I’m working on Win11, WSL 2, Ubuntu 22.04.
The problem is what the title shows, and it happens when I was trying to set the environment for Mamba structure.
To reproduce,
conda create -n cmamba2 python=3.10
conda activate cmamba2
conda install -c pytorch -c conda-forge -c nvidia timm==0.6.5 pytorch==2.3.0 torchvision==0.18.0 torchaudio==2.3.0 pytorch-cuda=11.8
conda install -c conda-forge triton
Then, I checked Python, PyTorch and CUDA versions, and their versions decide which .whl file I should download.
Commands and outputs are separately and sequentially showed below.
python -V
Python 3.10.16
nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Wed_Sep_21_10:33:58_PDT_2022
Cuda compilation tools, release 11.8, V11.8.89
Build cuda_11.8.r11.8/compiler.31833905_0
conda list cuda
# packages in environment at /root/anaconda3/envs/cmamba2:
#
# Name Version Build Channel
cuda-cudart 11.8.89 0 nvidia
cuda-cupti 11.8.87 0 nvidia
cuda-libraries 11.8.0 0 nvidia
cuda-nvrtc 11.8.89 0 nvidia
cuda-nvtx 11.8.86 0 nvidia
cuda-runtime 11.8.0 0 nvidia
cuda-version 11.8 h70ddcb2_3 conda-forge
cudatoolkit 11.8.0 h4ba93d1_13 conda-forge
pytorch-cuda 11.8 h7e8668a_6 pytorch
conda list pytorch
# packages in environment at /root/anaconda3/envs/cmamba2:
#
# Name Version Build Channel
pytorch 2.3.0 cuda118_py310h954aa82_301 conda-forge
pytorch-cuda 11.8 h7e8668a_6 pytorch
pytorch-mutex 1.0 cuda pytorch
Also, I ran a command to check whether GLIBCXX_USE_CXX11_ABI is true, maybe it means to use a specific way to compile some packages, and I cannot quite understand it.
python -c 'import torch; print(torch._C._GLIBCXX_USE_CXX11_ABI); print(torch.compiled_with_cxx11_abi())'
Its output is
True
True
So I downloaded 2 below .whl files.
causal_conv1d-1.5.0.post8+cu11torch2.3cxx11abiTRUE-cp310-cp310-linux_x86_64.whl
mamba_ssm-2.2.2+cu118torch2.3cxx11abiTRUE-cp310-cp310-linux_x86_64.whl
separately from Releases · Dao-AILab/causal-conv1d · GitHub and Releases · state-spaces/mamba · GitHub.
These 2 .whl files are stored in a file folder called whl, which is the sub file folder of the main project file folder.
Then I entered the whl file folder with cd command and ran the 2 following commands to install:
pip install causal_conv1d-1.5.0.post8+cu11torch2.3cxx11abiTRUE-cp310-cp310-linux_x86_64.whl
pip install mamba_ssm-2.2.2+cu118torch2.3cxx11abiTRUE-cp310-cp310-linux_x86_64.whl
Then
python
import trochvision
The problem appears, full output
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/root/anaconda3/envs/cmamba2/lib/python3.10/site-packages/torchvision/__init__.py", line 6, in <module>
from torchvision import _meta_registrations, datasets, io, models, ops, transforms, utils
File "/root/anaconda3/envs/cmamba2/lib/python3.10/site-packages/torchvision/_meta_registrations.py", line 164, in <module>
def meta_nms(dets, scores, iou_threshold):
File "/root/anaconda3/envs/cmamba2/lib/python3.10/site-packages/torch/library.py", line 467, in inner
handle = entry.abstract_impl.register(func_to_register, source)
File "/root/anaconda3/envs/cmamba2/lib/python3.10/site-packages/torch/_library/abstract_impl.py", line 30, in register
if torch._C._dispatch_has_kernel_for_dispatch_key(self.qualname, "Meta"):
RuntimeError: operator torchvision::nms does not exist
nvidia-smi
Tue Apr 15 17:30:07 2025
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 570.133.07 Driver Version: 572.83 CUDA Version: 12.8 |
|-----------------------------------------+------------------------+----------------------+
| 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 RTX 4070 ... On | 00000000:01:00.0 On | N/A |
| 0% 40C P8 18W / 285W | 788MiB / 16376MiB | 5% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| 0 N/A N/A 28 G /Xwayland N/A |
+----------------------------------------------------------------------------------