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Update rl_replacements.py

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Daniel Han 2025-03-14 05:51:08 -07:00
commit 5b24b2e761
1 changed files with 6 additions and 3 deletions
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9
unsloth/models/rl_replacements.py
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@ -207,9 +207,12 @@ def grpo_trainer__get_per_token_logps(function_name, function):
if function_name != "_get_per_token_logps": return function
def _get_per_token_logps(self, model, input_ids, attention_mask, logits_to_keep):
return None # Unsloth efficient GRPO
if os.environ.get('UNSLOTH_USE_NEW_MODEL', '0') == '1':
return None # Unsloth efficient GRPO
# Otherwise, calculate normally:
if not hasattr(self, '_autocast_dtype'):
self._autocast_dtype = torch.float16 if os.environ.get('ACCELERATE_MIXED_PRECISION', 'fp16') == 'fp16' else torch.bfloat16
if os.environ.get('UNSLOTH_FORCE_FLOAT32', '0') == '1': self._autocast_dtype = torch.float32
with torch.amp.autocast(device_type = 'cuda', dtype = self._autocast_dtype):
# We add 1 to `logits_to_keep` because the last logits of the sequence is later excluded
logits = model(input_ids=input_ids, attention_mask=attention_mask, logits_to_keep=logits_to_keep + 1).logits
@ -266,8 +269,8 @@ def grpo_trainer_compute_loss(function_name, function):
# 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:]
if False:#per_token_logps is not None:
loss, completion_length, mean_kl = grpo_compute_loss(
if per_token_logps is not None:
loss, completion_length, mean_kl = grpo_compute_loss_compiled(
ref_per_token_logps, per_token_logps, input_ids, completion_mask, self.beta, advantages,
)
else: