| ## 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`: | |
| ```shell | |
| 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) | |
| ```shell | |
| cd <path-to-LibContinual> # cd in `LibContinual` directory | |
| conda env create -f requirements.yaml | |
| ``` | |
| 2. pip | |
| ```shell | |
| 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`: | |
| ```python | |
| 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 | |
| ```shell | |
| python run_trainer.py | |
| ``` | |
| 4. If the first output is correct, it means that `LibContinual` has been successfully installed. | |
| ## Next | |