Errors when installing the package

[Roberyan]

pip install mamba-ssm Collecting mamba-ssm Downloading mamba_ssm-1.2.0.post1.tar.gz (34 kB) Preparing metadata (setup.py) ... error error: subprocess-exited-with-error

× python setup.py egg_info did not run successfully. │ exit code: 1 ╰─> [13 lines of output] /tmp/pip-install-lee62uu9/mamba-ssm_33455b8c07f14e07975c949a8e215835/setup.py:78: UserWarning: mamba_ssm was requested, but nvcc was not found. Are you sure your environment has nvcc available? If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc. warnings.warn( Traceback (most recent call last): File "", line 2, in File "", line 34, in File "/tmp/pip-install-lee62uu9/mamba-ssm_33455b8c07f14e07975c949a8e215835/setup.py", line 112, in if bare_metal_version >= Version("11.8"): NameError: name 'bare_metal_version' is not defined

  torch.__version__  = 1.12.0+cu102

  [end of output]

note: This error originates from a subprocess, and is likely not a problem with pip. error: metadata-generation-failed

× Encountered error while generating package metadata. ╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.

Above is the error when I was trying to install the mamba package, how should I fix this. I am using WSL2 on win11, my computer does not have nvidia GPU, must the package be downloaded on a computer with gpu?

[vasqu]

You have answered your own question at the end. mamba-ssm expects a working cuda installation >=11.6 along an nvidia gpu. The error logs also tell you this: UserWarning: mamba_ssm was requested, but nvcc was not found. Are you sure your environment has nvcc available? If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc

The readme also gives the following dependencies:

Other requirements:
- Linux
- NVIDIA GPU
- PyTorch 1.12+
- CUDA 11.6+

So I'm also not sure if it even worked under Windows (with wsl2). If you only want to play around with mamba, I'd suggest using google collab for example where the requirements are already met.

[WhatAShot]

My pytorch is 2.2 with CUDA Version 12.2, but the error still happens.

[g00184435]

My pytorch is 2.2 with CUDA Version 12.2, but the error still happens.

You need to set CUDA_HOME

[vasqu]

My pytorch is 2.2 with CUDA Version 12.2, but the error still happens.

On which system are you and is nvcc --version recognized as command in your terminal? If not, you might have to set some env variables up such as cuda etc. (see this as quick reference but adjust it to your according installation directories). You can also find your cuda installation with whereis cuda (under most linux os).

[tmm88]

this seems to work for me

# Download CUDA pin file
#wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-wsl-ubuntu.pin
#sudo mv cuda-wsl-ubuntu.pin /etc/apt/preferences.d/cuda-repository-pin-600

# Download CUDA repository package
#wget https://developer.download.nvidia.com/compute/cuda/12.4.0/local_installers/cuda-repo-wsl-ubuntu-12-4-local_12.4.0-1_amd64.deb

'''

# Update package lists
sudo apt update

# Upgrade packages
sudo apt upgrade -y
sudo apt dist-upgrade -y
sudo apt full-upgrade -y

sudo apt install software-properties-common
sudo add-apt-repository ppa:ubuntu-toolchain-r/test

sudo dpkg --configure -

sudo apt update

sudo apt install gcc-12 g++-12 gcc-13 g++-13 -y

sudo dpkg --configure -

sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-12 12 --slave /usr/bin/g++ g++ /usr/bin/g++-12
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-13 13 --slave /usr/bin/g++ g++ /usr/bin/g++-13

sudo dpkg --configure -

sudo update-alternatives --config gcc

sudo dpkg --configure -

gcc --version

sudo apt install build-essential
sudo apt install libmpfr-dev libgmp3-dev libmpc-dev -y
wget http://ftp.gnu.org/gnu/gcc/gcc-13.2.0/gcc-13.2.0.tar.gz
#tar -xf gcc-13.2.0.tar.gz

sudo dpkg --configure -

cd gcc-13.2.0

sudo dpkg --configure -

./configure -v --build=x86_64-linux-gnu --host=x86_64-linux-gnu --target=x86_64-linux-gnu --prefix=/usr/local/gcc-13.2.0 --enable-checking=release --enable-languages=c,c++ --disable-multilib --program-suffix=-13.2.0

sudo dpkg --configure -

make -j3
sudo make install

sudo dpkg --configure -

/usr/local/gcc-13.2.0/bin/gcc-13.2.0 --version

sudo dpkg --configure -

# Install required packages
sudo apt install -y \
    libxkbcommon0=1.6.0-1 \
    fakeroot \
    libalgorithm-merge-perl \
    g++=4:13.2.0-7 \
    cpp-x86-64-linux-gnu=4:13.2.0-7 \
    g++-13>=13.2.0-11 \
    g++-x86-64-linux-gnu=4:13.2.0-7 \
    gcc-13>=13.2.0-11 \
    gcc=4:13.2.0-7 \
    gcc-x86-64-linux-gnu=4:13.2.0-7 \
    libglvnd0=1.7.0-1 \
    lto-disabled-list \
    openjdk-17-jre-headless=17.0.10+7-1~22.04.1 \
    libatk-wrapper-java-jni>=0.30.4-0ubuntu2 \
    cpp=4:13.2.0-7 \
    cpp-x86-64-linux-gnu=4:13.2.0-7 \
    g++-13>=13.2.0-11~ \
    g++-x86-64-linux-gnu=4:13.2.0-7 \ 
    gcc-13>=13.2.0-11~ \
    gcc=4:13.2.0-7 \
    cpp-x86-64-linux-gnu=4:13.2.0-7 \ 
    gcc-13>=13.2.0-11~ \
    gcc-x86-64-linux-gnu=4:13.2.0-7 \ 
    openjdk-17-jre-headless=17.0.10+7-1~22.04.1 \
    libatk-wrapper-java-jni>=0.30.4-0ubuntu2

'''

# Install CUDA repository
sudo dpkg -i cuda-repo-wsl-ubuntu-12-4-local_12.4.0-1_amd64

# Copy CUDA keyring
sudo cp /var/cuda-repo-wsl-ubuntu-12-4-local/cuda-*-keyring.gpg /usr/share/keyrings/

# Update package lists
sudo apt-get update

# Install CUDA toolkit
sudo apt-get -y install cuda-toolkit-12-4

# Install pycuda (optional)
#sudo pip3 install pycuda

[MindEvo]

I had the same problem because CUDA wasn't installed. I did the following to setup CUDA 11.6 on Ubuntu 20.04:

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin sudo mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600 wget http://developer.download.nvidia.com/compute/cuda/11.6.0/local_installers/cuda-repo-ubuntu2004-11-6-local_11.6.0-510.39.01-1_amd64.deb sudo dpkg -i cuda-repo-ubuntu2004-11-6-local_11.6.0-510.39.01-1_amd64.deb sudo apt-key add /var/cuda-repo-ubuntu2004-11-6-local/7fa2af80.pub sudo apt-get update sudo apt-get install cuda-11-6

Added to my bashrc: export PATH=/usr/local/cuda-11.6/bin${PATH:+:${PATH}} export LD_LIBRARY_PATH=/usr/local/cuda-11.6/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

Then source the changes. That allowed me to install both.

[ching-yao-lin]

This worked for me: conda install nvidia::cuda-toolkit=12.1

[WangYao-GoGoGo]

This worked for me: conda install nvidia::cuda-toolkit=12.1

nice!!