fix

app.py

@@ -13,6 +13,7 @@ from shap_e.diffusion.sample import sample_latents
 from shap_e.diffusion.gaussian_diffusion import diffusion_from_config
 from shap_e.models.download import load_model, load_config
 from shap_e.util.notebooks import create_pan_cameras, decode_latent_images, create_custom_cameras
+import spaces
 
 from src.utils.train_util import instantiate_from_config
 from src.utils.camera_util import (
@@ -193,6 +194,7 @@ class ShapERenderer:
         self.diffusion = diffusion_from_config(load_config('diffusion'))
         print("Shap-E models loaded!")
 
+    @spaces.GPU(duration=60)
     def generate_views(self, prompt, guidance_scale=15.0, num_steps=64):
         # Generate latents using the text-to-3D model
         batch_size = 1

zero123plus/pipeline.py

@@ -31,6 +31,7 @@ from diffusers.models.attention_processor import (
     AttnProcessor2_0,
 )
 from diffusers.utils.import_utils import is_xformers_available
+import spaces
 
 
 def extract_into_tensor(a, t, x_shape):
@@ -416,6 +417,7 @@ class Zero123PlusPipeline(diffusers.StableDiffusionPipeline):
         image = self.vae.encode(image).latent_dist.sample()
         return image
 
+    @spaces.GPU(duration=60)
     @torch.no_grad()
     def edit_latents(
         self,
@@ -530,6 +532,7 @@ class Zero123PlusPipeline(diffusers.StableDiffusionPipeline):
         latents = scale_latents(latents)
         return latents
 
+    @spaces.GPU(duration=60)
     @torch.no_grad()
     def sdedit(
         self,
@@ -619,6 +622,7 @@ class Zero123PlusPipeline(diffusers.StableDiffusionPipeline):
 
         return ImagePipelineOutput(images=image)
 
+    @spaces.GPU(duration=60)
     @torch.no_grad()
     def refine(
         self,
@@ -1030,6 +1034,7 @@ class Zero123PlusPipeline(diffusers.StableDiffusionPipeline):
             images=image, nsfw_content_detected=has_nsfw_concept
         )
 
+    @spaces.GPU(duration=60)
     @torch.no_grad()
     def __call__(
         self,