sdxl support cpu_text_encoder

iopaint/model/helper/cpu_text_encoder.py

@@ -8,6 +8,7 @@ class CPUTextEncoderWrapper(PreTrainedModel):
     def __init__(self, text_encoder, torch_dtype):
         super().__init__(text_encoder.config)
         self.config = text_encoder.config
+        # cpu not support float16
         self.text_encoder = text_encoder.to(torch.device("cpu"), non_blocking=True)
         self.text_encoder = self.text_encoder.to(torch.float32, non_blocking=True)
         self.torch_dtype = torch_dtype
@@ -16,11 +17,15 @@ class CPUTextEncoderWrapper(PreTrainedModel):
 
     def __call__(self, x, **kwargs):
         input_device = x.device
-        return [
-            self.text_encoder(x.to(self.text_encoder.device), **kwargs)[0]
-            .to(input_device)
-            .to(self.torch_dtype)
-        ]
+        original_output = self.text_encoder(x.to(self.text_encoder.device), **kwargs)
+        for k, v in original_output.items():
+            if isinstance(v, tuple):
+                original_output[k] = [
+                    v[i].to(input_device).to(self.torch_dtype) for i in range(len(v))
+                ]
+            else:
+                original_output[k] = v.to(input_device).to(self.torch_dtype)
+        return original_output
 
     @property
     def dtype(self):

iopaint/model/sdxl.py

@@ -9,6 +9,7 @@ from loguru import logger
 from iopaint.schema import InpaintRequest, ModelType
 
 from .base import DiffusionInpaintModel
+from .helper.cpu_text_encoder import CPUTextEncoderWrapper
 from .utils import handle_from_pretrained_exceptions, get_torch_dtype, enable_low_mem
 
 
@@ -37,11 +38,11 @@ class SDXL(DiffusionInpaintModel):
             )
         else:
             model_kwargs = {**kwargs.get("pipe_components", {})}
-            if 'vae' not in model_kwargs:
+            if "vae" not in model_kwargs:
                 vae = AutoencoderKL.from_pretrained(
                     "madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch_dtype
                 )
-                model_kwargs['vae'] = vae
+                model_kwargs["vae"] = vae
             self.model = handle_from_pretrained_exceptions(
                 StableDiffusionXLInpaintPipeline.from_pretrained,
                 pretrained_model_name_or_path=self.model_id_or_path,
@@ -58,7 +59,13 @@ class SDXL(DiffusionInpaintModel):
         else:
             self.model = self.model.to(device)
             if kwargs["sd_cpu_textencoder"]:
-                logger.warning("Stable Diffusion XL not support run TextEncoder on CPU")
+                logger.info("Run Stable Diffusion TextEncoder on CPU")
+                self.model.text_encoder = CPUTextEncoderWrapper(
+                    self.model.text_encoder, torch_dtype
+                )
+                self.model.text_encoder_2 = CPUTextEncoderWrapper(
+                    self.model.text_encoder_2, torch_dtype
+                )
 
         self.callback = kwargs.pop("callback", None)