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

unwrap model on multi gpu

examples/dreambooth/train_dreambooth.py

@@ -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)