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More targeted embedding_connector loading for LTX2 text encoder (#11992)

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Reduces errors
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Jukka Seppänen 2026-01-22 06:05:06 +02:00 committed by GitHub
parent 3365ad18a5
commit 245f6139b6
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1 changed files with 12 additions and 3 deletions
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15
comfy/text_encoders/lt.py
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@ -118,9 +118,18 @@ class LTXAVTEModel(torch.nn.Module):
sdo = comfy.utils.state_dict_prefix_replace(sd, {"text_embedding_projection.aggregate_embed.weight": "text_embedding_projection.weight", "model.diffusion_model.video_embeddings_connector.": "video_embeddings_connector.", "model.diffusion_model.audio_embeddings_connector.": "audio_embeddings_connector."}, filter_keys=True)
if len(sdo) == 0:
sdo = sd
missing, unexpected = self.load_state_dict(sdo, strict=False)
missing = [k for k in missing if not k.startswith("gemma3_12b.")] # filter out keys that belong to the main gemma model
return (missing, unexpected)
missing_all = []
unexpected_all = []
for prefix, component in [("text_embedding_projection.", self.text_embedding_projection), ("video_embeddings_connector.", self.video_embeddings_connector), ("audio_embeddings_connector.", self.audio_embeddings_connector)]:
component_sd = {k.replace(prefix, ""): v for k, v in sdo.items() if k.startswith(prefix)}
if component_sd:
missing, unexpected = component.load_state_dict(component_sd, strict=False)
missing_all.extend([f"{prefix}{k}" for k in missing])
unexpected_all.extend([f"{prefix}{k}" for k in unexpected])
return (missing_all, unexpected_all)
def memory_estimation_function(self, token_weight_pairs, device=None):
constant = 6.0