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[dreambooth] fix multi on gpu. (#2088)

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unwrap model on multi gpu
This commit is contained in:
Suraj Patil
2023-01-24 13:23:56 +01:00
committed by GitHub
parent 31336dae3b
commit fc8afa3ab5
1 changed files with 9 additions and 4 deletions
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13
examples/dreambooth/train_dreambooth.py
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@@ -716,11 +716,16 @@ def main(args):
" doing mixed precision training. copy of the weights should still be float32."
)
if unet.dtype != torch.float32:
raise ValueError(f"Unet loaded as datatype {unet.dtype}. {low_precision_error_string}")
if accelerator.unwrap_model(unet).dtype != torch.float32:
raise ValueError(
f"Unet loaded as datatype {accelerator.unwrap_model(unet).dtype}. {low_precision_error_string}"
)
if args.train_text_encoder and text_encoder.dtype != torch.float32:
raise ValueError(f"Text encoder loaded as datatype {text_encoder.dtype}. {low_precision_error_string}")
if args.train_text_encoder and accelerator.unwrap_model(text_encoder).dtype != torch.float32:
raise ValueError(
f"Text encoder loaded as datatype {accelerator.unwrap_model(text_encoder).dtype}."
f" {low_precision_error_string}"
)
# We need to recalculate our total training steps as the size of the training dataloader may have changed.
num_update_steps_per_epoch = math.ceil(len(train_dataloader) / args.gradient_accumulation_steps)