Open 2461011611 opened 6 months ago
:~/autodl-tmp/yolov5_anime# python train.py --hyp ./data/hyp.finetune.yaml --batch-size 4 --epochs 360 --data ./data/anime.yaml --cfg ./models/yolov5x.yaml --weights ./weights/yolov5x_anime.pt Using CUDA device0 _CudaDeviceProperties(name='NVIDIA GeForce RTX 4090', total_memory=24217MB)
Namespace(adam=False, batch_size=4, bucket='', cache_images=False, cfg='./models/yolov5x.yaml', data='./data/anime.yaml', device='', epochs=360, evolve=False, global_rank=-1, hyp='./data/hyp.finetune.yaml', img_size=[640, 640], local_rank=-1, logdir='runs/', multi_scale=False, name='', noautoanchor=False, nosave=False, notest=False, rect=False, resume=False, single_cls=False, sync_bn=False, total_batch_size=4, weights='./weights/yolov5x_anime.pt', world_size=1) Start Tensorboard with "tensorboard --logdir runs/", view at http://localhost:6006/ Hyperparameters {'lr0': 0.01, 'momentum': 0.937, 'weight_decay': 0.0005, 'giou': 0.05, 'cls': 0.5, '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': 0.5, 'scale': 0.5, 'shear': 0.0, 'perspective': 0.0, 'flipud': 0.0, 'fliplr': 0.5, 'mixup': 0.0} Overriding ./models/yolov5x.yaml nc=1 with nc=20
from n params module arguments
0 -1 1 8800 models.common.Focus [3, 80, 3] 1 -1 1 115520 models.common.Conv [80, 160, 3, 2] 2 -1 1 315680 models.common.BottleneckCSP [160, 160, 4] 3 -1 1 461440 models.common.Conv [160, 320, 3, 2] 4 -1 1 3311680 models.common.BottleneckCSP [320, 320, 12] 5 -1 1 1844480 models.common.Conv [320, 640, 3, 2] 6 -1 1 13228160 models.common.BottleneckCSP [640, 640, 12] 7 -1 1 7375360 models.common.Conv [640, 1280, 3, 2] 8 -1 1 4099840 models.common.SPP [1280, 1280, [5, 9, 13]] 9 -1 1 20087040 models.common.BottleneckCSP [1280, 1280, 4, False] 10 -1 1 820480 models.common.Conv [1280, 640, 1, 1] 11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] 12 [-1, 6] 1 0 models.common.Concat [1] 13 -1 1 5435520 models.common.BottleneckCSP [1280, 640, 4, False] 14 -1 1 205440 models.common.Conv [640, 320, 1, 1] 15 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] 16 [-1, 4] 1 0 models.common.Concat [1] 17 -1 1 1360960 models.common.BottleneckCSP [640, 320, 4, False] 18 -1 1 922240 models.common.Conv [320, 320, 3, 2] 19 [-1, 14] 1 0 models.common.Concat [1] 20 -1 1 5025920 models.common.BottleneckCSP [640, 640, 4, False] 21 -1 1 3687680 models.common.Conv [640, 640, 3, 2] 22 [-1, 10] 1 0 models.common.Concat [1] 23 -1 1 20087040 models.common.BottleneckCSP [1280, 1280, 4, False] 24 [17, 20, 23] 1 168225 models.yolo.Detect [20, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [320, 640, 1280]] Traceback (most recent call last): File "train.py", line 441, in train(hyp, opt, device, tb_writer) File "train.py", line 68, in train model = Model(opt.cfg or ckpt['model'].yaml, ch=3, nc=nc).to(device) # create File "/root/autodl-tmp/yolov5_anime/models/yolo.py", line 83, in init self._initialize_biases() # only run once File "/root/autodl-tmp/yolov5_anime/models/yolo.py", line 142, in _initialize_biases b[:, 4] += math.log(8 / (640 / s) ** 2) # obj (8 objects per 640 image) RuntimeError: a view of a leaf Variable that requires grad is being used in an in-place operation.
