Sara bot Training fails on windows 10 ,python 3.6

I was trying to train rasa on windows 10 , python 3.6 with rasa 2.0.8 training stops after starting DIET Classifier Please help me resolve issue . I am stuck since two days

here are the logs . 2021-01-08 19:59:04 INFO rasa.nlu.model - Starting to train component DIETClassifier Traceback (most recent call last): File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\runpy.py”, line 193, in run_module_as_main “main”, mod_spec) File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\runpy.py”, line 85, in run_code exec(code, run_globals) File "C:\Users\KNI9KOR\Anaconda3\envs\rasabot\Scripts\rasa.exe_main.py", line 7, in File "c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\rasa_main.py", line 116, in main cmdline_arguments.func(cmdline_arguments) File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\rasa\cli\train.py”, line 90, in train nlu_additional_arguments=extract_nlu_additional_arguments(args), File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\rasa\train.py”, line 55, in train loop, File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\rasa\utils\common.py”, line 308, in run_in_loop result = loop.run_until_complete(f) File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\asyncio\base_events.py”, line 488, in run_until_complete return future.result() File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\rasa\train.py”, line 110, in train_async nlu_additional_arguments=nlu_additional_arguments, File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\rasa\train.py”, line 207, in _train_async_internal old_model_zip_path=old_model, File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\rasa\train.py”, line 246, in _do_training additional_arguments=nlu_additional_arguments, File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\rasa\train.py”, line 547, in _train_nlu_with_validated_data **additional_arguments, File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\rasa\nlu\train.py”, line 114, in train interpreter = trainer.train(training_data, **kwargs) File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\rasa\nlu\model.py”, line 206, in train updates = component.train(working_data, self.config, **context) File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\rasa\nlu\classifiers\diet_classifier.py”, line 760, in train self.model = self._instantiate_model_class(model_data) File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\rasa\nlu\classifiers\diet_classifier.py”, line 1086, in _instantiate_model_class config=self.component_config, File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\rasa\nlu\classifiers\diet_classifier.py”, line 1104, in init super().init(“DIET”, config, data_signature, label_data) File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\rasa\utils\tensorflow\models.py”, line 654, in init checkpoint_model=config[CHECKPOINT_MODEL], File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\rasa\utils\tensorflow\models.py”, line 83, in init super().init(**kwargs) File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\tensorflow\python\training\tracking\base.py”, line 457, in _method_wrapper result = method(self, *args, **kwargs) File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\tensorflow\python\keras\engine\training.py”, line 308, in init self._init_batch_counters() File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\tensorflow\python\training\tracking\base.py”, line 457, in _method_wrapper result = method(self, *args, **kwargs) File “c:\users\kni9kor\anaconda3\envs\rasabot\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 “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\tensorflow\python\ops\variables.py”, line 262, in call return cls._variable_v2_call(*args, **kwargs) File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\tensorflow\python\ops\variables.py”, line 256, in _variable_v2_call shape=shape) File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\tensorflow\python\ops\variables.py”, line 237, in previous_getter = lambda **kws: default_variable_creator_v2(None, **kws) File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\tensorflow\python\ops\variable_scope.py”, line 2646, in default_variable_creator_v2 shape=shape) File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\tensorflow\python\ops\variables.py”, line 264, in call return super(VariableMetaclass, cls).call(*args, **kwargs) File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py”, line 1518, in init distribute_strategy=distribute_strategy) File “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py”, line 1666, in _init_from_args graph_mode=self._in_graph_mode) File “c:\users\kni9kor\anaconda3\envs\rasabot\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 “c:\users\kni9kor\anaconda3\envs\rasabot\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 “c:\users\kni9kor\anaconda3\envs\rasabot\lib\site-packages\tensorflow\python\ops\gen_logging_ops.py”, line 49, in _assert _ops.raise_from_not_ok_status(e, name) File “c:\users\kni9kor\anaconda3\envs\rasabot\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 “”, line 3, in raise_from tensorflow.python.framework.errors_impl.InvalidArgumentError: assertion failed: [0] [Op:Assert] name: EagerVariableNameReuse