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Update rl_replacements.py

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Daniel Han 2025-02-14 04:49:41 -08:00
commit 9adbd6909b
1 changed files with 3 additions and 3 deletions
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unsloth/models/rl_replacements.py
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@ -195,7 +195,7 @@ RL_FUNCTIONS["grpo_trainer"].append(grpo_trainer__get_per_token_logps)
# Custom compiled GRPO loss - creates 3 Triton kernels
# @torch.compile(dynamic = True, fullgraph = True, options = torch_compile_options,)
@torch.compile(dynamic = True, fullgraph = True, options = torch_compile_options,)
def _grpo_compute_loss(old_logits, new_logits, input_ids, mask, beta):
old_logits = old_logits.to(torch.float32)
new_logits = new_logits.to(torch.float32)
@ -247,7 +247,7 @@ def grpo_trainer_compute_loss(function_name, function):
# attention_mask = torch.cat([prompt_mask, completion_mask], dim=1)
attention_mask = None
logits_to_keep = completion_ids.size(1) # we only need to compute the logits for the completion tokens
per_token_logps = self._get_per_token_logps(model, input_ids, attention_mask, logits_to_keep)
# Compute the KL divergence between the model and the reference model
@ -259,7 +259,7 @@ def grpo_trainer_compute_loss(function_name, function):
# per_token_loss = torch.exp(per_token_logps - per_token_logps.detach()) * advantages.unsqueeze(1)
# per_token_loss = -(per_token_loss - self.beta * per_token_kl)
# loss = ((per_token_loss * completion_mask).sum(dim=1) / completion_mask.sum(dim=1)).mean()
input_ids = input_ids[:, -logits_to_keep:]
loss, completion_length, mean_kl = grpo_compute_loss(
ref_per_token_logps, per_token_logps, input_ids, completion_mask, self.beta,
)