how to solve? Thanks~
:~/autodl-tmp/yolov5_anime# python train.py --hyp ./data/hyp.finetune.yaml --batch-size 4 --epochs 360 --data ./data/anime.yaml --cfg ./models/yolov5x.yaml --weights ./weights/yolov5x_anime.pt Using CUDA device0 _CudaDeviceProperties(name='NVIDIA GeForce RTX 4090', total_memory=24217MB)
Namespace(adam=False, batch_size=4, bucket='', cache_images=False, cfg='./models/yolov5x.yaml', data='./data/anime.yaml', device='', epochs=360, evolve=False, global_rank=-1, hyp='./data/hyp.finetune.yaml', img_size=[640, 640], local_rank=-1, logdir='runs/', multi_scale=False, name='', noautoanchor=False, nosave=False, notest=False, rect=False, resume=False, single_cls=False, sync_bn=False, total_batch_size=4, weights='./weights/yolov5x_anime.pt', world_size=1) Start Tensorboard with "tensorboard --logdir runs/", view at http://localhost:6006/ Hyperparameters {'lr0': 0.01, 'momentum': 0.937, 'weight_decay': 0.0005, 'giou': 0.05, 'cls': 0.5, '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': 0.5, 'scale': 0.5, 'shear': 0.0, 'perspective': 0.0, 'flipud': 0.0, 'fliplr': 0.5, 'mixup': 0.0} Overriding ./models/yolov5x.yaml nc=1 with nc=20
0 -1 1 8800 models.common.Focus [3, 80, 3]
train(hyp, opt, device, tb_writer)
File "train.py", line 68, in train
model = Model(opt.cfg or ckpt['model'].yaml, ch=3, nc=nc).to(device) # create
File "/root/autodl-tmp/yolov5_anime/models/yolo.py", line 83, in init
self._initialize_biases() # only run once
File "/root/autodl-tmp/yolov5_anime/models/yolo.py", line 142, in _initialize_biases
b[:, 4] += math.log(8 / (640 / s) ** 2) # obj (8 objects per 640 image)
RuntimeError: a view of a leaf Variable that requires grad is being used in an in-place operation.
1 -1 1 115520 models.common.Conv [80, 160, 3, 2]
2 -1 1 315680 models.common.BottleneckCSP [160, 160, 4]
3 -1 1 461440 models.common.Conv [160, 320, 3, 2]
4 -1 1 3311680 models.common.BottleneckCSP [320, 320, 12]
5 -1 1 1844480 models.common.Conv [320, 640, 3, 2]
6 -1 1 13228160 models.common.BottleneckCSP [640, 640, 12]
7 -1 1 7375360 models.common.Conv [640, 1280, 3, 2]
8 -1 1 4099840 models.common.SPP [1280, 1280, [5, 9, 13]]
9 -1 1 20087040 models.common.BottleneckCSP [1280, 1280, 4, False]
10 -1 1 820480 models.common.Conv [1280, 640, 1, 1]
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
12 [-1, 6] 1 0 models.common.Concat [1]
13 -1 1 5435520 models.common.BottleneckCSP [1280, 640, 4, False]
14 -1 1 205440 models.common.Conv [640, 320, 1, 1]
15 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
16 [-1, 4] 1 0 models.common.Concat [1]
17 -1 1 1360960 models.common.BottleneckCSP [640, 320, 4, False]
18 -1 1 922240 models.common.Conv [320, 320, 3, 2]
19 [-1, 14] 1 0 models.common.Concat [1]
20 -1 1 5025920 models.common.BottleneckCSP [640, 640, 4, False]
21 -1 1 3687680 models.common.Conv [640, 640, 3, 2]
22 [-1, 10] 1 0 models.common.Concat [1]
23 -1 1 20087040 models.common.BottleneckCSP [1280, 1280, 4, False]
24 [17, 20, 23] 1 168225 models.yolo.Detect [20, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [320, 640, 1280]] Traceback (most recent call last): File "train.py", line 441, in
how to solve? Thanks~