IDM-VTON一键换衣工具 8G显存可用

本软件完全免费，请勿上当受骗。教程：【B站 秋雨画风】 【网站： py99.xyz】 The config attributes {'decay': 0.9999, 'inv_gamma': 1.0, 'min_decay': 0.0, 'optimization_step': 37000, 'power': 0.6666666666666666, 'update_after_step': 0, 'use_ema_warmup': False} were passed to UNet2DConditionModel, but are not expected and will be ignored. Please verify your config.json configuration file. The config attributes {'decay': 0.9999, 'inv_gamma': 1.0, 'min_decay': 0.0, 'optimization_step': 37000, 'power': 0.6666666666666666, 'update_after_step': 0, 'use_ema_warmup': False} were passed to UNet2DConditionModel, but are not expected and will be ignored. Please verify your config.json configuration file. Some weights of the model checkpoint were not used when initializing UNet2DConditionModel: ['add_embedding.linear_1.bias, add_embedding.linear_1.weight, add_embedding.linear_2.bias, add_embedding.linear_2.weight'] Loading pipeline components...: 100%|████████████████████████████████████████████████████| 8/8 [00:00<00:00, 29.94it/s] ----------------------低显存模式-------------------- 100%|████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:02<00:00, 2.37s/it] 100%|████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:04<00:00, 4.40s/it] torch\functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at C:\cb\pytorch_1000000000000\work\aten\src\ATen\native\TensorShape.cpp:3484.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] Some weights of the model checkpoint were not used when initializing UNet2DConditionModel: ['add_embedding.linear_1.bias, add_embedding.linear_1.weight, add_embedding.linear_2.bias, add_embedding.linear_2.weight'] Loading pipeline components...: 100%|██████████████████████████████████████████████████| 8/8 [00:00<00:00, 1149.87it/s] ----------------------低显存模式-------------------- 100%|████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 1.39it/s] 100%|████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 1.10it/s] 0%| | 0/30 [00:02<?, ?it/s] Traceback (most recent call last): File "view\TryonInterface.py", line 51, in run File "app.py", line 290, in start_tryon File "torch\utils\_contextlib.py", line 115, in decorate_context File "src\tryon_pipeline.py", line 1799, in __call__ File "src\tryon_pipeline.py", line 1799, in torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 20.00 MiB (GPU 0; 12.00 GiB total capacity; 10.84 GiB already allocated; 0 bytes free; 11.29 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF 0%| | 0/30 [00:00> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF The config attributes {'decay': 0.9999, 'inv_gamma': 1.0, 'min_decay': 0.0, 'optimization_step': 37000, 'power': 0.6666666666666666, 'update_after_step': 0, 'use_ema_warmup': False} were passed to UNet2DConditionModel, but are not expected and will be ignored. Please verify your config.json configuration file. Some weights of the model checkpoint were not used when initializing UNet2DConditionModel: ['add_embedding.linear_1.bias, add_embedding.linear_1.weight, add_embedding.linear_2.bias, add_embedding.linear_2.weight'] Loading pipeline components...: 100%|██████████████████████████████████████████████████| 8/8 [00:00<00:00, 1000.55it/s] ----------------------低显存模式-------------------- 100%|████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 1.47it/s] 100%|████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF