Prerequisites
Linux or macOS (Windows is in experimental support)
Python 3.6+
PyTorch 1.3+
CUDA 9.2+ (If you run using GPU)
Installation
Prepare environment
Create a conda virtual environment and activate it.
conda create -n coala python=3.7 -y conda activate coala
Install PyTorch and torchvision following the official instructions, e.g.,
conda install pytorch torchvision -c pytorch
or
pip install torch==1.10.1 torchvision==0.11.2
You can skip the following CUDA-related content if you plan to run it on CPU. Make sure that your compilation CUDA version and runtime CUDA version match.
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 10.1 installed under/usr/local/cuda
and would like to install PyTorch 1.5, you need to install the prebuilt PyTorch with CUDA 10.1.conda install pytorch cudatoolkit=10.1 torchvision -c pytorch
E.g.,
2. If you have CUDA 9.2 installed under/usr/local/cuda
and would like to install PyTorch 1.3.1., you need to install the prebuilt PyTorch with CUDA 9.2.conda install pytorch=1.3.1 cudatoolkit=9.2 torchvision=0.4.2 -c pytorch
If you build PyTorch from source instead of installing the prebuilt package, you can use more CUDA versions such as 9.0.
A from-scratch setup script
Assuming that you already have CUDA 10.1 installed, here is a full script for setting up MMDetection with conda.
conda create -n coala python=3.7 -y
conda activate coala
# Without GPU
conda install pytorch==1.6.0 torchvision==0.7.0 -c pytorch -y
# With GPU
conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.1 -c pytorch -y
# install coala
git clone https://github.com/SonyResearch/COALA.git
cd coala
pip install -v -e .