My running outputs remain the same for a long time

[hosea7456]

Hi, When I running the code, the outputs remain the same, it can't keep on running.

2021-07-21 12:24:37 | INFO | yolox.core.trainer:130 - Model Summary: Params: 99.00M, Gflops: 281.52
2021-07-21 12:24:37 | INFO | apex.amp.frontend:328 - Selected optimization level O1: Insert automatic casts around Pytorch functions and Tensor methods.
2021-07-21 12:24:37 | INFO | apex.amp.frontend:329 - Defaults for this optimization level are:
2021-07-21 12:24:37 | INFO | apex.amp.frontend:331 - enabled : True
2021-07-21 12:24:37 | INFO | apex.amp.frontend:331 - opt_level : O1
2021-07-21 12:24:37 | INFO | apex.amp.frontend:331 - cast_model_type : None
2021-07-21 12:24:37 | INFO | apex.amp.frontend:331 - patch_torch_functions : True
2021-07-21 12:24:37 | INFO | apex.amp.frontend:331 - keep_batchnorm_fp32 : None
2021-07-21 12:24:37 | INFO | apex.amp.frontend:331 - master_weights : None
2021-07-21 12:24:37 | INFO | apex.amp.frontend:331 - loss_scale : dynamic
2021-07-21 12:24:37 | INFO | apex.amp.frontend:336 - Processing user overrides (additional kwargs that are not None)...
2021-07-21 12:24:37 | INFO | apex.amp.frontend:354 - After processing overrides, optimization options are:
2021-07-21 12:24:37 | INFO | apex.amp.frontend:356 - enabled : True
2021-07-21 12:24:37 | INFO | apex.amp.frontend:356 - opt_level : O1
2021-07-21 12:24:37 | INFO | apex.amp.frontend:356 - cast_model_type : None
2021-07-21 12:24:37 | INFO | apex.amp.frontend:356 - patch_torch_functions : True
2021-07-21 12:24:37 | INFO | apex.amp.frontend:356 - keep_batchnorm_fp32 : None
2021-07-21 12:24:37 | INFO | apex.amp.frontend:356 - master_weights : None
2021-07-21 12:24:37 | INFO | apex.amp.frontend:356 - loss_scale : dynamic
2021-07-21 12:24:37 | INFO | apex.amp.scaler:69 - Warning: multi_tensor_applier fused unscale kernel is unavailable, possibly because apex was installed without --cuda_ext --cpp_ext. Using Python fallback. Original ImportError was: ModuleNotFoundError("No module named 'amp_C'")
2021-07-21 12:24:37 | INFO | yolox.core.trainer:283 - loading checkpoint for fine tuning
2021-07-21 12:24:38 | WARNING | yolox.utils.checkpoint:26 - Shape of head.cls_preds.0.weight in checkpoint is torch.Size([80, 320, 1, 1]), while shape of head.cls_preds.0.weight in model is torch.Size([3, 320, 1, 1]).
2021-07-21 12:24:38 | WARNING | yolox.utils.checkpoint:26 - Shape of head.cls_preds.0.bias in checkpoint is torch.Size([80]), while shape of head.cls_preds.0.bias in model is torch.Size([3]).
2021-07-21 12:24:38 | WARNING | yolox.utils.checkpoint:26 - Shape of head.cls_preds.1.weight in checkpoint is torch.Size([80, 320, 1, 1]), while shape of head.cls_preds.1.weight in model is torch.Size([3, 320, 1, 1]).
2021-07-21 12:24:38 | WARNING | yolox.utils.checkpoint:26 - Shape of head.cls_preds.1.bias in checkpoint is torch.Size([80]), while shape of head.cls_preds.1.bias in model is torch.Size([3]).
2021-07-21 12:24:38 | WARNING | yolox.utils.checkpoint:26 - Shape of head.cls_preds.2.weight in checkpoint is torch.Size([80, 320, 1, 1]), while shape of head.cls_preds.2.weight in model is torch.Size([3, 320, 1, 1]).
2021-07-21 12:24:38 | WARNING | yolox.utils.checkpoint:26 - Shape of head.cls_preds.2.bias in checkpoint is torch.Size([80]), while shape of head.cls_preds.2.bias in model is torch.Size([3]).
2021-07-21 12:24:38 | INFO | yolox.data.datasets.coco:44 - loading annotations into memory...
2021-07-21 12:24:38 | INFO | yolox.data.datasets.coco:44 - Done (t=0.28s)
2021-07-21 12:24:38 | INFO | pycocotools.coco:92 - creating index...
2021-07-21 12:24:38 | INFO | pycocotools.coco:92 - index created!
2021-07-21 12:24:38 | INFO | yolox.core.trainer:149 - init prefetcher, this might take one minute or less...

What's the problem?

[Joker316701882]

How long does it remain here?

[hosea7456]

@Joker316701882
More than half an hour then I closed it. It hasn't print any error worring but it remain sucking up GPU memory.

[Joker316701882]

YOLOX/yolox/exp/yolox_base.py

Line 27 in ce7d754

self.data_num_workers = 4

Please try to set this value to 0.

[Joker316701882]

You may also need to try to use single gpu:
-d 1 -b 8

[hosea7456]

@Joker316701882
Yea, I have already set it to be 0. And I also try use single gpu with: -d 1 -b 2, but it still doesn't works.

[GOATmessi8]

See #103, plz pull the latest updates and retry it