Fix Wan I2V prepare_latents dtype (#11371)

update

src/diffusers/pipelines/wan/pipeline_wan_i2v.py

@@ -409,7 +409,7 @@ class WanImageToVideoPipeline(DiffusionPipeline, WanLoraLoaderMixin):
                 [image, image.new_zeros(image.shape[0], image.shape[1], num_frames - 2, height, width), last_image],
                 dim=2,
             )
-        video_condition = video_condition.to(device=device, dtype=dtype)
+        video_condition = video_condition.to(device=device, dtype=self.vae.dtype)
 
         latents_mean = (
             torch.tensor(self.vae.config.latents_mean)
@@ -429,6 +429,7 @@ class WanImageToVideoPipeline(DiffusionPipeline, WanLoraLoaderMixin):
             latent_condition = retrieve_latents(self.vae.encode(video_condition), sample_mode="argmax")
             latent_condition = latent_condition.repeat(batch_size, 1, 1, 1, 1)
 
+        latent_condition = latent_condition.to(dtype)
         latent_condition = (latent_condition - latents_mean) * latents_std
 
         mask_lat_size = torch.ones(batch_size, 1, num_frames, latent_height, latent_width)