docs/tutorials/install.md

Installation

This section provides a tutorial on building a working environment for LibContinual from scratch.

Get the LibContinual library

Use the following command to get LibContinual:

cd ~
git clone https://github.com/RL-VIG/LibContinual.git

Configure the LibContinual environment

The environment can be configured in any of the following ways:

1. conda(recommend)

   cd <path-to-LibContinual> # cd in `LibContinual` directory
   conda env create -f requirements.yaml
   

2. pip

   cd <path-to-LibContinual> # cd in `LibContinual` directory
   pip install -r requirements.txt
   

3. or whatever works for you as long as the following package version conditions are meet:

   diffdist==0.1
   numpy==1.21.5
   pandas==1.1.5
   Pillow==9.2.0
   PyYAML==6.0.1
   scikit_learn==1.0.2
   torch==1.12.1
   torchvision==0.13.1
   tqdm==4.64.1
   python==3.8.0
   timm=0.6.7
   

Test the installation

1. set the config as follows in run_trainer.py:

   config = Config("./config/lucir.yaml").get_config_dict()
   

2. modify data_root in config/lucir.yaml to the path of the dataset to be used.
3. run code

   python run_trainer.py
   

4. If the first output is correct, it means that LibContinual has been successfully installed.

Next