Update app.py

app.py

@@ -12,11 +12,23 @@ from diffusers.utils import export_to_video
 from diffusers.utils import load_image
 from PIL import Image
 
-#predictor = None
-#task_type = None
+import torch
+
+torch.backends.cuda.matmul.allow_tf32 = False
+torch.backends.cuda.matmul.allow_bf16_reduced_precision_reduction = False
+torch.backends.cuda.matmul.allow_fp16_reduced_precision_reduction = False
+torch.backends.cudnn.allow_tf32 = False
+torch.backends.cudnn.deterministic = False
+torch.backends.cudnn.benchmark = False
+torch.backends.cuda.preferred_blas_library="cublas"
+torch.backends.cuda.preferred_linalg_library="cusolver"
+torch.set_float32_matmul_precision("highest")
+
+os.putenv("HF_HUB_ENABLE_HF_TRANSFER","1")
+os.environ["SAFETENSORS_FAST_GPU"] = "1"
+
 os.putenv("TOKENIZERS_PARALLELISM","False")
 
-#@spaces.GPU(duration=120)
 def init_predictor():
     global predictor
     predictor = SkyReelsVideoSingleGpuInfer(
@@ -31,8 +43,8 @@ def init_predictor():
         )
     )
     
-@spaces.GPU(duration=80)
-def generate_video(prompt, seed, image, size, steps, frames):
+@spaces.GPU(duration=90)
+def generate_video(prompt, seed, image, size, steps, frames, progress=gr.Progress(track_tqdm=True) ):
     print(f"image:{type(image)}")
     if seed == -1:
         random.seed(time.time())
@@ -53,7 +65,6 @@ def generate_video(prompt, seed, image, size, steps, frames):
     img = load_image(image=image)
     img.resize((320,320), Image.LANCZOS)
     kwargs["image"] = img
-    #global predictor
     output = predictor.inference(kwargs)
     save_dir = f"./"
     video_out_file = f"{save_dir}/{seed}.mp4"
@@ -61,7 +72,6 @@ def generate_video(prompt, seed, image, size, steps, frames):
     export_to_video(output, video_out_file, fps=24)
     return video_out_file
 
-#def create_gradio_interface():
 with gr.Blocks() as demo:
             with gr.Row():
                 image = gr.Image(label="Upload Image", type="filepath")
@@ -95,13 +105,7 @@ with gr.Blocks() as demo:
                 inputs=[prompt, seed, image, size, steps, frames],
                 outputs=[output_video],
             )
-#        return demo
     
-#init_predictor()
-
 if __name__ == "__main__":
-    #import multiprocessing
-    #multiprocessing.freeze_support()
     init_predictor()
-    #demo = create_gradio_interface()
-    demo.launch()
+    demo.launch()