Linux
Python 3.7+
PyTorch 1.5+
CUDA 9.2+ (If you build PyTorch from source, CUDA 9.0 is also compatible)
GCC 5+
Note: You need to run pip uninstall mmcv
first if you have mmcv installed. If mmcv and mmcv-full are both installed, there will be ModuleNotFoundError
.
Create a conda virtual environment and activate it.
conda create -n openmmlab python=3.7 -y
conda activate openmmlab
Install PyTorch and torchvision following the official instructions.
Note: Make sure that your compilation CUDA version and runtime CUDA version match. You can check the supported CUDA version for precompiled packages on the PyTorch website.
E.g.1
If you have CUDA 10.2 installed under /usr/local/cuda
and would like to install PyTorch 1.10, you need to install the prebuilt PyTorch with CUDA 10.2.
conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch
E.g.2
If you have CUDA 9.2 installed under /usr/local/cuda
and would like to install PyTorch 1.5.1, you need to install the prebuilt PyTorch with CUDA 9.2.
conda install pytorch==1.5.1 torchvision==0.6.1 cudatoolkit=9.2 -c pytorch
If you build PyTorch from source instead of installing the prebuilt package, you can use more CUDA versions such as 9.0.
It is recommended to install MMRazor with MIM, which automatically handles the dependencies of OpenMMLab projects, including mmcv and other python packages.
pip install openmim
mim install mmrazor
Or you can still install MMRazor manually
Install mmcv-full.
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.html
Please replace {cu_version}
and {torch_version}
in the url to your desired one. For example, to install the latest mmcv-full
with CUDA 10.2
and PyTorch 1.10.0
, use the following command:
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.10.0/index.html
See here for different versions of MMCV compatible to different PyTorch and CUDA versions.
Optionally, you can compile mmcv from source if you need to develop both mmcv and mmdet. Refer to the guide for details.
Install MMRazor.
You can simply install mmrazor with the following command:
pip install mmrazor
or:
pip install git+https://github.com/open-mmlab/mmrazor.git # install the master branch
Instead, if you would like to install MMRazor in dev
mode, run following:
git clone https://github.com/open-mmlab/mmrazor.git
cd mmrazor
pip install -v -e . # or "python setup.py develop"
Note:
dev
mode, any local modifications made to the code will take effect without the need to reinstall it.pip install -v -e .
will install mmcls
, mmdet
, mmsegmentation
. We will work on minimum runtime requirements in future.conda create -n openmmlab python=3.7 -y
conda activate openmmlab
conda install pytorch torchvision cudatoolkit=10.2 -c pytorch
# install the latest mmcv
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.10.0/index.html
# install mmrazor
git clone https://github.com/open-mmlab/mmrazor.git
cd mmrazor
pip install -v -e .
Вы можете оставить комментарий после Вход в систему
Неприемлемый контент может быть отображен здесь и не будет показан на странице. Вы можете проверить и изменить его с помощью соответствующей функции редактирования.
Если вы подтверждаете, что содержание не содержит непристойной лексики/перенаправления на рекламу/насилия/вульгарной порнографии/нарушений/пиратства/ложного/незначительного или незаконного контента, связанного с национальными законами и предписаниями, вы можете нажать «Отправить» для подачи апелляции, и мы обработаем ее как можно скорее.
Комментарий ( 0 )