Update app.py

app.py

@@ -48,32 +48,15 @@ def download_component_subfolder(repo_id, subfolder):
     )
     return os.path.join(local_dir, subfolder)
 
-def download_model_component(repo_id, subpath):
-    return os.path.join(snapshot_download(
-        repo_id=repo_id,
-        repo_type="model",
-        #local_dir=f"ckpt/{repo_id.replace('/', '--')}",
-        local_dir="ckpt/ROSE",
-        local_dir_use_symlinks=False,
-    ), subpath)
-
-# pretrained_model_path = "./models/Diffusion_Transformer/Wan2.1-Fun-1.3B-InP"
 pretrained_model_path = "alibaba-pai/Wan2.1-Fun-1.3B-InP"
 transformer_path = "Kunbyte/ROSE"
-# config_path = "configs/wan2.1/wan_civitai.yaml"
 config_path = "configs/wan2.1/wan_civitai.yaml"
 config = OmegaConf.load(config_path)
 
-repo_id = "alibaba-pai/Wan2.1-Fun-1.3B-InP"
-
-text_encoder_path = download_component_subfolder(repo_id, config['text_encoder_kwargs'].get('text_encoder_subpath', 'text_encoder'))
-tokenizer_path = download_component_subfolder(repo_id, config['text_encoder_kwargs'].get('tokenizer_subpath', 'tokenizer'))
-image_encoder_path = download_component_subfolder(repo_id, config['image_encoder_kwargs'].get('image_encoder_subpath', 'image_encoder'))
-vae_path = download_component_subfolder(repo_id, config['vae_kwargs'].get('vae_subpath', 'vae'))
-# tokenizer_path = download_model_component("alibaba-pai/Wan2.1-Fun-1.3B-InP", config['text_encoder_kwargs'].get('tokenizer_subpath', 'tokenizer'))
-# text_encoder_path = download_model_component("alibaba-pai/Wan2.1-Fun-1.3B-InP", config['text_encoder_kwargs'].get('text_encoder_subpath', 'text_encoder'))
-# image_encoder_path = download_model_component("alibaba-pai/Wan2.1-Fun-1.3B-InP", config['image_encoder_kwargs'].get('image_encoder_subpath', 'image_encoder'))
-# vae_path = download_model_component("alibaba-pai/Wan2.1-Fun-1.3B-InP", config['vae_kwargs'].get('vae_subpath', 'vae'))
+text_encoder_path = download_component_subfolder("alibaba-pai/Wan2.1-Fun-1.3B-InP", config['text_encoder_kwargs'].get('text_encoder_subpath', 'text_encoder'))
+tokenizer_path = download_component_subfolder("alibaba-pai/Wan2.1-Fun-1.3B-InP", config['text_encoder_kwargs'].get('tokenizer_subpath', 'tokenizer'))
+image_encoder_path = download_component_subfolder("alibaba-pai/Wan2.1-Fun-1.3B-InP", config['image_encoder_kwargs'].get('image_encoder_subpath', 'image_encoder'))
+vae_path = download_component_subfolder("alibaba-pai/Wan2.1-Fun-1.3B-InP", config['vae_kwargs'].get('vae_subpath', 'vae'))
 transformer_path = download_component_subfolder("Kunbyte/ROSE", config['transformer_additional_kwargs'].get('transformer_subpath', 'transformer'))
 
 tokenizer= AutoTokenizer.from_pretrained(tokenizer_path)
@@ -102,30 +85,6 @@ noise_scheduler = FlowMatchEulerDiscreteScheduler(
     **filter_kwargs(FlowMatchEulerDiscreteScheduler, OmegaConf.to_container(config['scheduler_kwargs']))
 )
 
-
-# tokenizer = AutoTokenizer.from_pretrained(
-#     os.path.join(pretrained_model_path, config['text_encoder_kwargs'].get('tokenizer_subpath', 'tokenizer')),
-# )
-# text_encoder = WanT5EncoderModel.from_pretrained(
-#     os.path.join(pretrained_model_path, config['text_encoder_kwargs'].get('text_encoder_subpath', 'text_encoder')),
-#     additional_kwargs=OmegaConf.to_container(config['text_encoder_kwargs']),
-#     low_cpu_mem_usage=True,
-# )
-# clip_image_encoder = CLIPModel.from_pretrained(
-#     os.path.join(pretrained_model_path, config['image_encoder_kwargs'].get('image_encoder_subpath', 'image_encoder')),
-# )
-# vae = AutoencoderKLWan.from_pretrained(
-#     os.path.join(pretrained_model_path, config['vae_kwargs'].get('vae_subpath', 'vae')),
-#     additional_kwargs=OmegaConf.to_container(config['vae_kwargs']),
-# )
-# transformer3d = WanTransformer3DModel.from_pretrained(
-#     os.path.join(transformer_path, config['transformer_additional_kwargs'].get('transformer_subpath', 'transformer')),
-#     transformer_additional_kwargs=OmegaConf.to_container(config['transformer_additional_kwargs']),
-# )
-# noise_scheduler = FlowMatchEulerDiscreteScheduler(
-#     **filter_kwargs(FlowMatchEulerDiscreteScheduler, OmegaConf.to_container(config['scheduler_kwargs']))
-# )
-
 pipeline = WanFunInpaintPipeline(
     vae=vae,
     text_encoder=text_encoder,
@@ -167,6 +126,7 @@ def get_prompt(click_state, click_input):
     }
     return prompt
 
+@spaces.GPU
 # extract frames from upload video
 def get_frames_from_video(video_input, video_state):
     """