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[refactor] PPO cleanup

pull/815/head
jingyaogong 2026-07-23 11:11:05 +08:00
parent 2d4c385b0f
commit 89d674b8a5
1 changed files with 3 additions and 4 deletions
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7
trainer/train_ppo.py
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@ -12,7 +12,6 @@ import warnings
import torch
import torch.distributed as dist
import torch.nn.functional as F
from transformers import AutoTokenizer
from contextlib import nullcontext
from torch import optim, nn
from torch.nn.parallel import DistributedDataParallel
@ -76,7 +75,7 @@ def calculate_rewards(prompts, responses, reward_model):
return rewards
def ppo_train_epoch(epoch, loader, iters, rollout_engine, ref_model, actor_scheduler, critic_scheduler, reward_model, start_step=0, wandb=None, use_sglang=False):
def ppo_train_epoch(epoch, loader, iters, rollout_engine, ref_model, actor_scheduler, critic_scheduler, reward_model, start_step=0, wandb=None):
actor_model.train()
critic_model.train()
grad_accum_step = 0
@ -442,9 +441,9 @@ if __name__ == "__main__":
loader = DataLoader(train_ds, batch_sampler=batch_sampler, num_workers=args.num_workers, pin_memory=True)
if skip > 0:
Logger(f'Epoch [{epoch + 1}/{args.epochs}]: 跳过前{start_step}个step，从step {start_step + 1}开始')
ppo_train_epoch(epoch, loader, len(loader) + skip, rollout_engine, ref_model, actor_scheduler, critic_scheduler, reward_model, start_step, wandb, use_sglang = (args.rollout_engine == "sglang"))
ppo_train_epoch(epoch, loader, len(loader) + skip, rollout_engine, ref_model, actor_scheduler, critic_scheduler, reward_model, start_step, wandb)
else:
ppo_train_epoch(epoch, loader, len(loader), rollout_engine, ref_model, actor_scheduler, critic_scheduler, reward_model, 0, wandb, use_sglang = (args.rollout_engine == "sglang"))
ppo_train_epoch(epoch, loader, len(loader), rollout_engine, ref_model, actor_scheduler, critic_scheduler, reward_model, 0, wandb)
# ========== 9. 清理分布进程 ==========
if dist.is_initialized():