diff --git a/ldm/invoke/generator/diffusers_pipeline.py b/ldm/invoke/generator/diffusers_pipeline.py
index 54e9d555af..388d7a3342 100644
--- a/ldm/invoke/generator/diffusers_pipeline.py
+++ b/ldm/invoke/generator/diffusers_pipeline.py
@@ -578,11 +578,20 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             output = InvokeAIStableDiffusionPipelineOutput(images=image, nsfw_content_detected=[], attention_map_saver=result_attention_maps)
             return self.check_for_safety(output, dtype=conditioning_data.dtype)
 
-    def non_noised_latents_from_image(self, init_image, *, device, dtype):
+    def non_noised_latents_from_image(self, init_image, *, device: torch.device, dtype):
         init_image = init_image.to(device=device, dtype=dtype)
         with torch.inference_mode():
+            if device.type == 'mps':
+                # workaround for torch MPS bug that has been fixed in https://github.com/kulinseth/pytorch/pull/222
+                # TODO remove this workaround once kulinseth#222 is merged to pytorch mainline
+                self.vae.to('cpu')
+                init_image = init_image.to('cpu')
             init_latent_dist = self.vae.encode(init_image).latent_dist
             init_latents = init_latent_dist.sample().to(dtype=dtype)  # FIXME: uses torch.randn. make reproducible!
+            if device.type == 'mps':
+                self.vae.to(device)
+                init_latents = init_latents.to(device)
+
         init_latents = 0.18215 * init_latents
         return init_latents