one of the variables needed for gradient computation has been modified by an inplace operation: [torch.FloatTensor [204, 2]], which is output 0 of AsStridedBackward0, is at version 4; expected version 0 instead. Hint: the backtrace further above shows the operation that failed to compute its gradient. The variable in question was changed in there or anywhere later. Good luck! #26
Transferred 498/500 items from weights/plate_detect.pt
Optimizer groups: 85 .bias, 85 conv.weight, 82 other
Scanning '/data/train_data/CRPD_TRAIN.cache' for images and labels... 3137 found, 0 missing, 4 empty, 0 corrupted: 100%|█████████████████████████████████████████████████████████████████████████████████████| 3137/3137 [00:00<?, ?it/s]
Scanning '/data/val_detect/blue.cache' for images and labels... 5946 found, 0 missing, 0 empty, 0 corrupted: 100%|███████████████████████████████████████████████████████████████████████████████████████████| 5946/5946 [00:00<?, ?it/s]
Plotting labels...
/usr/local/anaconda3/envs/carbase/lib/python3.8/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight
self._figure.tight_layout(*args, **kwargs)
autoanchor: Analyzing anchors... anchors/target = 2.73, Best Possible Recall (BPR) = 1.0000
Image sizes 640 train, 640 test
Using 1 dataloader workers
Logging results to runs/train/exp4
Starting training for 120 epochs...
Epoch gpu_mem box obj cls landmark total targets img_size
0%| | 0/99 [00:00<?, ?it/s]/usr/local/anaconda3/envs/carbase/lib/python3.8/site-packages/torch/autograd/init.py:200: UserWarning: Error detected in BinaryCrossEntropyWithLogitsBackward0. Traceback of forward call that caused the error:
File "train.py", line 522, in
train(hyp, opt, device, tb_writer, wandb)
File "train.py", line 291, in train
loss, loss_items = compute_loss(pred, targets.to(device), model) # loss scaled by batch_size
File "/data/Chinese_license_plate_detection_recognition-main/utils/loss.py", line 163, in compute_loss
lcls += BCEcls(ps[:, 13:], t) # BCE
File "/usr/local/anaconda3/envs/carbase/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/usr/local/anaconda3/envs/carbase/lib/python3.8/site-packages/torch/nn/modules/loss.py", line 720, in forward
return F.binary_cross_entropy_with_logits(input, target,
File "/usr/local/anaconda3/envs/carbase/lib/python3.8/site-packages/torch/nn/functional.py", line 3165, in binary_cross_entropy_with_logits
return torch.binary_cross_entropy_with_logits(input, target, weight, pos_weight, reduction_enum)
(Triggered internally at ../torch/csrc/autograd/python_anomaly_mode.cpp:114.)
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
0%| | 0/99 [00:02<?, ?it/s]
Traceback (most recent call last):
File "train.py", line 522, in
train(hyp, opt, device, tb_writer, wandb)
File "train.py", line 296, in train
scaler.scale(loss).backward()
File "/usr/local/anaconda3/envs/carbase/lib/python3.8/site-packages/torch/_tensor.py", line 487, in backward
torch.autograd.backward(
File "/usr/local/anaconda3/envs/carbase/lib/python3.8/site-packages/torch/autograd/init.py", line 200, in backward
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.FloatTensor [204, 2]], which is output 0 of AsStridedBackward0, is at version 4; expected version 0 instead. Hint: the backtrace further above shows the operation that failed to compute its gradient. The variable in question was changed in there or anywhere later. Good luck!
(carbase) root@kfcs-Stad:/data/Chinese_license_plate_detection_recognition-main# python3 train.py --data data/widerface.yaml --cfg models/yolov5n-0.5.yaml --weights weights/plate_detect.pt --epoch 120 YOLOv5 torch 2.0.1+cu117 CPU
Namespace(adam=False, batch_size=32, bucket='', cache_images=False, cfg='models/yolov5n-0.5.yaml', data='data/widerface.yaml', device='cpu', epochs=120, evolve=False, exist_ok=False, global_rank=-1, hyp='data/hyp.scratch.yaml', image_weights=False, img_size=[640, 640], local_rank=-1, log_artifacts=False, log_imgs=16, multi_scale=True, name='exp', noautoanchor=False, nosave=False, notest=False, project='runs/train', rect=False, resume=False, save_dir='runs/train/exp4', single_cls=False, sync_bn=False, total_batch_size=32, weights='weights/plate_detect.pt', workers=1, world_size=1) Start Tensorboard with "tensorboard --logdir runs/train", view at http://localhost:6006/ Hyperparameters {'lr0': 0.01, 'lrf': 0.2, 'momentum': 0.937, 'weight_decay': 0.0005, 'warmup_epochs': 3.0, 'warmup_momentum': 0.8, 'warmup_bias_lr': 0.1, 'box': 0.05, 'cls': 0.5, 'landmark': 0.005, 'cls_pw': 1.0, 'obj': 1.0, 'obj_pw': 1.0, 'iou_t': 0.2, 'anchor_t': 4.0, 'fl_gamma': 0.0, 'hsv_h': 0.015, 'hsv_s': 0.7, 'hsv_v': 0.4, 'degrees': 0.0, 'translate': 0.1, 'scale': 0.5, 'shear': 0.5, 'perspective': 0.0, 'flipud': 0.0, 'fliplr': 0.5, 'mosaic': 0.5, 'mixup': 0.0} Overriding model.yaml nc=1 with nc=2
