From PyTorch DDP to Accelerate to Trainer, mastery of distributed training with ease

This post details the progression from native PyTorch DDP to 🤗 Accelerate and 🤗 Trainer for distributed training. It explains the setup and cleanup functions for DDP, the role of `DistributedDataParallel`, and the advantages of Accelerate in simplifying code modifications for various distributed scenarios (single GPU, multi-GPU, TPU). It also highlights the boilerplate abstraction provided by the 🤗 Trainer API.