I did the rasa training, on a server with the following configurations.
PC settings: Ubuntu 18.04.5 LTS
My config
language: "pt"
pipeline:
- name: "HFTransformersNLP"
model_name: "bert"
model_weights: "bert-base-multilingual-cased"
cache_dir: "bert_cache"
- name: "SpacyNLP"
model: "pa_lang_model_infix"
- name: "SpacyTokenizer"
- name: "SpacyFeaturizer"
- name: "DIETClassifier"
epochs: 100
random_seed: 42
embedding_dimension: 30
tensorboard_log_directory: "./tensorboard/ed30/"
tensorboard_log_level: "epoch"
regularization_constant: 0.02
batch_strategy: "balanced"
checkpoint_model: true
- name: "EntitySynonymMapper"
- name: FallbackClassifier
threshold: 0.6
policies:
- name: MemoizationPolicy
- name: TEDPolicy
max_history: 5
epochs: 100
- name: RulePolicy
I installed anaconda3 and installed the dependencies in a conda python3.8 environment rasa==2.4.3 spacy==2.3.5 transformers==2.11.0 tensorflow==2.3.1
Here on the server everything works fine, both the rasa shell, the API and the inference.
Now when I’m going to try to use the template on my local machine, which is an Ubuntu 20.04.3 LTS, I installed the same virtual environment on my machine with the proper versions, but after running “rasa shell -m ./trained_model/” and sending a message, I get this error:
NLU model loaded. Type a message and press enter to parse it.
Next message:
"hello"
Traceback (most recent call last):
File "/home/user/anaconda3/envs/rasa38/bin/rasa", line 8, in <module>
sys.exit(main())
File "/home/user/anaconda3/envs/rasa38/lib/python3.8/site-packages/rasa/__main__.py", line 116, in main
cmdline_arguments.func(cmdline_arguments)
File "/home/user/anaconda3/envs/rasa38/lib/python3.8/site-packages/rasa/cli/shell.py", line 117, in shell
rasa.nlu.run.run_cmdline(nlu_model)
File "/home/user/anaconda3/envs/rasa38/lib/python3.8/site-packages/rasa/nlu/run.py", line 36, in run_cmdline
result = interpreter.parse(message)
File "/home/user/anaconda3/envs/rasa38/lib/python3.8/site-packages/rasa/nlu/model.py", line 453, in parse
component.process(message, **self.context)
File "/home/user/anaconda3/envs/rasa38/lib/python3.8/site-packages/rasa/nlu/classifiers/diet_classifier.py", line 963, in process
out = self._predict(message)
File "/home/user/anaconda3/envs/rasa38/lib/python3.8/site-packages/rasa/nlu/classifiers/diet_classifier.py", line 878, in _predict
return self.model.rasa_predict(model_data)
File "/home/user/anaconda3/envs/rasa38/lib/python3.8/site-packages/rasa/utils/tensorflow/models.py", line 270, in rasa_predict
return tf_utils.to_numpy_or_python_type(self._tf_predict_step(batch_in))
File "/home/user/anaconda3/envs/rasa38/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 780, in __call__
result = self._call(*args, **kwds)
File "/home/user/anaconda3/envs/rasa38/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 814, in _call
results = self._stateful_fn(*args, **kwds)
File "/home/user/anaconda3/envs/rasa38/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 2828, in __call__
graph_function, args, kwargs = self._maybe_define_function(args, kwargs)
File "/home/user/anaconda3/envs/rasa38/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3170, in _maybe_define_function
args, kwargs = self._function_spec.canonicalize_function_inputs(
File "/home/user/anaconda3/envs/rasa38/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 2619, in canonicalize_function_inputs
inputs = _convert_inputs_to_signature(
File "/home/user/anaconda3/envs/rasa38/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 2712, in _convert_inputs_to_signature
raise ValueError("Python inputs incompatible with input_signature:\n%s" %
ValueError: Python inputs incompatible with input_signature:
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