TypeError: AutomaticSpeechRecognitionPipeline._sanitize_parameters() got an unexpected keyword argument 'use_auth_token'

[utility-aagrawal]

Getting the following error while trying to run the sample ASR diarization code.

Created a fresh python virtual environment and installed speechbox, transformers and pyannote (as suggested in the readme document). Can you advise what's wrong? Thank you!

[utility-aagrawal]

Here's the list of packages in the virtual environment for your reference -

$ pip freeze absl-py==1.4.0 aiohttp==3.8.5 aiosignal==1.3.1 alembic==1.11.3 antlr4-python3-runtime==4.9.3 asteroid-filterbanks==0.4.0 async-timeout==4.0.3 attrs==23.1.0 audioread==3.0.0 backports.cached-property==1.0.2 cachetools==5.3.1 certifi==2023.7.22 cffi==1.15.1 charset-normalizer==3.2.0 click==8.1.7 cmaes==0.10.0 cmake==3.27.2 colorama==0.4.6 colorlog==6.7.0 contourpy==1.1.0 cycler==0.11.0 datasets==2.14.4 decorator==5.1.1 dill==0.3.7 docopt==0.6.2 einops==0.3.2 filelock==3.12.2 fonttools==4.42.1 frozenlist==1.4.0 fsspec==2023.6.0 google-auth==2.22.0 google-auth-oauthlib==1.0.0 greenlet==2.0.2 grpcio==1.57.0 hmmlearn==0.2.8 huggingface-hub==0.16.4 HyperPyYAML==1.2.1 idna==3.4 importlib-metadata==6.8.0 Jinja2==3.1.2 joblib==1.3.2 julius==0.2.7 kiwisolver==1.4.4 librosa==0.9.2 lit==16.0.6 llvmlite==0.40.1 Mako==1.2.4 Markdown==3.4.4 markdown-it-py==3.0.0 MarkupSafe==2.1.3 matplotlib==3.7.2 mdurl==0.1.2 mpmath==1.3.0 multidict==6.0.4 multiprocess==0.70.15 networkx==2.8.8 numba==0.57.1 numpy==1.24.4 nvidia-cublas-cu11==11.10.3.66 nvidia-cuda-cupti-cu11==11.7.101 nvidia-cuda-nvrtc-cu11==11.7.99 nvidia-cuda-runtime-cu11==11.7.99 nvidia-cudnn-cu11==8.5.0.96 nvidia-cufft-cu11==10.9.0.58 nvidia-curand-cu11==10.2.10.91 nvidia-cusolver-cu11==11.4.0.1 nvidia-cusparse-cu11==11.7.4.91 nvidia-nccl-cu11==2.14.3 nvidia-nvtx-cu11==11.7.91 oauthlib==3.2.2 omegaconf==2.3.0 optuna==3.3.0 packaging==23.1 pandas==2.0.3 Pillow==10.0.0 pipdeptree==2.13.0 platformdirs==3.10.0 pooch==1.7.0 primePy==1.3 protobuf==3.20.1 pyannote.audio==2.1.1 pyannote.core==4.5 pyannote.database==4.1.3 pyannote.metrics==3.2.1 pyannote.pipeline==2.3 pyarrow==12.0.1 pyasn1==0.5.0 pyasn1-modules==0.3.0 pycparser==2.21 pyDeprecate==0.3.2 Pygments==2.16.1 pyparsing==3.0.9 python-dateutil==2.8.2 pytorch-lightning==1.6.5 pytorch-metric-learning==1.7.3 pytz==2023.3 PyYAML==6.0.1 regex==2023.8.8 requests==2.31.0 requests-oauthlib==1.3.1 resampy==0.4.2 rich==13.5.2 rsa==4.9 ruamel.yaml==0.17.28 ruamel.yaml.clib==0.2.7 safetensors==0.3.2 scikit-learn==1.3.0 scipy==1.11.2 semver==2.13.0 sentencepiece==0.1.99 shellingham==1.5.3 simplejson==3.19.1 singledispatchmethod==1.0 six==1.16.0 sortedcontainers==2.4.0 SoundFile==0.10.3.post1 speechbox==0.2.1 speechbrain==0.5.15 SQLAlchemy==2.0.20 sympy==1.12 tabulate==0.9.0 tensorboard==2.14.0 tensorboard-data-server==0.7.1 threadpoolctl==3.2.0 tokenizers==0.13.3 torch==1.13.1 torch-audiomentations==0.11.0 torch-pitch-shift==1.2.4 torchaudio==0.13.1 torchmetrics==0.11.4 tqdm==4.66.1 transformers==4.32.0 triton==2.0.0 typer==0.9.0 typing_extensions==4.7.1 tzdata==2023.3 urllib3==1.26.16 Werkzeug==2.3.7 xxhash==3.3.0 yarl==1.9.2 zipp==3.16.2

[utility-aagrawal]

I was able to resolve it. I had the latest transformers release 4.32.0 and they must have changed the argument name from use_auth_token to token at some point (See here - https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.pipeline)

I had to make that change in the file diarize.py and it worked! Let me know what you think about this temporary resolution. Thanks!

[sanchit-gandhi]

Thanks @utility-aagrawal - would you like to open a PR to fix this on main?

[utility-aagrawal]

Thanks for your response, @sanchit-gandhi! Sure, I can do that.

[utility-aagrawal]

Added specific kwargs for ASR and diarization pipelines. Closing the issue. Let me know in case of any questions. Thanks!