**First**, run the command below to get the splited dataset:

```sh
# generate the splited dataset
python generate_fedtask.py --benchmark mnist_classification --dist 1 --skew 0.0 --num_clients 100
```

**Second**, run the command below to quickly get a result of the basic algorithm FedAvg on MNIST with a simple CNN:

```sh
python main.py --task mnist_classification_cnum100_dist0_skew0.0_seed0 --model mlp --algorithm fedeba --num_rounds 2000 --num_epochs 1 --learning_rate 0.1 --proportion 0.1 --batch_size 64 --eval_interval 1 --T 0.9 --feda 0.1
# if using gpu, add the id of the gpu device as '--gpu id' to the end of the command like this
python main.py --task mnist_classification_cnum100_dist0_skew0.0_seed0 --model mlp --algorithm fedeba --num_rounds 2000 --num_epochs 1 --learning_rate 0.1 --proportion 0.1 --batch_size 64 --eval_interval 1 --T 0.9 --feda 0.1 --gpu 0
```