Skip to content

TypeError: Descriptors cannot be created directly. | Win11 #20

@LightC0de

Description

@LightC0de

Hello esteemed developer. Firstly, I'd like to express my gratitude for creating and maintaining this project. Thanks to individuals like you, OpenSource thrives!

I followed the instructions in the readme, but unfortunately, I still encountered an error.

My ENV
Win 11 x64 - Python 3.10 (from Microsoft Store).
FFmpeg, Espeak-NG, and MSVC Build Tools are installed.
My GPU is an Nvidia RTX 4070 Ti.

Steps to reproduce the error:

  1. git clone https://github.com/FlorianEagox/weeablind.git
  2. cd weeablind
  3. python3.10 -m venv venv
  4. .\venv\Scripts\activate
  5. pip install -r requirements-win-310.txt --no-deps
  6. python weeablind.py

Error in the console:

C:\Users\Danil\dev\weeablind\output\sample.wav
espeak [WinError 2] The system cannot find the file specified
espeakng [WinError 2] The system cannot find the file specified
torchvision is not available - cannot save figures
C:\Users\Danil\dev\weeablind\venv\lib\site-packages\pyannote\audio\core\io.py:43: UserWarning: torchaudio._backend.set_audio_backend has been deprecated. With dispatcher enabled, this function is no-op. You can remove the function call.
  torchaudio.set_audio_backend("soundfile")
2024-04-03 22:55:50.907235: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2024-04-03 22:55:50.907388: 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.
Traceback (most recent call last):
  File "C:\Users\Danil\dev\weeablind\weeablind.py", line 6, in <module>
    from tabs.ListStreams import ListStreamsTab
  File "C:\Users\Danil\dev\weeablind\tabs\ListStreams.py", line 3, in <module>
    import vocal_isolation
  File "C:\Users\Danil\dev\weeablind\vocal_isolation.py", line 4, in <module>
    from spleeter.separator import Separator
  File "C:\Users\Danil\dev\weeablind\venv\lib\site-packages\spleeter\separator.py", line 26, in <module>
    import tensorflow as tf  # type: ignore
  File "C:\Users\Danil\dev\weeablind\venv\lib\site-packages\tensorflow\__init__.py", line 37, in <module>
    from tensorflow.python.tools import module_util as _module_util
  File "C:\Users\Danil\dev\weeablind\venv\lib\site-packages\tensorflow\python\__init__.py", line 37, in <module>
    from tensorflow.python.eager import context
  File "C:\Users\Danil\dev\weeablind\venv\lib\site-packages\tensorflow\python\eager\context.py", line 29, in <module>
    from tensorflow.core.framework import function_pb2
  File "C:\Users\Danil\dev\weeablind\venv\lib\site-packages\tensorflow\core\framework\function_pb2.py", line 16, in <module>
    from tensorflow.core.framework import attr_value_pb2 as tensorflow_dot_core_dot_framework_dot_attr__value__pb2
  File "C:\Users\Danil\dev\weeablind\venv\lib\site-packages\tensorflow\core\framework\attr_value_pb2.py", line 16, in <module>
    from tensorflow.core.framework import tensor_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__pb2
  File "C:\Users\Danil\dev\weeablind\venv\lib\site-packages\tensorflow\core\framework\tensor_pb2.py", line 16, in <module>
    from tensorflow.core.framework import resource_handle_pb2 as tensorflow_dot_core_dot_framework_dot_resource__handle__pb2
  File "C:\Users\Danil\dev\weeablind\venv\lib\site-packages\tensorflow\core\framework\resource_handle_pb2.py", line 16, in <module>
    from tensorflow.core.framework import tensor_shape_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2
  File "C:\Users\Danil\dev\weeablind\venv\lib\site-packages\tensorflow\core\framework\tensor_shape_pb2.py", line 36, in <module>
    _descriptor.FieldDescriptor(
  File "C:\Users\Danil\dev\weeablind\venv\lib\site-packages\google\protobuf\descriptor.py", line 621, in __new__
    _message.Message._CheckCalledFromGeneratedFile()
TypeError: Descriptors cannot be created directly.
If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0.
If you cannot immediately regenerate your protos, some other possible workarounds are:
 1. Downgrade the protobuf package to 3.20.x or lower.
 2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower).

More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates

Please let me know how I could avoid such an error? Perhaps I did something wrong.

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions