The training details about Unet parameters frozen

[hda-xian]

Why are the UNet parameters frozen during training for SD1v5, but not for SDXL? the haggingface training sdxl script sets " Unet.train() "

* huggingface train sdxl ***** vae.requiresgrad(False) text_encoder_one.requiresgrad(False) text_encoder_two.requiresgrad(False) t2iadapter.train() unet.train()

***Tencent ARC train sd1v5 ** model.cuda() model.eval() # model is contain all models vae ,cliptext return model

***Tencent ARC train sdxl ** vae.requiresgrad(False) text_encoder_one.requiresgrad(False) text_encoder_two.requiresgrad(False) -> the Unet does not set no grad means Unet need grad

[bonlime]

because they have params_to_optimize = adapter.parameters(), and only optimise the adapter's params. But disabling unet grads reduces the memory consumption, they just forgot it

[hda-xian]

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