I'm trying to reproduce the results of the liquid s4 paper, but I ran into this problem of not being able to import Pyarrow. The entire error message read:import pyarrow as pa
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/nfs/state_space_model/.local/lib/python3.10/site-packages/pyarrow/__init__.py", line 65, in <module>
import pyarrow.lib as _lib
ImportError: /lib/x86_64-linux-gnu/libc.so.6: version `GLIBC_2.28' not found (required by /home/nfs/path/.local/lib/python3.10/site-packages/pyarrow/libarrow.so.1500)
It seems like something to do with my linux system. But I have no idea where to get started. Below are my current environment setup and information about my gpu.
absl-py==1.4.0
aiohttp==3.9.3
aiosignal==1.3.1
antlr4-python3-runtime==4.9.3
appdirs==1.4.4
async-timeout==4.0.3
attrs==23.2.0
certifi==2024.2.2
charset-normalizer==3.3.2
chex==0.1.6
click==8.1.7
cmake==3.29.0.1
contourpy==1.2.0
cycler==0.12.1
datasets==2.18.0
dill==0.3.8
dm-tree==0.1.8
docker-pycreds==0.4.0
einops==0.7.0
filelock==3.13.1
fonttools==4.50.0
frozenlist==1.4.1
fsspec==2024.2.0
future==1.0.0
gitdb==4.0.11
GitPython==3.1.42
googleapis-common-protos==1.63.0
grpcio==1.62.1
huggingface-hub==0.21.4
hydra-core==1.3.2
idna==3.6
Jinja2==3.1.3
joblib==1.3.2
keopscore==2.2.2
kiwisolver==1.4.5
lightning-utilities==0.11.2
Markdown==3.6
markdown-it-py==3.0.0
MarkupSafe==2.1.5
matplotlib==3.8.3
mdurl==0.1.2
ml-dtypes==0.3.2
mpmath==1.3.0
msgpack==1.0.8
multidict==6.0.5
multiprocess==0.70.16
networkx==3.2.1
numpy==1.26.4
nvidia-cublas-cu12==12.1.3.1
nvidia-cuda-cupti-cu12==12.1.105
nvidia-cuda-nvrtc-cu12==12.1.105
nvidia-cuda-runtime-cu12==12.1.105
nvidia-cudnn-cu12==8.9.2.26
nvidia-cufft-cu12==11.0.2.54
nvidia-curand-cu12==10.3.2.106
nvidia-cusolver-cu12==11.4.5.107
nvidia-cusparse-cu12==12.1.0.106
nvidia-nccl-cu12==2.19.3
nvidia-nvjitlink-cu12==12.4.99
nvidia-nvtx-cu12==12.1.105
omegaconf==2.3.0
opt-einsum==3.3.0
optax==0.1.7
packaging==24.0
pandas==2.2.1
pillow==10.2.0
promise==2.3
protobuf==3.20.3
psutil==5.9.8
pyarrow==15.0.2
pyarrow-hotfix==0.6
pybind11==2.12.0
pyDeprecate==0.3.1
pydub==0.25.1
Pygments==2.17.2
pykeops==2.2.2
pyparsing==3.1.2
python-dateutil==2.9.0.post0
pytorch-lightning==1.5.10
pytz==2024.1
PyYAML==6.0.1
regex==2023.12.25
requests==2.31.0
rich==13.7.1
safetensors==0.4.2
scikit-learn==1.4.1.post1
scipy==1.12.0
sentry-sdk==1.44.0
setproctitle==1.3.3
six==1.16.0
smmap==5.0.1
sympy==1.12
tensorboard==2.16.2
tensorboard-data-server==0.7.2
tensorflow-datasets==4.5.2
tensorflow-metadata==1.14.0
termcolor==2.4.0
threadpoolctl==3.4.0
tokenizers==0.15.2
toolz==0.12.1
torch==2.2.1
torchaudio==2.2.1
torchdata==0.7.1
torchmetrics==1.3.2
torchtext==0.17.1
torchvision==0.17.1
tqdm==4.66.2
transformers==4.39.2
triton==2.2.0
typing_extensions==4.10.0
tzdata==2024.1
urllib3==2.2.1
wandb==0.16.5
Werkzeug==3.0.1
xxhash==3.4.1
yarl==1.9.4
I'm using a RTX3060 gpu.
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.60.13 Driver Version: 525.60.13 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... On | 00000000:01:00.0 Off | N/A |
| 30% 33C P8 13W / 170W | 1MiB / 12288MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
Does anyone know what could go wrong and how I can fix them? Any help is appreciated. Please let me know if you need further information.