mirror of
https://github.com/open-mmlab/mmrazor.git
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114 lines
3.7 KiB
Markdown
114 lines
3.7 KiB
Markdown
## Prerequisites
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- Linux
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- Python 3.7+
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- PyTorch 1.5+
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- CUDA 9.2+ (If you build PyTorch from source, CUDA 9.0 is also compatible)
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- GCC 5+
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- [MMCV](https://mmcv.readthedocs.io/en/latest/#installation)
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**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`.
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## Installation
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### Prepare environment
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1. Create a conda virtual environment and activate it.
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```Bash
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conda create -n openmmlab python=3.7 -y
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conda activate openmmlab
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```
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2. Install PyTorch and torchvision following the [official instructions](https://pytorch.org/).
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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](https://pytorch.org/).
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`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.
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```Bash
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conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch
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```
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`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.
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```Bash
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conda install pytorch==1.5.1 torchvision==0.6.1 cudatoolkit=9.2 -c pytorch
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```
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If you build PyTorch from source instead of installing the prebuilt package, you can use more CUDA versions such as 9.0.
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### Install MMRazor
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It is recommended to install MMRazor with [MIM](https://github.com/open-mmlab/mim), which automatically handles the dependencies of OpenMMLab projects, including mmcv and other python packages.
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```Bash
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pip install openmim
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mim install mmrazor
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```
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Or you can still install MMRazor manually
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1. Install mmcv-full.
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```Bash
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pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.html
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```
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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:
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```Bash
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pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.10.0/index.html
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```
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See [here](https://github.com/open-mmlab/mmcv#installation) for different versions of MMCV compatible to different PyTorch and CUDA versions.
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Optionally, you can compile mmcv from source if you need to develop both mmcv and mmdet. Refer to the [guide](https://github.com/open-mmlab/mmcv#installation) for details.
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2. Install MMRazor.
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You can simply install mmrazor with the following command:
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```Bash
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pip install mmrazor
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```
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or:
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```Bash
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pip install git+https://github.com/open-mmlab/mmrazor.git # install the master branch
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```
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Instead, if you would like to install MMRazor in `dev` mode, run following:
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```Bash
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git clone https://github.com/open-mmlab/mmrazor.git
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cd mmrazor
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pip install -v -e . # or "python setup.py develop"
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```
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**Note:**
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- When MMRazor is installed on `dev` mode, any local modifications made to the code will take effect without the need to reinstall it.
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- Currently, running `pip install -v -e .` will install `mmcls`, `mmdet`, `mmsegmentation`. We will work on minimum runtime requirements in future.
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### A from-scratch setup script
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```Bash
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conda create -n openmmlab python=3.7 -y
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conda activate openmmlab
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conda install pytorch torchvision cudatoolkit=10.2 -c pytorch
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# install the latest mmcv
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pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.10.0/index.html
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# install mmrazor
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git clone https://github.com/open-mmlab/mmrazor.git
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cd mmrazor
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pip install -v -e .
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```
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