【快捷查询】pytorch\pytorch3d\python版本对应关系 | pytorch\pytorch3d\python version correspondence
目前建议直接使用第三方源。 官方的安装说明。 第三方预构建源的安装说明：Prebuilt wheels provided via 3rd party repository pip包检索页：https://miropsota.github.io/torch_packages_builder/ 安装包时可以直接使用： pip install --extra-index-url https://miropsota.github.io/torch_packages_builder <your package list> 发布页：https://github.com/MiroPsota/torch_packages_builder/releases 同时，这个项目也包含了以下预构建源： pytorch3d[0.7.5,0.7.6,0.7.7,0.7.8,0.7.8+366eff2,0.7.8+5043d15,0.7.9] fairseq[0.12.2+d9a6270,0.12.2+d13e14a,0.12.2+3d262bb] detectron2[0.6+864913f,0.6,0.6+2a420ed,0.6+18f6958,0.6+fd27788] flash_attn[2.8.3] tinycudann[1.7+075158a,2.0] fused_ssim[0.0.1+30fb258,0.0.1+b4fd832] simple_knn[0.0.1+86710c2] diff_gaussian_rasterization[0.0.1+9c5c202] mmcv[2.2.0] SAM_2[1.0+86827e2,1.0+c2ec8e1] MultiScaleDeformableAttention[1.0+9b0651c]
【快捷查询】pytorch\xformers\python版本对应关系 | pytorch\xformers\python version correspondence
注意：仅指预构建的轮子 (其实之前的构建没那么全的，不知道是哪位大好人给补齐了各版本的。。。所以其实做这个表也没啥用了) xformers pytorch python cuda 0.0.27.post1 >= 2.4 py38-py311 11.8 & 12.1 0.0.27 >= 2.2 py38-py312 11.8 & 12.1 0.0.26.post1 >= 2.1 py38-py311 11.8 & 12.1 0.0.26 >= 2.1 py38-py311 11.8 & 12.1 0.0.25.post1 >= 2.1 py38-py311 11.8 & 12.1 0.0.25 >= 2.1 py38-py311 11.8 & 12.1 0.0.24 >= 2.1 py38-py311 11.8 & 12.1 0.0.23.post1 >= 1.12 py38-py311 11.8 & 12.1 0.0.23 >= 1.12 py38-py311 11.8 & 12.1 0.0.22.post7 >= 1.12 py38-py311 11.8 & 12.1 0.0.22.post4 >= 1.12 py38-py311 11.8 & 12.1 0.0.22.post3 >= 1.12 py38-py311 11.8 & 12.1, 12.1 For Only Linux 0.0.22.post2 >= 1.12 py38-py311 11.8 For Only Windows 注意，0.0.27.post1的预构建whl文件需要pytorch2.4.0 Installing xFormers (RECOMMENDED, linux) Install latest stable with conda: Requires PyTorch 2.3.1 installed with conda conda install xformers -c xformers (RECOMMENDED, linux & win) Install latest stable with pip: Requires PyTorch 2.3.1 # cuda 11.8 version pip3 install -U xformers --index-url https://download.pytorch.org/whl/cu118 # cuda 12.1 version pip3 install -U xformers --index-url https://download.pytorch.org/whl/cu121 Development binaries: # Use either conda or pip, same requirements as for the stable version above conda install xformers -c xformers/label/dev pip install --pre -U xformers Install from source: If you want to use with another version of PyTorch for instance (including nightly-releases) # (Optional) Makes the build much faster pip install ninja # Set TORCH_CUDA_ARCH_LIST if running and building on different GPU types pip install -v -U git+https://github.com/facebookresearch/xformers.git@main#egg=xformers # (this can take dozens of minutes)