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Fix some LoRA not trained if gradient checkpointing
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@@ -166,6 +166,9 @@ def train(args):
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if args.gradient_checkpointing: # according to TI example in Diffusers, train is required
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if args.gradient_checkpointing: # according to TI example in Diffusers, train is required
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unet.train()
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unet.train()
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text_encoder.train()
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text_encoder.train()
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# set top parameter requires_grad = True for gradient checkpointing works
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text_encoder.text_model.embeddings.requires_grad_(True)
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else:
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else:
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unet.eval()
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unet.eval()
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text_encoder.eval()
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text_encoder.eval()
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