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Add left padding to LTXAV text encoder. (#12456)

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comfyanonymous 2026-02-13 18:56:54 -08:00 committed by GitHub
parent 726af73867
commit 712efb466b
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1 changed files with 3 additions and 1 deletions
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comfy/text_encoders/lt.py
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@ -25,7 +25,7 @@ def ltxv_te(*args, **kwargs):
class Gemma3_12BTokenizer(sd1_clip.SDTokenizer):
def __init__(self, embedding_directory=None, tokenizer_data={}):
tokenizer = tokenizer_data.get("spiece_model", None)
super().__init__(tokenizer, pad_with_end=False, embedding_size=3840, embedding_key='gemma3_12b', tokenizer_class=SPieceTokenizer, has_end_token=False, pad_to_max_length=False, max_length=99999999, min_length=1, disable_weights=True, tokenizer_args={"add_bos": True, "add_eos": False}, tokenizer_data=tokenizer_data)
super().__init__(tokenizer, pad_with_end=False, embedding_size=3840, embedding_key='gemma3_12b', tokenizer_class=SPieceTokenizer, has_end_token=False, pad_to_max_length=False, max_length=99999999, min_length=512, pad_left=True, disable_weights=True, tokenizer_args={"add_bos": True, "add_eos": False}, tokenizer_data=tokenizer_data)
def state_dict(self):
return {"spiece_model": self.tokenizer.serialize_model()}
@ -97,6 +97,7 @@ class LTXAVTEModel(torch.nn.Module):
token_weight_pairs = token_weight_pairs["gemma3_12b"]
out, pooled, extra = self.gemma3_12b.encode_token_weights(token_weight_pairs)
out = out[:, :, -torch.sum(extra["attention_mask"]).item():]
out_device = out.device
if comfy.model_management.should_use_bf16(self.execution_device):
out = out.to(device=self.execution_device, dtype=torch.bfloat16)
@ -138,6 +139,7 @@ class LTXAVTEModel(torch.nn.Module):
token_weight_pairs = token_weight_pairs.get("gemma3_12b", [])
num_tokens = sum(map(lambda a: len(a), token_weight_pairs))
num_tokens = max(num_tokens, 64)
return num_tokens * constant * 1024 * 1024
def ltxav_te(dtype_llama=None, llama_quantization_metadata=None):