I’m following all steps on windows 10 to install rasa, as described in the docs
I end up a bit frustrated with this error log
c:\Projects\rasa
(v00) λ rasa init
2021-03-19 16:25:15.647977: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll
2021-03-19 16:25:23.376028: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library nvcuda.dll
2021-03-19 16:25:23.887628: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce GTX 960M computeCapability: 5.0
coreClock: 1.176GHz coreCount: 5 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 74.65GiB/s
2021-03-19 16:25:23.887938: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll
2021-03-19 16:25:23.938980: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cublas64_10.dll
2021-03-19 16:25:23.983473: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cufft64_10.dll
2021-03-19 16:25:23.993417: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library curand64_10.dll
2021-03-19 16:25:24.051077: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusolver64_10.dll
2021-03-19 16:25:24.077288: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusparse64_10.dll
2021-03-19 16:25:24.188541: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudnn64_7.dll
2021-03-19 16:25:24.508893: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0
Welcome to Rasa! 🤖
To get started quickly, an initial project will be created.
If you need some help, check out the documentation at https://rasa.com/docs/rasa.
Now let's start! 👇🏽
? Please enter a path where the project will be created [default: current directory] 00
? Path '00' does not exist 🧐. Create path? Yes
Created project directory at 'c:\Projects\rasa\00'.
Finished creating project structure.
? Do you want to train an initial model? 💪🏽 Yes
Training an initial model...
The configuration for pipeline and policies was chosen automatically. It was written into the config file at '00\config.yml'.
Training NLU model...
c:\projects\rasa\v00\lib\site-packages\rasa\utils\train_utils.py:531: UserWarning: model_confidence is set to `softmax`. It is recommended to try using `model_confidence=linear_norm` to make it easier to tune fallback thresholds.
rasa.shared.utils.io.raise_warning(
2021-03-19 16:25:52 INFO rasa.shared.nlu.training_data.training_data - Training data stats:
2021-03-19 16:25:52 INFO rasa.shared.nlu.training_data.training_data - Number of intent examples: 69 (7 distinct intents)
2021-03-19 16:25:52 INFO rasa.shared.nlu.training_data.training_data - Found intents: 'greet', 'bot_challenge', 'goodbye', 'affirm', 'mood_great', 'mood_unhappy', 'deny'
2021-03-19 16:25:52 INFO rasa.shared.nlu.training_data.training_data - Number of response examples: 0 (0 distinct responses)
2021-03-19 16:25:52 INFO rasa.shared.nlu.training_data.training_data - Number of entity examples: 0 (0 distinct entities)
2021-03-19 16:25:52 INFO rasa.nlu.model - Starting to train component WhitespaceTokenizer
2021-03-19 16:25:52 INFO rasa.nlu.model - Finished training component.
2021-03-19 16:25:52 INFO rasa.nlu.model - Starting to train component RegexFeaturizer
2021-03-19 16:25:52 INFO rasa.nlu.model - Finished training component.
2021-03-19 16:25:52 INFO rasa.nlu.model - Starting to train component LexicalSyntacticFeaturizer
2021-03-19 16:25:52 INFO rasa.nlu.model - Finished training component.
2021-03-19 16:25:52 INFO rasa.nlu.model - Starting to train component CountVectorsFeaturizer
2021-03-19 16:25:52 INFO rasa.nlu.featurizers.sparse_featurizer.count_vectors_featurizer - 80 vocabulary slots consumed out of 1080 slots configured for text attribute.
2021-03-19 16:25:52 INFO rasa.nlu.model - Finished training component.
2021-03-19 16:25:52 INFO rasa.nlu.model - Starting to train component CountVectorsFeaturizer
2021-03-19 16:25:52 INFO rasa.nlu.featurizers.sparse_featurizer.count_vectors_featurizer - 697 vocabulary slots consumed out of 1697 slots configured for text attribute.
2021-03-19 16:25:52 INFO rasa.nlu.model - Finished training component.
2021-03-19 16:25:52 INFO rasa.nlu.model - Starting to train component DIETClassifier
2021-03-19 16:25:52.329695: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations: AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-03-19 16:25:52.345030: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x25190fd2e30 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2021-03-19 16:25:52.345314: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2021-03-19 16:25:52.751585: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce GTX 960M computeCapability: 5.0
coreClock: 1.176GHz coreCount: 5 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 74.65GiB/s
2021-03-19 16:25:52.752158: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll
2021-03-19 16:25:52.752365: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cublas64_10.dll
2021-03-19 16:25:52.752580: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cufft64_10.dll
2021-03-19 16:25:52.752919: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library curand64_10.dll
2021-03-19 16:25:52.753116: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusolver64_10.dll
2021-03-19 16:25:52.753301: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusparse64_10.dll
2021-03-19 16:25:52.753512: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudnn64_7.dll
2021-03-19 16:25:52.753857: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0
2021-03-19 16:25:52.921776: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1257] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-03-19 16:25:52.922077: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1263] 0
2021-03-19 16:25:52.922412: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1276] 0: N
2021-03-19 16:25:52.922984: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1402] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 3122 MB memory) -> physical GPU (device: 0, name: GeForce GTX 960M, pci bus id: 0000:01:00.0, compute capability: 5.0)
2021-03-19 16:25:52.930999: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x25190fd2fb0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2021-03-19 16:25:52.931313: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): GeForce GTX 960M, Compute Capability 5.0
Traceback (most recent call last):
File "C:\Python38\lib\runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "C:\Python38\lib\runpy.py", line 87, in _run_code
exec(code, run_globals)
File "c:\Projects\rasa\v00\Scripts\rasa.exe\__main__.py", line 7, in <module>
File "c:\projects\rasa\v00\lib\site-packages\rasa\__main__.py", line 116, in main
cmdline_arguments.func(cmdline_arguments)
File "c:\projects\rasa\v00\lib\site-packages\rasa\cli\scaffold.py", line 234, in run
init_project(args, path)
File "c:\projects\rasa\v00\lib\site-packages\rasa\cli\scaffold.py", line 129, in init_project
print_train_or_instructions(args, path)
File "c:\projects\rasa\v00\lib\site-packages\rasa\cli\scaffold.py", line 68, in print_train_or_instructions
training_result = rasa.train(domain, config, training_files, output)
File "c:\projects\rasa\v00\lib\site-packages\rasa\train.py", line 94, in train
return rasa.utils.common.run_in_loop(
File "c:\projects\rasa\v00\lib\site-packages\rasa\utils\common.py", line 307, in run_in_loop
result = loop.run_until_complete(f)
File "C:\Python38\lib\asyncio\base_events.py", line 616, in run_until_complete
return future.result()
File "c:\projects\rasa\v00\lib\site-packages\rasa\train.py", line 163, in train_async
return await _train_async_internal(
File "c:\projects\rasa\v00\lib\site-packages\rasa\train.py", line 342, in _train_async_internal
await _do_training(
File "c:\projects\rasa\v00\lib\site-packages\rasa\train.py", line 388, in _do_training
model_path = await _train_nlu_with_validated_data(
File "c:\projects\rasa\v00\lib\site-packages\rasa\train.py", line 812, in _train_nlu_with_validated_data
await rasa.nlu.train(
File "c:\projects\rasa\v00\lib\site-packages\rasa\nlu\train.py", line 115, in train
interpreter = trainer.train(training_data, **kwargs)
File "c:\projects\rasa\v00\lib\site-packages\rasa\nlu\model.py", line 209, in train
updates = component.train(working_data, self.config, **context)
File "c:\projects\rasa\v00\lib\site-packages\rasa\nlu\classifiers\diet_classifier.py", line 834, in train
self.model = self._instantiate_model_class(model_data)
File "c:\projects\rasa\v00\lib\site-packages\rasa\nlu\classifiers\diet_classifier.py", line 1174, in _instantiate_model_class
return self.model_class()(
File "c:\projects\rasa\v00\lib\site-packages\rasa\nlu\classifiers\diet_classifier.py", line 1192, in __init__
super().__init__("DIET", config, data_signature, label_data)
File "c:\projects\rasa\v00\lib\site-packages\rasa\utils\tensorflow\models.py", line 447, in __init__
super().__init__(
File "c:\projects\rasa\v00\lib\site-packages\rasa\utils\tensorflow\models.py", line 82, in __init__
super().__init__(**kwargs)
File "c:\projects\rasa\v00\lib\site-packages\tensorflow\python\training\tracking\base.py", line 457, in _method_wrapper
result = method(self, *args, **kwargs)
File "c:\projects\rasa\v00\lib\site-packages\tensorflow\python\keras\engine\training.py", line 308, in __init__
self._init_batch_counters()
File "c:\projects\rasa\v00\lib\site-packages\tensorflow\python\training\tracking\base.py", line 457, in _method_wrapper
result = method(self, *args, **kwargs)
File "c:\projects\rasa\v00\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:\projects\rasa\v00\lib\site-packages\tensorflow\python\ops\variables.py", line 262, in __call__
return cls._variable_v2_call(*args, **kwargs)
File "c:\projects\rasa\v00\lib\site-packages\tensorflow\python\ops\variables.py", line 244, in _variable_v2_call
return previous_getter(
File "c:\projects\rasa\v00\lib\site-packages\tensorflow\python\ops\variables.py", line 237, in <lambda>
previous_getter = lambda **kws: default_variable_creator_v2(None, **kws)
File "c:\projects\rasa\v00\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 2633, in default_variable_creator_v2
return resource_variable_ops.ResourceVariable(
File "c:\projects\rasa\v00\lib\site-packages\tensorflow\python\ops\variables.py", line 264, in __call__
return super(VariableMetaclass, cls).__call__(*args, **kwargs)
File "c:\projects\rasa\v00\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 1507, in __init__
self._init_from_args(
File "c:\projects\rasa\v00\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 1661, in _init_from_args
handle = eager_safe_variable_handle(
File "c:\projects\rasa\v00\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 242, in eager_safe_variable_handle
return _variable_handle_from_shape_and_dtype(
File "c:\projects\rasa\v00\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 174, in _variable_handle_from_shape_and_dtype
gen_logging_ops._assert( # pylint: disable=protected-access
File "c:\projects\rasa\v00\lib\site-packages\tensorflow\python\ops\gen_logging_ops.py", line 49, in _assert
_ops.raise_from_not_ok_status(e, name)
File "c:\projects\rasa\v00\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
c:\Projects\rasa
(v00) λ
Not sure how to go from here