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5fee096 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | ## 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
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