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[flux lora training] fix t5 training bug #10845

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[flux lora training] fix t5 training bug #10845

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25f5e06
fix t5 training bug
linoytsaban Feb 20, 2025
213c155
Merge branch 'main' into bug-fix
linoytsaban Feb 20, 2025
5c47abf
Merge branch 'main' into bug-fix
linoytsaban Feb 26, 2025
8c1751e
Apply style fixes
github-actions[bot] Feb 26, 2025
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10 changes: 3 additions & 7 deletions examples/advanced_diffusion_training/train_dreambooth_lora_flux_advanced.py
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Original file line number Diff line number Diff line change
Expand Up @@ -880,9 +880,7 @@ def save_embeddings(self, file_path: str):
idx_to_text_encoder_name = {0: "clip_l", 1: "t5"}
for idx, text_encoder in enumerate(self.text_encoders):
train_ids = self.train_ids if idx == 0 else self.train_ids_t5
embeds = (
text_encoder.text_model.embeddings.token_embedding if idx == 0 else text_encoder.encoder.embed_tokens
)
embeds = text_encoder.text_model.embeddings.token_embedding if idx == 0 else text_encoder.shared
assert embeds.weight.data.shape[0] == len(self.tokenizers[idx]), "Tokenizers should be the same."
new_token_embeddings = embeds.weight.data[train_ids]

Expand All @@ -904,9 +902,7 @@ def device(self):
@torch.no_grad()
def retract_embeddings(self):
for idx, text_encoder in enumerate(self.text_encoders):
embeds = (
text_encoder.text_model.embeddings.token_embedding if idx == 0 else text_encoder.encoder.embed_tokens
)
embeds = text_encoder.text_model.embeddings.token_embedding if idx == 0 else text_encoder.shared
index_no_updates = self.embeddings_settings[f"index_no_updates_{idx}"]
embeds.weight.data[index_no_updates] = (
self.embeddings_settings[f"original_embeddings_{idx}"][index_no_updates]
Expand Down Expand Up @@ -1749,7 +1745,7 @@ def load_model_hook(models, input_dir):
if args.enable_t5_ti: # whether to do pivotal tuning/textual inversion for T5 as well
text_lora_parameters_two = []
for name, param in text_encoder_two.named_parameters():
if "token_embedding" in name:
if "shared" in name:
# ensure that dtype is float32, even if rest of the model that isn't trained is loaded in fp16
param.data = param.to(dtype=torch.float32)
param.requires_grad = True
Expand Down