categories: [Python]
tags: Python MacOS
写在前面
试试 m3 的 metal 加速效果如何
- Mac computers with Apple silicon or AMD GPUs
- macOS 12.3 or later
- Python 3.7 or later
- Xcode command-line tools:
xcode-select --install
安装 Python: conda-forge
brew install miniforge
镜像
channels:- defaults
show_channel_urls: true
auto_activate_base: false
ssl-verify: false
default_channels:- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
custom_channels:conda-forge: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloudmsys2: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloudbioconda: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloudmenpo: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloudpytorch: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloudpytorch-lts: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloudsimpleitk: https://mirrors.tuna.tsinghua.edu.cn/anaconda/clouddeepmodeling: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/
安装
开一个新的虚拟环境, 这个是重点, 如果不开的话, 原有的环境会污染 C 库的链接, 所以这一步是必须的
On Mac OS X, import numpy complaining about “Library not loaded: @rpath/libgfortran.3.dylib” · Issue #12970 · numpy/numpy;
这个方案不彻底, 直接卸载 numpy 然后重装不能解决问题…
conda create -n py3xi python=3.11
conda activate py3xi
# conda update --all -c conda-forge # optional
# 重点:
conda install pytorch torchvision torchaudio -c pytorch-nightly
然后测试
Accelerated PyTorch training on Mac - Metal - Apple Developer;
import torch
if torch.backends.mps.is_available():mps_device = torch.device("mps")x = torch.ones(1, device=mps_device)print (x)
else:print ("MPS device not found.")
'''
tensor([1.], device='mps:0')
'''
可以在 MacOS 上跑深度学习了.