Model is not loading properly - Error: Python inputs incompatible with input_signature

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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      dtype=float32), FeatureArray([3.], dtype=float32)))
  input_signature: (
    [TensorSpec(shape=(None, None, 1), dtype=tf.float32, name=None), TensorSpec(shape=(None, 3), dtype=tf.int64, name=None), TensorSpec(shape=(None,), dtype=tf.float32, name=None), TensorSpec(shape=(None,), dtype=tf.int64, name=None), TensorSpec(shape=(None, None, 200), dtype=tf.float32, name=None), TensorSpec(shape=(None, 3), dtype=tf.int64, name=None), TensorSpec(shape=(None,), dtype=tf.float32, name=None), TensorSpec(shape=(None,), dtype=tf.int64, name=None), TensorSpec(shape=(None, None, 200), dtype=tf.float32, name=None), TensorSpec(shape=(None,), dtype=tf.float32, name=None)])

can you activate your environment and share the rasa --version, can you confirm with me at the time of installing rasa did you ignored any dependencies issues?

1 Like
(rasa38) [email protected]:~/projetos/pagnotr_rasa/$ rasa --version
2022-03-09 15:26:06.995292: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.10.1'; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory
2022-03-09 15:26:06.995318: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
Rasa Version     : 2.4.3
Rasa SDK Version : 2.4.1
Rasa X Version   : None
Python Version   : 3.8.8
Operating System : Linux-5.13.0-30-generic-x86_64-with-glibc2.10
Python Path      : /home/user/anaconda3/envs/rasa38/bin/python

I even looked here, but there was no problem installing Rasa.

I hope you are aware of this?

DEPRECATED IN 2.1

The HFTransformersNLP is deprecated and will be removed in 3.0. The LanguageModelFeaturizer now implements its behavior.

Ref: Components

OR

CHANGED IN 2.1

The default pre-trained weights for BERT have been renamed from bert-base-uncased to rasa/LaBSE.

OR

To use HFTransformersNLP component, install Rasa Open Source with pip3 install rasa[transformers] .

Good Luck! As I personally have not implemented this use case, I am just helping you and guiding you in the right direction. I hope you respect my concern.

1 Like

I didn’t know, thanks for letting me know!

But it should still work with those versions I’m running right? After all, on the server that was trained, it works. When I try to use it on my local machine it doesn’t… Very strange!

I tested it with rasa/LaBSE, but I got the same error.

It’s strange, I’d recommend deleting the environment and creating it again, and trying to follow the same requirements on which it’s working fine. I wish it will work.

1 Like

Wow, I just took this test and it worked!

To get documented,

My tests were:

Export the conda environment from the server to use locally

conda env export --name ENVNAME > envname.yml.

On the local machine

conda env create -f envname.yml

I was not successful like that.

I’m using the Pycharm IDE, I needed to create a new conda environment in python3.8 and I manually installed it in this sequence

pip install rasa==2.4.3

pip install -U spacy==2.3.5

python -m spacy download pt_core_news_lg

pip install transformers==2.11.0

Apparently it was some bug/conflict during the creation of the conda environments.