Traceback (most recent call last): File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/gradio/queueing.py", line 622, in process_events response = await route_utils.call_process_api( File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/gradio/route_utils.py", line 323, in call_process_api output = await app.get_blocks().process_api( File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/gradio/blocks.py", line 2014, in process_api result = await self.call_function( File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/gradio/blocks.py", line 1567, in call_function prediction = await anyio.to_thread.run_sync( # type: ignore File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/anyio/to_thread.py", line 33, in run_sync return await get_asynclib().run_sync_in_worker_thread( File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 877, in run_sync_in_worker_thread return await future File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 807, in run result = context.run(func, *args) File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/gradio/utils.py", line 846, in wrapper response = f(*args, **kwargs) File "/u01/SdProject/app/gradio_ui/gen_video.py", line 38, in generate_video_from_image frames = stable_video(image, pipeline, generator) File "/u01/SdProject/app/service/sd_inference.py", line 226, in stable_video frames = pipeline(image, decode_chunk_size=8, generator=generator).frames[0] File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context return func(*args, **kwargs) File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/diffusers/pipelines/stable_video_diffusion/pipeline_stable_video_diffusion.py", line 576, in __call__ noise_pred = self.unet( File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl return forward_call(*args, **kwargs) File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 465, in _fn return fn(*args, **kwargs) File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl return forward_call(*args, **kwargs) File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/diffusers/models/unets/unet_spatio_temporal_condition.py", line 357, in forward def forward( File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 632, in _fn return fn(*args, **kwargs) File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/_functorch/aot_autograd.py", line 1100, in forward return compiled_fn(full_args) File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 321, in runtime_wrapper all_outs = call_func_at_runtime_with_args( File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/utils.py", line 124, in call_func_at_runtime_with_args out = normalize_as_list(f(args)) File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 667, in inner_fn outs = compiled_fn(args) File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 488, in wrapper return compiled_fn(runtime_args) File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/_inductor/codecache.py", line 1478, in __call__ return self.current_callable(inputs) File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 1008, in run return compiled_fn(new_inputs) File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/_inductor/cudagraph_trees.py", line 398, in deferred_cudagraphify fn, out = cudagraphify(model, inputs, new_static_input_idxs, *args, **kwargs) File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/_inductor/cudagraph_trees.py", line 420, in cudagraphify manager = get_container(device_index).get_tree_manager() File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/_inductor/cudagraph_trees.py", line 341, in get_container container_dict = get_obj(local, "tree_manager_containers") File "/home/self/anaconda3/envs/Diffusers/lib/python3.10/site-packages/torch/_inductor/cudagraph_trees.py", line 336, in get_obj assert torch._C._is_key_in_tls(attr_name) AssertionError

def generate_video_path() -> str: timestamp = int(time.time()) video_dir = settings.VIDEO_DIR if not os.path.exists(video_dir): os.makedirs(video_dir) video_path = os.path.join(video_dir, f"generated_video_{timestamp}.mp4") return video_path def generate_random_seed(): """Generate a random seed.""" return random.randint(0, 2 ** 32 - 1) def stable_video(image, pipeline, generator): image = image.resize((1024, 576)) frames = pipeline(image, decode_chunk_size=8, generator=generator).frames[0] return frames def generate_video_from_image(image, fps, seed): # pipeline = model_loader.pipeline model_path = settings.STABLE_VIDEO_DIFFUSION_DIR pipeline = StableVideoDiffusionPipeline.from_pretrained( model_path, torch_dtype=torch.float16, variant="fp16" ).to('cuda') pipeline.unet = torch.compile(pipeline.unet, mode="reduce-overhead", fullgraph=True) generator = torch.Generator(device=pipeline.device) generator.manual_seed(seed) frames = stable_video(image, pipeline, generator) video_path = generate_video_path() video_path = export_to_video(frames, video_path, fps) return video_path def make_video(): with gr.Block(): with gr.Row(): with gr.Accordion("stable-video", open=False): with gr.Row(): with gr.Column(): with gr.Row(): seed_input = gr.Number(value=generate_random_seed(), show_label=False) generate_seed_button = gr.Button("🎲 Generate Random Seed") generate_seed_button.click(fn=generate_random_seed, outputs=seed_input) with gr.Row(): fps = gr.Slider(label="Frames per second", minimum=7, maximum=25, step=1, value=10) steps_slider = gr.Slider(label="Inference Steps", minimum=0, maximum=100, value=28, info="The number of steps the denoiser removes image noise") with gr.Column(): video_output = gr.Video(label='Video Output', width='600px', height='200px') # Video output img_input = gr.Image(type="pil", width='600px', height='200px') # Image input generate_button = gr.Button("Generate Video") generate_button.click(generate_video_from_image, inputs=[img_input, fps, seed_input], outputs=video_output) # Launch the interface make_video().launch()