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Installation

We provide some tips for OpenTSGV installation in this file.

Requirements

  • Linux
  • Python 3.7.9
  • PyTorch 1.10.2
  • Torchvision 0.11.3
  • CUDA 11.4
  • GCC 5+
  • mmcv (Version is depended on cuda and pytorch versions)
  • Numpy
  • Scipy
  • Transformers
  • future
  • Tensorboard
  • h5py

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.

Prepare environment

a. Create a conda virtual environment and activate it.

conda create -n tsgv python=3.7 -y
conda activate tsgv

b. Install PyTorch and torchvision following the official instructions, e.g.,

conda install pytorch torchvision -c pytorch

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. :::

Install OpenTSGV

You can install OpenTSGV manually:

a. Install mmcv-full, we recommend you to install the pre-built package as below.

# pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.html
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.10.0/index.html

mmcv-full is only compiled on PyTorch 1.x.0 because the compatibility usually holds between 1.x.0 and 1.x.1. If your PyTorch version is 1.x.1, you can install mmcv-full compiled with PyTorch 1.x.0 and it usually works well.

# We can ignore the micro version of PyTorch
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.10/index.html

See here for different versions of MMCV compatible to different PyTorch and CUDA versions.

Optionally you can choose to compile mmcv from source by the following command

git clone https://github.com/open-mmlab/mmcv.git
cd mmcv
MMCV_WITH_OPS=1 pip install -e .  # package mmcv-full, which contains cuda ops, will be installed after this step
# OR pip install -e .  # package mmcv, which contains no cuda ops, will be installed after this step
cd ..

Or directly run

pip install mmcv-full
# alternative: pip install mmcv

Important: 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.

b. Clone the OpenTSGV repository.

git clone **
cd **

c. Install build requirements and then install OpenTSGV.

pip install -r requirements/build.txt
pip install -v -e .  # or "python setup.py develop"

NOTE: The git commit id will be written to the version number with step b, e.g. 0.6.0+2e7045c. The version will also be saved in trained models. It is recommended that you run step b each time you pull some updates from github. If C++/CUDA codes are modified, then this step is compulsory.