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Fix bugs in CISPO conditions #4499

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Merged
pramodith merged 2 commits into from
Nov 7, 2025
Merged

Fix bugs in CISPO conditions #4499

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7bbfc96
Fix bugs!
pramodith Nov 6, 2025
f215701
nits.
pramodith Nov 6, 2025
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9 changes: 5 additions & 4 deletions trl/trainer/grpo_trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1824,11 +1824,10 @@ def _compute_loss(self, model, inputs):

# From here, log_importance_weights (and all subsequent tensors, coef_1, coef_2, etc.) shape depends on
# importance_sampling_level: "token" level: (B, T); "sequence" level: (B, 1)
if self.loss_type in ["grpo", "bnpo", "dr_grpo", "dapo"]:
if self.loss_type == "cispo":
clamped_ratios = torch.clamp(coef_1, max=self.epsilon_high).detach()
per_token_loss = -clamped_ratios * advantages.unsqueeze(1) * per_token_logps

else:
elif self.loss_type in ["grpo", "bnpo", "dr_grpo", "dapo"]:
coef_2 = torch.clamp(coef_1, 1 - self.epsilon_low, 1 + self.epsilon_high)
# Two-sided clipping
if self.args.delta is not None:
Expand All @@ -1837,6 +1836,8 @@ def _compute_loss(self, model, inputs):
per_token_loss1 = coef_1 * advantages.unsqueeze(1)
per_token_loss2 = coef_2 * advantages.unsqueeze(1)
per_token_loss = -torch.min(per_token_loss1, per_token_loss2)
else:
raise ValueError(f"Unknown loss type: {self.loss_type}")

if entropy_mask is not None:
per_token_loss = per_token_loss * entropy_mask
Expand Down Expand Up @@ -1880,7 +1881,7 @@ def masked_batch_mean(x):
mean_entropy = masked_batch_mean(entropies)
self._metrics[mode]["entropy"].append(self.accelerator.gather(mean_entropy).nanmean().item())

if self.loss_type != "cispo":
if self.loss_type in ["grpo", "bnpo", "dr_grpo", "dapo"]:
# Compute the clipped probability ratios
is_low_clipped = (coef_1 < 1 - self.epsilon_low) & (advantages.unsqueeze(1) < 0)
is_high_clipped = (coef_1 > 1 + self.epsilon_high) & (advantages.unsqueeze(1) > 0)
Expand Down
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