remove torch_dtype from usage scripts.

Author: sayakpaul

scripts/convert_gligen_to_diffusers.py

@@ -576,6 +576,6 @@ def convert_gligen_to_diffusers(
     )
 
     if args.half:
-        pipe.to(torch_dtype=torch.float16)
+        pipe.to(dtype=torch.float16)
 
     pipe.save_pretrained(args.dump_path)

scripts/convert_original_stable_diffusion_to_diffusers.py

@@ -179,7 +179,7 @@
     )
 
     if args.half:
-        pipe.to(torch_dtype=torch.float16)
+        pipe.to(dtype=torch.float16)
 
     if args.controlnet:
         # only save the controlnet model

scripts/convert_zero123_to_diffusers.py

@@ -801,6 +801,6 @@ def convert_from_original_zero123_ckpt(checkpoint_path, original_config_file, ex
     )
 
     if args.half:
-        pipe.to(torch_dtype=torch.float16)
+        pipe.to(dtype=torch.float16)
 
     pipe.save_pretrained(args.dump_path, safe_serialization=args.to_safetensors)

src/diffusers/pipelines/pipeline_utils.py

@@ -776,7 +776,7 @@ def to(self, *args, **kwargs):
             [`DiffusionPipeline`]: The pipeline converted to specified `dtype` and/or `dtype`.
         """
         dtype = kwargs.pop("dtype", None)
-        device= kwargs.pop("device", None)
+        device = kwargs.pop("device", None)
         silence_dtype_warnings = kwargs.pop("silence_dtype_warnings", False)
 
         dtype_arg = None
@@ -851,12 +851,12 @@ def module_is_offloaded(module):
 
             if is_loaded_in_8bit and dtype is not None:
                 logger.warning(
-                    f"The module '{module.__class__.__name__}' has been loaded in 8bit and conversion to {torch_dtype} is not yet supported. Module is still in 8bit precision."
+                    f"The module '{module.__class__.__name__}' has been loaded in 8bit and conversion to {dtype} is not yet supported. Module is still in 8bit precision."
                 )
 
             if is_loaded_in_8bit and device is not None:
                 logger.warning(
-                    f"The module '{module.__class__.__name__}' has been loaded in 8bit and moving it to {torch_dtype} via `.to()` is not yet supported. Module is still on {module.device}."
+                    f"The module '{module.__class__.__name__}' has been loaded in 8bit and moving it to {dtype} via `.to()` is not yet supported. Module is still on {module.device}."
                 )
             else:
                 module.to(device, dtype)

tests/pipelines/animatediff/test_animatediff.py

@@ -218,7 +218,7 @@ def test_to_dtype(self):
         model_dtypes = [component.dtype for component in pipe.components.values() if hasattr(component, "dtype")]
         self.assertTrue(all(dtype == torch.float32 for dtype in model_dtypes))
 
-        pipe.to(torch_dtype=torch.float16)
+        pipe.to(dtype=torch.float16)
         model_dtypes = [component.dtype for component in pipe.components.values() if hasattr(component, "dtype")]
         self.assertTrue(all(dtype == torch.float16 for dtype in model_dtypes))
 

tests/pipelines/animatediff/test_animatediff_video2video.py

@@ -224,7 +224,7 @@ def test_to_dtype(self):
         model_dtypes = [component.dtype for component in pipe.components.values() if hasattr(component, "dtype")]
         self.assertTrue(all(dtype == torch.float32 for dtype in model_dtypes))
 
-        pipe.to(torch_dtype=torch.float16)
+        pipe.to(dtype=torch.float16)
         model_dtypes = [component.dtype for component in pipe.components.values() if hasattr(component, "dtype")]
         self.assertTrue(all(dtype == torch.float16 for dtype in model_dtypes))
 

tests/pipelines/audioldm2/test_audioldm2.py

@@ -483,7 +483,7 @@ def test_to_dtype(self):
         self.assertTrue(all(dtype == torch.float32 for dtype in model_dtypes.values()))
 
         # Once we send to fp16, all params are in half-precision, including the logit scale
-        pipe.to(torch_dtype=torch.float16)
+        pipe.to(dtype=torch.float16)
         model_dtypes = {key: component.dtype for key, component in components.items() if hasattr(component, "dtype")}
         self.assertTrue(all(dtype == torch.float16 for dtype in model_dtypes.values()))
 

tests/pipelines/musicldm/test_musicldm.py

@@ -400,7 +400,7 @@ def test_to_dtype(self):
         self.assertTrue(all(dtype == torch.float32 for dtype in model_dtypes.values()))
 
         # Once we send to fp16, all params are in half-precision, including the logit scale
-        pipe.to(torch_dtype=torch.float16)
+        pipe.to(dtype=torch.float16)
         model_dtypes = {key: component.dtype for key, component in components.items() if hasattr(component, "dtype")}
         self.assertTrue(all(dtype == torch.float16 for dtype in model_dtypes.values()))
 

tests/pipelines/pia/test_pia.py

@@ -231,7 +231,7 @@ def test_to_dtype(self):
         model_dtypes = [component.dtype for component in pipe.components.values() if hasattr(component, "dtype")]
         self.assertTrue(all(dtype == torch.float32 for dtype in model_dtypes))
 
-        pipe.to(torch_dtype=torch.float16)
+        pipe.to(dtype=torch.float16)
         model_dtypes = [component.dtype for component in pipe.components.values() if hasattr(component, "dtype")]
         self.assertTrue(all(dtype == torch.float16 for dtype in model_dtypes))
 

tests/pipelines/stable_video_diffusion/test_stable_video_diffusion.py

@@ -396,7 +396,7 @@ def test_to_dtype(self):
         model_dtypes = [component.dtype for component in pipe.components.values() if hasattr(component, "dtype")]
         self.assertTrue(all(dtype == torch.float32 for dtype in model_dtypes))
 
-        pipe.to(torch_dtype=torch.float16)
+        pipe.to(dtype=torch.float16)
         model_dtypes = [component.dtype for component in pipe.components.values() if hasattr(component, "dtype")]
         self.assertTrue(all(dtype == torch.float16 for dtype in model_dtypes))