ColossalAI/examples/tutorial/large_batch_optimizer/README.md

Comparison of Large Batch Training Optimization

Table of contents

• Overview
• Quick Start

📚 Overview

This example lets you to quickly try out the large batch training optimization provided by Colossal-AI. We use synthetic dataset to go through the process, thus, you don't need to prepare any dataset. You can try out the Lamb and Lars optimizers from Colossal-AI with the following code.

from colossalai.nn.optimizer import Lamb, Lars

🚀 Quick Start

1. Install PyTorch

2. Install the dependencies.

pip install -r requirements.txt

3. Run the training scripts with synthetic data.

# run on 4 GPUs
# run with lars
colossalai run --nproc_per_node 4 train.py --config config.py --optimizer lars

# run with lamb
colossalai run --nproc_per_node 4 train.py --config config.py --optimizer lamb