Error log appeared when running command "rasa shell"

Rasa Open Source
1

I am trying to create a project and test it with the command “rasa shell”. But during the execution, I got an error message. Here is the error log:

    2021-02-24 20:53:11.112484: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
    2021-02-24 20:53:11.112593: 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.
    2021-02-24 20:53:13 INFO     root  - Connecting to channel 'cmdline' which was specified by the '--connector' argument. Any other channels will be ignored. To connect to all given channels, omit the '--connector' argument.
    2021-02-24 20:53:13 INFO     root  - Starting Rasa server on http://localhost:5005
    c:\users\phucnb\anaconda3\envs\chatbot2\lib\site-packages\sklearn\externals\joblib\__init__.py:15: FutureWarning: sklearn.externals.joblib is deprecated in 0.21 and will be removed in 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib. If this warning is raised when loading pickled models, you may need to re-serialize those models with scikit-learn 0.21+.
      warnings.warn(msg, category=FutureWarning)
    c:\users\phucnb\anaconda3\envs\chatbot2\lib\site-packages\rasa\utils\common.py:347: UserWarning: 'CRFEntityExtractor' is deprecated and will be removed in version 2.0. Use 'DIETClassifier' instead.
      More info at https://rasa.com/docs/rasa/migration-guide/
    2021-02-24 20:53:14.374746: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
    2021-02-24 20:53:15.393585: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
    pciBusID: 0000:01:00.0 name: GeForce GTX 1050 computeCapability: 6.1
    coreClock: 1.493GHz coreCount: 5 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 104.43GiB/s
    2021-02-24 20:53:15.394525: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
    2021-02-24 20:53:15.395876: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cublas64_10.dll'; dlerror: cublas64_10.dll not found
    2021-02-24 20:53:15.398446: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cufft64_10.dll'; dlerror: cufft64_10.dll not found
    2021-02-24 20:53:15.399325: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'curand64_10.dll'; dlerror: curand64_10.dll not found
    2021-02-24 20:53:15.400140: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cusolver64_10.dll'; dlerror: cusolver64_10.dll not found
    2021-02-24 20:53:15.401014: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cusparse64_10.dll'; dlerror: cusparse64_10.dll not found
    2021-02-24 20:53:15.401837: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cudnn64_7.dll'; dlerror: cudnn64_7.dll not found
    2021-02-24 20:53:15.401948: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1592] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
    Skipping registering GPU devices...
    2021-02-24 20:53:15.402726: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
    2021-02-24 20:53:15.403252: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix:
    2021-02-24 20:53:15.403337: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102]
    2021-02-24 20:53:15.651578: W tensorflow/core/kernels/data/generator_dataset_op.cc:103] Error occurred when finalizing GeneratorDataset iterator: Cancelled: Operation was cancelled
    c:\users\phucnb\anaconda3\envs\chatbot2\lib\site-packages\rasa\nlu\classifiers\diet_classifier.py:852: FutureWarning: 'EmbeddingIntentClassifier' is deprecated and will be removed in version 2.0. Use 'DIETClassifier' instead.
      model=model,
    c:\users\phucnb\anaconda3\envs\chatbot2\lib\site-packages\rasa\core\policies\keras_policy.py:265: FutureWarning: 'KerasPolicy' is deprecated and will be removed in version 2.0. Use 'TEDPolicy' instead.
      current_epoch=meta["epochs"],
    Bot loaded. Type a message and press enter (use '/stop' to exit):

Every time I talk to a bot. There is a message attached like this:

2021-02-24 21:04:22.474926: W tensorflow/core/kernels/data/generator_dataset_op.cc:103] Error occurred when finalizing GeneratorDataset iterator: Cancelled: Operation was cancelled

Does this have any effect on training and running the bot? How do I solve this problem?

2

Hi @baphuc1998 ,

in the future it would be most helpful if you use backticks to wrap logs/code using Markdown syntax. That way the output looks;

like this

That said, let’s have a look at your logs. Are you seeing warnings (this is not ideal, but your program doesn’t crash) or are you seeing errors (the program crashes)?

3

I’m not sure. But I think it’s an error. My program keeps running but that message still appears every time I reply to my bot

4

Could you share the text that is exchanged back and forth?

5

After I upgrade Rasa version the above message (Error occurred when finalizing…) no longer appears. Even when I send and receive messages with bot. But I don’t understand why the execution time of the rasa train command took longer than before. Time to complete 100 Epochs takes a few minutes (instead of a few seconds as before). Version:

  • The old version I used: 1.8.0
  • The version after upgrade: 2.3.2