11个月前
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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
