running gradio_ootd.py, cuda error

[TigerHH6866]

(ootd) root@autodl-container-cf29119c3c-0ecee78c:~/autodl-tmp/OOTDiffusion/run# python gradio_ootd.py Loading pipeline components...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7/7 [00:01<00:00, 6.08it/s] text_config_dict is provided which will be used to initialize CLIPTextConfig. The value text_config["id2label"] will be overriden. text_config_dict is provided which will be used to initialize CLIPTextConfig. The value text_config["bos_token_id"] will be overriden. text_config_dict is provided which will be used to initialize CLIPTextConfig. The value text_config["eos_token_id"] will be overriden. Loading pipeline components...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7/7 [00:00<00:00, 11.18it/s] Traceback (most recent call last): File "/root/autodl-tmp/OOTDiffusion/run/gradio_ootd.py", line 31, in ootd_model_dc = OOTDiffusionDC(1) File "/root/autodl-tmp/OOTDiffusion/ootd/inference_ootd_dc.py", line 74, in init ).to(self.gpu_id) File "/root/miniconda3/envs/ootd/lib/python3.10/site-packages/diffusers/pipelines/pipeline_utils.py", line 864, in to module.to(device, dtype) File "/root/miniconda3/envs/ootd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1145, in to return self._apply(convert) File "/root/miniconda3/envs/ootd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 797, in _apply module._apply(fn) File "/root/miniconda3/envs/ootd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 820, in _apply param_applied = fn(param) File "/root/miniconda3/envs/ootd/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1143, in convert return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking) RuntimeError: CUDA error: invalid device ordinal CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1. Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.

[levihsu]

Our gradio demo requires 2 GPUs. Since ootd_dc checkpoints are not released yet, you may simply comment out the code involving ootd_dc for now.

[TigerHH6866]

Our gradio demo requires 2 GPUs. Since ootd_dc checkpoints are not released yet, you may simply comment the code involving ootd_dc for now.

o thx

[karthikg-09]

Our gradio demo requires 2 GPUs. Since ootd_dc checkpoints are not released yet, you may simply comment the code involving ootd_dc for now.

Any ETA for ootd_dc?

[levihsu]

Our gradio demo requires 2 GPUs. Since ootd_dc checkpoints are not released yet, you may simply comment the code involving ootd_dc for now.

Any ETA for ootd_dc?

Available now.