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Fix the deletion of SD3 text encoders for Dreambooth/LoRA training if the text encoders are not being trained (#8536)

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* Update train_dreambooth_sd3.py to fix TE garbage collection

* Update train_dreambooth_lora_sd3.py to fix TE garbage collection

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Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
This commit is contained in:
spacepxl
2024-06-16 15:52:33 -04:00
committed by GitHub
parent 6946facf69
commit 8e1b7a084a
2 changed files with 6 additions and 0 deletions
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3
examples/dreambooth/train_dreambooth_lora_sd3.py
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@@ -1316,6 +1316,9 @@ def main(args):
# Clear the memory here
if not train_dataset.custom_instance_prompts:
del tokenizers, text_encoders
# Explicitly delete the objects as well, otherwise only the lists are deleted and the original references remain, preventing garbage collection
del tokenizer_one, tokenizer_two, tokenizer_three
del text_encoder_one, text_encoder_two, text_encoder_three
gc.collect()
if torch.cuda.is_available():
torch.cuda.empty_cache()

3
examples/dreambooth/train_dreambooth_sd3.py
View File

@@ -1347,6 +1347,9 @@ def main(args):
# Clear the memory here
if not args.train_text_encoder and not train_dataset.custom_instance_prompts:
del tokenizers, text_encoders
# Explicitly delete the objects as well, otherwise only the lists are deleted and the original references remain, preventing garbage collection
del tokenizer_one, tokenizer_two, tokenizer_three
del text_encoder_one, text_encoder_two, text_encoder_three
gc.collect()
if torch.cuda.is_available():
torch.cuda.empty_cache()