0 -1 1 2336 models.common.StemBlock [3, 16, 3, 2]
1 -1 1 2768 models.common.ShuffleV2Block [16, 64, 2]
2 -1 3 7584 models.common.ShuffleV2Block [64, 64, 1]
3 -1 1 14080 models.common.ShuffleV2Block [64, 128, 2]
4 -1 7 64064 models.common.ShuffleV2Block [128, 128, 1]
5 -1 1 52736 models.common.ShuffleV2Block [128, 256, 2]
6 -1 3 104064 models.common.ShuffleV2Block [256, 256, 1]
7 -1 1 16512 models.common.Conv [256, 64, 1, 1]
8 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
9 [-1, 4] 1 0 models.common.Concat [1]
10 -1 1 27008 models.common.C3 [192, 64, 1, False]
11 -1 1 4224 models.common.Conv [64, 64, 1, 1]
12 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
13 [-1, 2] 1 0 models.common.Concat [1]
14 -1 1 22912 models.common.C3 [128, 64, 1, False]
15 -1 1 36992 models.common.Conv [64, 64, 3, 2]
16 [-1, 11] 1 0 models.common.Concat [1]
17 -1 1 22912 models.common.C3 [128, 64, 1, False]
18 -1 1 36992 models.common.Conv [64, 64, 3, 2]
19 [-1, 7] 1 0 models.common.Concat [1]
20 -1 1 22912 models.common.C3 [128, 64, 1, False]
21 [14, 17, 20] 1 8775 models.yolo.Detect [2, [[4, 5, 8, 10, 13, 16], [23, 29, 43, 55, 73, 105], [146, 217, 231, 300, 335, 433]], [64, 64, 64]] /usr/local/anaconda3/envs/carbase/lib/python3.8/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3483.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] Model Summary: 333 layers, 446871 parameters, 446871 gradients, 1.6 GFLOPS
Transferred 498/500 items from weights/plate_detect.pt Optimizer groups: 85 .bias, 85 conv.weight, 82 other Scanning '/data/train_data/CRPD_TRAIN.cache' for images and labels... 3137 found, 0 missing, 4 empty, 0 corrupted: 100%|█████████████████████████████████████████████████████████████████████████████████████| 3137/3137 [00:00<?, ?it/s] Scanning '/data/val_detect/blue.cache' for images and labels... 5946 found, 0 missing, 0 empty, 0 corrupted: 100%|███████████████████████████████████████████████████████████████████████████████████████████| 5946/5946 [00:00<?, ?it/s] Plotting labels... /usr/local/anaconda3/envs/carbase/lib/python3.8/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight self._figure.tight_layout(*args, **kwargs)
autoanchor: Analyzing anchors... anchors/target = 2.73, Best Possible Recall (BPR) = 1.0000 Image sizes 640 train, 640 test Using 1 dataloader workers Logging results to runs/train/exp4 Starting training for 120 epochs...
0%| | 0/99 [00:00<?, ?it/s]/usr/local/anaconda3/envs/carbase/lib/python3.8/site-packages/torch/autograd/init.py:200: UserWarning: Error detected in BinaryCrossEntropyWithLogitsBackward0. Traceback of forward call that caused the error: File "train.py", line 522, in
train(hyp, opt, device, tb_writer, wandb)
File "train.py", line 291, in train
loss, loss_items = compute_loss(pred, targets.to(device), model) # loss scaled by batch_size
File "/data/Chinese_license_plate_detection_recognition-main/utils/loss.py", line 163, in compute_loss
lcls += BCEcls(ps[:, 13:], t) # BCE
File "/usr/local/anaconda3/envs/carbase/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/usr/local/anaconda3/envs/carbase/lib/python3.8/site-packages/torch/nn/modules/loss.py", line 720, in forward
return F.binary_cross_entropy_with_logits(input, target,
File "/usr/local/anaconda3/envs/carbase/lib/python3.8/site-packages/torch/nn/functional.py", line 3165, in binary_cross_entropy_with_logits
return torch.binary_cross_entropy_with_logits(input, target, weight, pos_weight, reduction_enum)
(Triggered internally at ../torch/csrc/autograd/python_anomaly_mode.cpp:114.)
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
0%| | 0/99 [00:02<?, ?it/s]
Traceback (most recent call last):
File "train.py", line 522, in
train(hyp, opt, device, tb_writer, wandb)
File "train.py", line 296, in train
scaler.scale(loss).backward()
File "/usr/local/anaconda3/envs/carbase/lib/python3.8/site-packages/torch/_tensor.py", line 487, in backward
torch.autograd.backward(
File "/usr/local/anaconda3/envs/carbase/lib/python3.8/site-packages/torch/autograd/init.py", line 200, in backward
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.FloatTensor [204, 2]], which is output 0 of AsStridedBackward0, is at version 4; expected version 0 instead. Hint: the backtrace further above shows the operation that failed to compute its gradient. The variable in question was changed in there or anywhere later. Good luck!