lllyasviel / Paints-UNDO

Understand Human Behavior to Align True Needs
Apache License 2.0
3.25k stars 287 forks source link

Generate video error #18

Open hl2dm opened 1 month ago

hl2dm commented 1 month ago

Unload to CPU: VideoAutoencoderKL Load to GPU: AutoencoderKL Unload to CPU: AutoencoderKL Load to GPU: CLIPTextModel Unload to CPU: CLIPTextModel Load to GPU: ModifiedUNet Unload to CPU: ModifiedUNet Load to GPU: AutoencoderKL Unload to CPU: AutoencoderKL Load to GPU: CLIPTextModel Unload to CPU: CLIPTextModel Load to GPU: Resampler Load to GPU: ImprovedCLIPVisionModelWithProjection Unload to CPU: Resampler Unload to CPU: ImprovedCLIPVisionModelWithProjection Load to GPU: VideoAutoencoderKL Traceback (most recent call last): File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\gradio\queueing.py", line 528, in process_events response = await route_utils.call_process_api( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\gradio\route_utils.py", line 270, in call_process_api output = await app.get_blocks().process_api( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\gradio\blocks.py", line 1908, in process_api result = await self.call_function( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\gradio\blocks.py", line 1485, in call_function prediction = await anyio.to_thread.run_sync( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\anyio\to_thread.py", line 56, in run_sync return await get_async_backend().run_sync_in_worker_thread( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\anyio_backends_asyncio.py", line 2177, in run_sync_in_worker_thread return await future File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\anyio_backends_asyncio.py", line 859, in run result = context.run(func, args) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\gradio\utils.py", line 808, in wrapper response = f(args, kwargs) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context return func(*args, *kwargs) File "E:\UNDO\Paints-UNDO\gradio_app.py", line 222, in process_video frames, im1, im2 = process_video_inner( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context return func(args, kwargs) File "E:\UNDO\Paints-UNDO\gradio_app.py", line 190, in process_video_inner input_frame_latents, vae_hidden_states = video_pipe.encode_latents(input_frames, return_hidden_states=True) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context return func(*args, kwargs) File "E:\UNDO\Paints-UNDO\diffusers_vdm\pipeline.py", line 102, in encode_latents encoder_posterior, hidden_states = self.vae.encode(x, return_hidden_states=return_hidden_states) File "E:\UNDO\Paints-UNDO\diffusers_vdm\vae.py", line 804, in encode h, hidden = self.encoder(x, return_hidden_states) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl return self._call_impl(*args, *kwargs) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl return forward_call(args, kwargs) File "E:\UNDO\Paints-UNDO\diffusers_vdm\vae.py", line 249, in forward h = self.mid.attn_1(h) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl return self._call_impl(*args, kwargs) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl return forward_call(*args, kwargs) File "E:\UNDO\Paints-UNDO\diffusersvdm\vae.py", line 411, in forward h = self.attention(h_) File "E:\UNDO\Paints-UNDO\diffusers_vdm\vae.py", line 397, in attention out = chunked_attention( File "E:\UNDO\Paints-UNDO\diffusers_vdm\vae.py", line 36, in chunked_attention out = xformers.ops.memory_efficient_attention(q, k, v) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\xformers\ops\fmha__init.py", line 276, in memory_efficient_attention return _memory_efficient_attention( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\xformers\ops\fmha\init.py", line 395, in _memory_efficient_attention return _memory_efficient_attention_forward( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\xformers\ops\fmha\init__.py", line 414, in _memory_efficient_attention_forward op = _dispatch_fw(inp, False) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\xformers\ops\fmha\dispatch.py", line 119, in _dispatch_fw return _run_priority_list( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\xformers\ops\fmha\dispatch.py", line 55, in _run_priority_list raise NotImplementedError(msg) NotImplementedError: No operator found for memory_efficient_attention_forward with inputs: query : shape=(2, 2688, 1, 512) (torch.float16) key : shape=(2, 2688, 1, 512) (torch.float16) value : shape=(2, 2688, 1, 512) (torch.float16) attn_bias : <class 'NoneType'> p : 0.0 decoderF is not supported because: max(query.shape[-1] != value.shape[-1]) > 128 xFormers wasn't build with CUDA support attn_bias type is <class 'NoneType'> operator wasn't built - see python -m xformers.info for more info flshattF@0.0.0 is not supported because: max(query.shape[-1] != value.shape[-1]) > 256 xFormers wasn't build with CUDA support operator wasn't built - see python -m xformers.info for more info cutlassF is not supported because: xFormers wasn't build with CUDA support operator wasn't built - see python -m xformers.info for more info smallkF is not supported because: max(query.shape[-1] != value.shape[-1]) > 32 xFormers wasn't build with CUDA support dtype=torch.float16 (supported: {torch.float32}) operator wasn't built - see python -m xformers.info for more info unsupported embed per head: 512 Unload to CPU: VideoAutoencoderKL Load to GPU: CLIPTextModel Unload to CPU: CLIPTextModel Load to GPU: Resampler Load to GPU: ImprovedCLIPVisionModelWithProjection Unload to CPU: Resampler Unload to CPU: ImprovedCLIPVisionModelWithProjection Load to GPU: VideoAutoencoderKL Traceback (most recent call last): File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\gradio\queueing.py", line 528, in process_events response = await route_utils.call_process_api( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\gradio\route_utils.py", line 270, in call_process_api output = await app.get_blocks().process_api( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\gradio\blocks.py", line 1908, in process_api result = await self.call_function( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\gradio\blocks.py", line 1485, in call_function prediction = await anyio.to_thread.run_sync( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\anyio\to_thread.py", line 56, in run_sync return await get_async_backend().run_sync_in_worker_thread( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\anyio_backends_asyncio.py", line 2177, in run_sync_in_worker_thread return await future File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\anyio_backends_asyncio.py", line 859, in run result = context.run(func, args) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\gradio\utils.py", line 808, in wrapper response = f(args, kwargs) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context return func(*args, kwargs) File "E:\UNDO\Paints-UNDO\gradio_app.py", line 222, in process_video frames, im1, im2 = process_video_inner( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context return func(*args, kwargs) File "E:\UNDO\Paints-UNDO\gradio_app.py", line 190, in process_video_inner input_frame_latents, vae_hidden_states = video_pipe.encode_latents(input_frames, return_hidden_states=True) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context return func(*args, *kwargs) File "E:\UNDO\Paints-UNDO\diffusers_vdm\pipeline.py", line 102, in encode_latents encoder_posterior, hidden_states = self.vae.encode(x, return_hidden_states=return_hidden_states) File "E:\UNDO\Paints-UNDO\diffusers_vdm\vae.py", line 804, in encode h, hidden = self.encoder(x, return_hidden_states) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl return self._call_impl(args, kwargs) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl return forward_call(*args, kwargs) File "E:\UNDO\Paints-UNDO\diffusers_vdm\vae.py", line 249, in forward h = self.mid.attn_1(h) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl return self._call_impl(*args, *kwargs) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl return forward_call(args, kwargs) File "E:\UNDO\Paints-UNDO\diffusersvdm\vae.py", line 411, in forward h = self.attention(h_) File "E:\UNDO\Paints-UNDO\diffusers_vdm\vae.py", line 397, in attention out = chunked_attention( File "E:\UNDO\Paints-UNDO\diffusers_vdm\vae.py", line 36, in chunked_attention out = xformers.ops.memory_efficient_attention(q, k, v) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\xformers\ops\fmha__init.py", line 276, in memory_efficient_attention return _memory_efficient_attention( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\xformers\ops\fmha\init.py", line 395, in _memory_efficient_attention return _memory_efficient_attention_forward( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\xformers\ops\fmha\init__.py", line 414, in _memory_efficient_attention_forward op = _dispatch_fw(inp, False) File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\xformers\ops\fmha\dispatch.py", line 119, in _dispatch_fw return _run_priority_list( File "C:\Users\DM.conda\envs\paints_undo\lib\site-packages\xformers\ops\fmha\dispatch.py", line 55, in _run_priority_list raise NotImplementedError(msg) NotImplementedError: No operator found for memory_efficient_attention_forward with inputs: query : shape=(2, 2688, 1, 512) (torch.float16) key : shape=(2, 2688, 1, 512) (torch.float16) value : shape=(2, 2688, 1, 512) (torch.float16) attn_bias : <class 'NoneType'> p : 0.0 decoderF is not supported because: max(query.shape[-1] != value.shape[-1]) > 128 xFormers wasn't build with CUDA support attn_bias type is <class 'NoneType'> operator wasn't built - see python -m xformers.info for more info flshattF@0.0.0 is not supported because: max(query.shape[-1] != value.shape[-1]) > 256 xFormers wasn't build with CUDA support operator wasn't built - see python -m xformers.info for more info cutlassF is not supported because: xFormers wasn't build with CUDA support operator wasn't built - see python -m xformers.info for more info smallkF is not supported because: max(query.shape[-1] != value.shape[-1]) > 32 xFormers wasn't build with CUDA support dtype=torch.float16 (supported: {torch.float32}) operator wasn't built - see python -m xformers.info for more info unsupported embed per head: 512

Windows 11 

13th Gen Intel(R) Core(TM) i7-13700K 3.40 GHz RTX 4090

hl2dm commented 1 month ago

Fix PyTorch and xformers compatibility issues

This resolves version conflicts and ensures proper GPU utilization.