kabachuha / sd-webui-text2video

Auto1111 extension implementing text2video diffusion models (like ModelScope or VideoCrafter) using only Auto1111 webui dependencies
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[Bug]: #119

Closed mhussar closed 1 year ago

mhussar commented 1 year ago

Is there an existing issue for this?

Are you using the latest version of the extension?

What happened?

getting this error just for modelscope: Exception occurred: GaussianDiffusion.ddim_sample_loop() got an unexpected keyword argument 'mask'

Steps to reproduce the problem

  1. Go to .... text2Video and enter in simple prompt cat running
  2. Press ....generate
  3. ... get Exception occurred: GaussianDiffusion.ddim_sample_loop() got an unexpected keyword argument 'mask' in the command window

What should have happened?

before the recent update modelscope was working fine creating a video

WebUI and Deforum extension Commit IDs

webui commit id - txt2vid commit id -

What GPU were you using for launching?

rtx 3090 24 vram

On which platform are you launching the webui backend with the extension?

Local PC setup (Windows)

Settings

default settings nothing fancy

Console logs

not sure where

Additional information

No response

kabachuha commented 1 year ago

If you're on Windows, install Windows Terminal and launch your webui-user.bat inside it. Once the bug occurs, right-click the tab and click save or copy logs

It's hard to get the cause of the error without the traceback

mhussar commented 1 year ago

text2video — The model selected is: ModelScope text2video extension for auto1111 webui Git commit: cac54c26 (Thu Apr 6 16:46:13 2023) Starting text2video Pipeline setup config namespace(framework='pytorch', task='text-to-video-synthesis', model={'type': 'latent-text-to-video-synthesis', 'model_args': {'ckpt_clip': 'open_clip_pytorch_model.bin', 'ckpt_unet': 'text2video_pytorch_model.pth', 'ckpt_autoencoder': 'VQGAN_autoencoder.pth', 'max_frames': 16, 'tiny_gpu': 1}, 'model_cfg': {'unet_in_dim': 4, 'unet_dim': 320, 'unet_y_dim': 768, 'unet_context_dim': 1024, 'unet_out_dim': 4, 'unet_dim_mult': [1, 2, 4, 4], 'unet_num_heads': 8, 'unet_head_dim': 64, 'unet_res_blocks': 2, 'unet_attn_scales': [1, 0.5, 0.25], 'unet_dropout': 0.1, 'temporal_attention': 'True', 'num_timesteps': 1000, 'mean_type': 'eps', 'var_type': 'fixed_small', 'loss_type': 'mse'}}, pipeline={'type': 'latent-text-to-video-synthesis'}) device cuda Working in txt2vid mode 0%| | 0/1 [00:00<?, ?it/s]latents torch.Size([1, 4, 24, 32, 32]) tensor(-0.0051, device='cuda:0') tensor(0.9974, device='cuda:0') Traceback (most recent call last): File "D:\Projects\Personal\AI_ImageCreation\StableDiffusion1111_010723\stable-diffusion-webui\extensions\sd-webui-modelscope-text2video\scripts\text2vid.py", line 92, in process process_modelscope(skip_video_creation, ffmpeg_location, ffmpeg_crf, ffmpeg_preset, fps, add_soundtrack, soundtrack_path, \ File "D:\Projects\Personal\AI_ImageCreation\StableDiffusion1111_010723\stable-diffusion-webui\extensions\sd-webui-modelscope-text2video\scripts\text2vid.py", line 234, in processmodelscope samples, = pipe.infer(prompt, n_prompt, steps, frames, seed + batch if seed != -1 else -1, cfg_scale, File "D:\Projects\Personal\AI_ImageCreation\StableDiffusion1111_010723\stable-diffusion-webui/extensions/sd-webui-text2video/scripts\modelscope\t2v_pipeline.py", line 245, in infer x0 = self.diffusion.ddim_sample_loop( File "D:\Projects\Personal\AI_ImageCreation\StableDiffusion1111_010723\stable-diffusion-webui\venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context return func(*args, **kwargs) TypeError: GaussianDiffusion.ddim_sample_loop() got an unexpected keyword argument 'mask' Exception occurred: GaussianDiffusion.ddim_sample_loop() got an unexpected keyword argument 'mask'

github-actions[bot] commented 1 year ago

This issue has been closed due to incorrect formatting. Please address the following mistakes and reopen the issue:

github-actions[bot] commented 1 year ago

This issue has been closed due to incorrect formatting. Please address the following mistakes and reopen the issue: