline_arguments)
  File "d:\nlp\rasa_env\lib\site-packages\rasa\cli\scaffold.py", line 234, in run
    init_project(args, path)
  File "d:\nlp\rasa_env\lib\site-packages\rasa\cli\scaffold.py", line 129, in init_project
    print_train_or_instructions(args, path)
  File "d:\nlp\rasa_env\lib\site-packages\rasa\cli\scaffold.py", line 68, in print_train_or_instructions
    training_result = rasa.train(domain, config, training_files, output)
  File "d:\nlp\rasa_env\lib\site-packages\rasa\train.py", line 109, in train
    loop,
  File "d:\nlp\rasa_env\lib\site-packages\rasa\utils\common.py", line 308, in run_in_loop
    result = loop.run_until_complete(f)
  File "c:\users\kni9kor\anaconda3\lib\asyncio\base_events.py", line 583, in run_until_complete
    return future.result()
  File "d:\nlp\rasa_env\lib\site-packages\rasa\train.py", line 174, in train_async
    finetuning_epoch_fraction=finetuning_epoch_fraction,
  File "d:\nlp\rasa_env\lib\site-packages\rasa\train.py", line 353, in _train_async_internal
    finetuning_epoch_fraction=finetuning_epoch_fraction,
  File "d:\nlp\rasa_env\lib\site-packages\rasa\train.py", line 396, in _do_training
    finetuning_epoch_fraction=finetuning_epoch_fraction,
  File "d:\nlp\rasa_env\lib\site-packages\rasa\train.py", line 818, in _train_nlu_with_validated_data
    **additional_arguments,
  File "d:\nlp\rasa_env\lib\site-packages\rasa\nlu\train.py", line 116, in train
    interpreter = trainer.train(training_data, **kwargs)
  File "d:\nlp\rasa_env\lib\site-packages\rasa\nlu\model.py", line 209, in train
    updates = component.train(working_data, self.config, **context)
  File "d:\nlp\rasa_env\lib\site-packages\rasa\nlu\classifiers\diet_classifier.py", line 810, in train
    self.model = self._instantiate_model_class(model_data)
  File "d:\nlp\rasa_env\lib\site-packages\rasa\nlu\classifiers\diet_classifier.py", line 1132, in _instantiate_model_class
    config=self.component_config,
  File "d:\nlp\rasa_env\lib\site-packages\rasa\nlu\classifiers\diet_classifier.py", line 1146, in __init__
    super().__init__("DIET", config, data_signature, label_data)
  File "d:\nlp\rasa_env\lib\site-packages\rasa\utils\tensorflow\models.py", line 705, in __init__
    checkpoint_model=config[CHECKPOINT_MODEL],
  File "d:\nlp\rasa_env\lib\site-packages\rasa\utils\tensorflow\models.py", line 91, in __init__
    super().__init__(**kwargs)
  File "d:\nlp\rasa_env\lib\site-packages\tensorflow\python\training\tracking\base.py", line 457, in _method_wrapper
    result = method(self, *args, **kwargs)
  File "d:\nlp\rasa_env\lib\site-packages\tensorflow\python\keras\engine\training.py", line 308, in __init__
    self._init_batch_counters()
  File "d:\nlp\rasa_env\lib\site-packages\tensorflow\python\training\tracking\base.py", line 457, in _method_wrapper
    result = method(self, *args, **kwargs)
  File "d:\nlp\rasa_env\lib\site-packages\tensorflow\python\keras\engine\training.py", line 317, in _init_batch_counters
    self._train_counter = variables.Variable(0, dtype='int64', aggregation=agg)
  File "d:\nlp\rasa_env\lib\site-packages\tensorflow\python\ops\variables.py", line 262, in __call__
    return cls._variable_v2_call(*args, **kwargs)
  File "d:\nlp\rasa_env\lib\site-packages\tensorflow\python\ops\variables.py", line 256, in _variable_v2_call
    shape=shape)
  File "d:\nlp\rasa_env\lib\site-packages\tensorflow\python\ops\variables.py", line 237, in <lambda>
    previous_getter = lambda **kws: default_variable_creator_v2(None, **kws)
  File "d:\nlp\rasa_env\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 2646, in default_variable_creator_v2
    shape=shape)
  File "d:\nlp\rasa_env\lib\site-packages\tensorflow\python\ops\variables.py", line 264, in __call__
    return super(VariableMetaclass, cls).__call__(*args, **kwargs)
  File "d:\nlp\rasa_env\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 1518, in __init__
    distribute_strategy=distribute_strategy)
  File "d:\nlp\rasa_env\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 1666, in _init_from_args
    graph_mode=self._in_graph_mode)
  File "d:\nlp\rasa_env\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 243, in eager_safe_variable_handle
    shape, dtype, shared_name, name, graph_mode, initial_value)
  File "d:\nlp\rasa_env\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 175, in _variable_handle_from_shape_and_dtype
    math_ops.logical_not(exists), [exists], name="EagerVariableNameReuse")
  File "d:\nlp\rasa_env\lib\site-packages\tensorflow\python\ops\gen_logging_ops.py", line 49, in _assert
    _ops.raise_from_not_ok_status(e, name)
  File "d:\nlp\rasa_env\lib\site-packages\tensorflow\python\framework\ops.py", line 6843, in raise_from_not_ok_status
    six.raise_from(core._status_to_exception(e.code, message), None)
  File "<string>", line 3, in raise_from
tensorflow.python.framework.errors_impl.InvalidArgumentError: assertion failed: [0] [Op:Assert] name: EagerVariableNameReuse

Answer 1

可能的解决方案：

1.终止同时尝试访问Tensorflow的并发python程序(如Jupyter notebooks)。

2.将环境变量TF_FORCE_GPU_ALLOW_GROWTH设置为true似乎可以消除此问题: import os os.environ‘’TF_FORCE_GPU_ALLOW_GROWTH‘= "true“

我还附上了以下类似的问题作为参考，这可能会对你有所帮助。link1、link2、link3