fix RuntimeError: Input type (float) and bias type (c10::Half) should be the...

fix RuntimeError: Input type (float) and bias type (c10::Half) should be the same in train_text_to_image_lora.py (#6259)

* fix RuntimeError: Input type (float) and bias type (c10::Half) should be the same

* format source code

* format code

* remove the autocast blocks within the pipeline

* add autocast blocks to pipeline caller in train_text_to_image_lora.py

examples/text_to_image/train_text_to_image_lora.py

@@ -847,10 +847,11 @@ def main():
                 if args.seed is not None:
                     generator = generator.manual_seed(args.seed)
                 images = []
-                for _ in range(args.num_validation_images):
-                    images.append(
-                        pipeline(args.validation_prompt, num_inference_steps=30, generator=generator).images[0]
-                    )
+                with torch.cuda.amp.autocast():
+                    for _ in range(args.num_validation_images):
+                        images.append(
+                            pipeline(args.validation_prompt, num_inference_steps=30, generator=generator).images[0]
+                        )
 
                 for tracker in accelerator.trackers:
                     if tracker.name == "tensorboard":
@@ -916,8 +917,11 @@ def main():
             if args.seed is not None:
                 generator = generator.manual_seed(args.seed)
             images = []
-            for _ in range(args.num_validation_images):
-                images.append(pipeline(args.validation_prompt, num_inference_steps=30, generator=generator).images[0])
+            with torch.cuda.amp.autocast():
+                for _ in range(args.num_validation_images):
+                    images.append(
+                        pipeline(args.validation_prompt, num_inference_steps=30, generator=generator).images[0]
+                    )
 
             for tracker in accelerator.trackers:
                 if len(images) != 0: