mamba，mamba2环境搭建

mamba和mamba2安装步骤的相关代码

conda create -n mamba_test python=3.10
conda activate mamba_test
conda install cudatoolkit=11.8 -c https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/linux-64/

pip install mamba_ssm-2.2.2+cu118torch2.0cxx11abiFALSE-cp310-cp310-linux_x86_64.whl 
pip install causal_conv1d-1.4.0+cu118torch2.0cxx11abiFALSE-cp310-cp310-linux_x86_64.whl 

pip install  triton==2.1.0
pip install numpy==1.22.4

对应的whl文件的下载地址：
mamba_ssm下载
causal_conv1d下载

可以运行的mamba和mamba2测试代码：

import torch
from mamba_ssm import Mamba
batch, length, dim = 2, 64, 16
x = torch.randn(batch, length, dim).to("cuda")
model = Mamba(
    # This module uses roughly 3 * expand * d_model^2 parameters
    d_model=dim,  # Model dimension d_model
    d_state=16,  # SSM state expansion factor
    d_conv=4,  # Local convolution width
    expand=2,  # Block expansion factor
).to("cuda")
y = model(x)
print("Mamba result", y.shape)
assert y.shape == x.shape
 
import torch
from mamba_ssm import Mamba2
 
batch, length, dim = 2, 64, 512
x = torch.randn(batch, length, dim).to("cuda")
model = Mamba2(
    # This module uses roughly 3 * expand * d_model^2 parameters
    # make sure d_model * expand / headdim = multiple of 8
    d_model=dim,  # Model dimension d_model
    d_state=64,  # SSM state expansion factor, typically 64 or 128
    d_conv=4,  # Local convolution width
    expand=2,  # Block expansion factor
    headdim=64,  # default 64
).to("cuda")
y = model(x)
print("Mamba2 result", y.shape)
assert y.shape == x.shape

可以参考的调试步骤：
Mamba-2 Error: ‘NoneType‘ object has no attribute ‘causal_conv1d_fwd‘

mamba_ssm和causal-conv1d安装教程