---------------------------------------------------------------------------
OSError Traceback (most recent call last)
Cell In[9], line 4
2 import time
3 import torch
----> 4 import torchaudio
5 from transformers import pipeline
6 from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor
File /opt/conda/lib/python3.10/site-packages/torchaudio/__init__.py:1
----> 1 from . import ( # noqa: F401
2 _extension,
3 compliance,
4 datasets,
5 functional,
6 io,
7 kaldi_io,
8 models,
9 pipelines,
10 sox_effects,
11 transforms,
12 utils,
13 )
14 from ._backend.common import AudioMetaData # noqa
16 try:
File /opt/conda/lib/python3.10/site-packages/torchaudio/_extension/__init__.py:45
43 _IS_ALIGN_AVAILABLE = False
44 if _IS_TORCHAUDIO_EXT_AVAILABLE:
---> 45 _load_lib("libtorchaudio")
47 import torchaudio.lib._torchaudio # noqa
49 _check_cuda_version()
File /opt/conda/lib/python3.10/site-packages/torchaudio/_extension/utils.py:64, in _load_lib(lib)
62 if not path.exists():
63 return False
---> 64 torch.ops.load_library(path)
65 torch.classes.load_library(path)
66 return True
File /opt/conda/lib/python3.10/site-packages/torch/_ops.py:933, in _Ops.load_library(self, path)
928 path = _utils_internal.resolve_library_path(path)
929 with dl_open_guard():
930 # Import the shared library into the process, thus running its
931 # static (global) initialization code in order to register custom
932 # operators with the JIT.
--> 933 ctypes.CDLL(path)
934 self.loaded_libraries.add(path)
File /opt/conda/lib/python3.10/ctypes/__init__.py:374, in CDLL.__init__(self, name, mode, handle, use_errno, use_last_error, winmode)
371 self._FuncPtr = _FuncPtr
373 if handle is None:
--> 374 self._handle = _dlopen(self._name, mode)
375 else:
376 self._handle = handle
OSError: /opt/conda/lib/python3.10/site-packages/torchaudio/lib/libtorchaudio.so: undefined symbol: _ZNK5torch8autograd4Node4nameB5cxx11Ev
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I am using a kaggle environment.
My installation code (it has a lot of dependency conflicts but i don’t know how to solve it):
!git clone GitHub - ivanhe123/seamless_communication: Foundational Models for State-of-the-Art Speech and Text Translation
!pip install ./seamless_communication
Dependency conflicts:
ERROR: pip’s dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
cudf 24.4.1 requires cubinlinker, which is not installed.
cudf 24.4.1 requires cupy-cuda11x>=12.0.0, which is not installed.
cudf 24.4.1 requires ptxcompiler, which is not installed.
cuml 24.4.0 requires cupy-cuda11x>=12.0.0, which is not installed.
dask-cudf 24.4.1 requires cupy-cuda11x>=12.0.0, which is not installed.
keras-cv 0.9.0 requires keras-core, which is not installed.
keras-nlp 0.12.1 requires keras-core, which is not installed.
tensorflow-decision-forests 1.8.1 requires wurlitzer, which is not installed.
beatrix-jupyterlab 2023.128.151533 requires jupyterlab~=3.6.0, but you have jupyterlab 4.2.1 which is incompatible.
cudf 24.4.1 requires cuda-python<12.0a0,>=11.7.1, but you have cuda-python 12.5.0 which is incompatible.
distributed 2024.1.1 requires dask==2024.1.1, but you have dask 2024.5.2 which is incompatible.
featuretools 1.31.0 requires tqdm>=4.66.3, but you have tqdm 4.64.1 which is incompatible.
fitter 1.7.0 requires tqdm<5.0.0,>=4.65.1, but you have tqdm 4.64.1 which is incompatible.
gcsfs 2024.3.1 requires fsspec==2024.3.1, but you have fsspec 2024.2.0 which is incompatible.
google-cloud-bigquery 2.34.4 requires packaging<22.0dev,>=14.3, but you have packaging 23.2 which is incompatible.
jupyterlab 4.2.1 requires jupyter-lsp>=2.0.0, but you have jupyter-lsp 1.5.1 which is incompatible.
jupyterlab-lsp 5.1.0 requires jupyter-lsp>=2.0.0, but you have jupyter-lsp 1.5.1 which is incompatible.
libpysal 4.9.2 requires shapely>=2.0.1, but you have shapely 1.8.5.post1 which is incompatible.
momepy 0.7.0 requires shapely>=2, but you have shapely 1.8.5.post1 which is incompatible.
osmnx 1.9.3 requires shapely>=2.0, but you have shapely 1.8.5.post1 which is incompatible.
rapids-dask-dependency 24.4.1a0 requires dask==2024.1.1, but you have dask 2024.5.2 which is incompatible.
rapids-dask-dependency 24.4.1a0 requires dask-expr==0.4.0, but you have dask-expr 1.1.2 which is incompatible.
s3fs 2024.3.1 requires fsspec==2024.3.1, but you have fsspec 2024.2.0 which is incompatible.
spopt 0.6.0 requires shapely>=2.0.1, but you have shapely 1.8.5.post1 which is incompatible.
tensorflow 2.15.0 requires keras<2.16,>=2.15.0, but you have keras 3.3.3 which is incompatible.
ydata-profiling 4.6.4 requires numpy<1.26,>=1.16.0, but you have numpy 1.26.4 which is incompatible.
I think by solving the dependency conflict it will solve the problem, but i don’t know how to.