diff --git a/ldm/gfpgan/gfpgan_tools.py b/ldm/gfpgan/gfpgan_tools.py
index 0de706ae42..72df72455a 100644
--- a/ldm/gfpgan/gfpgan_tools.py
+++ b/ldm/gfpgan/gfpgan_tools.py
@@ -75,52 +75,50 @@ def run_gfpgan(image, strength, seed, upsampler_scale=4):
 
 def _load_gfpgan_bg_upsampler(bg_upsampler, upsampler_scale, bg_tile=400):
     if bg_upsampler == 'realesrgan':
-        if not torch.cuda.is_available():  # CPU
-            warnings.warn(
-                'The unoptimized RealESRGAN is slow on CPU. We do not use it. '
-                'If you really want to use it, please modify the corresponding codes.'
-            )
-            bg_upsampler = None
+        if not torch.cuda.is_available(): # CPU or MPS on M1
+            use_half_precision = False
         else:
-            model_path = {
-                2: 'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth',
-                4: 'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth',
-            }
+            use_half_precision = True
 
-            if upsampler_scale not in model_path:
-                return None
+        model_path = {
+            2: 'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth',
+            4: 'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth',
+        }
 
-            from basicsr.archs.rrdbnet_arch import RRDBNet
-            from realesrgan import RealESRGANer
+        if upsampler_scale not in model_path:
+            return None
 
-            if upsampler_scale == 4:
-                model = RRDBNet(
-                    num_in_ch=3,
-                    num_out_ch=3,
-                    num_feat=64,
-                    num_block=23,
-                    num_grow_ch=32,
-                    scale=4,
-                )
-            if upsampler_scale == 2:
-                model = RRDBNet(
-                    num_in_ch=3,
-                    num_out_ch=3,
-                    num_feat=64,
-                    num_block=23,
-                    num_grow_ch=32,
-                    scale=2,
-                )
+        from basicsr.archs.rrdbnet_arch import RRDBNet
+        from realesrgan import RealESRGANer
 
-            bg_upsampler = RealESRGANer(
-                scale=upsampler_scale,
-                model_path=model_path[upsampler_scale],
-                model=model,
-                tile=bg_tile,
-                tile_pad=10,
-                pre_pad=0,
-                half=True,
-            )  # need to set False in CPU mode
+        if upsampler_scale == 4:
+            model = RRDBNet(
+                num_in_ch=3,
+                num_out_ch=3,
+                num_feat=64,
+                num_block=23,
+                num_grow_ch=32,
+                scale=4,
+            )
+        if upsampler_scale == 2:
+            model = RRDBNet(
+                num_in_ch=3,
+                num_out_ch=3,
+                num_feat=64,
+                num_block=23,
+                num_grow_ch=32,
+                scale=2,
+            )
+
+        bg_upsampler = RealESRGANer(
+            scale=upsampler_scale,
+            model_path=model_path[upsampler_scale],
+            model=model,
+            tile=bg_tile,
+            tile_pad=10,
+            pre_pad=0,
+            half=use_half_precision,
+        )
     else:
         bg_upsampler = None