Update gradio_app.py

gradio_app.py

@@ -107,9 +107,10 @@ era3d_pipeline = None
 def gen_mvimg(
     mvimg_model, image, seed, guidance_scale, step, text, neg_text, elevation, backgroud_color
 ):
+    global device
     if seed == 0:
         seed = np.random.randint(1, 65535)
-        global generator, device
+        global generator
         generator = torch.Generator(device)
         generator.manual_seed(seed)
 
@@ -144,6 +145,9 @@ def gen_mvimg(
 
     elif mvimg_model == "Era3D":
         global era3d_pipeline
+        era3d_pipeline.to(device=device)
+        era3d_pipeline.unet.enable_xformers_memory_efficient_attention()
+
         crop_size = 420
         batch = SingleImageDataset(root_dir='', num_views=6, img_wh=[512, 512], bg_color='white', 
             crop_size=crop_size, single_image=image, prompt_embeds_path='apps/third_party/Era3D/data/fixed_prompt_embeds_6view')[0]
@@ -254,7 +258,8 @@ if __name__=="__main__":
         # schema = OmegaConf.structured(TestConfig)
         # cfg = OmegaConf.merge(schema, cfg)
         era3d_pipeline = StableUnCLIPImg2ImgPipeline.from_pretrained(
-            'pengHTYX/MacLab-Era3D-512-6view'
+            'pengHTYX/MacLab-Era3D-512-6view',
+            dtype=torch.float16,
         )
         # enable xformers
         # era3d_pipeline.unet.enable_xformers_memory_efficient_attention()