1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
| (debug) youda@youda-ubuntu ~/workspace/yolov5
(debug) youda@youda-ubuntu ~/workspace/yolov5 python detect.py
detect: weights=yolov5s.pt, source=data/images, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False
/home/youda/anaconda3/envs/debug/lib/python3.6/site-packages/torch/cuda/__init__.py:143: UserWarning:
NVIDIA GeForce RTX 3070 with CUDA capability sm_86 is not compatible with the current PyTorch installation.
The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_70.
If you want to use the NVIDIA GeForce RTX 3070 GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/
warnings.warn(incompatible_device_warn.format(device_name, capability, " ".join(arch_list), device_name))
YOLOv5 🚀 2021-11-15 torch 1.10.0+cu102 CUDA:0 (NVIDIA GeForce RTX 3070, 7960MiB)
Traceback (most recent call last):
File "detect.py", line 244, in <module>
main(opt)
File "detect.py", line 239, in main
run(**vars(opt))
File "/home/youda/anaconda3/envs/debug/lib/python3.6/site-packages/torch/autograd/grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "detect.py", line 79, in run
model = DetectMultiBackend(weights, device=device, dnn=dnn)
File "/home/youda/workspace/yolov5/models/common.py", line 305, in __init__
model = torch.jit.load(w) if 'torchscript' in w else attempt_load(weights, map_location=device)
File "/home/youda/workspace/yolov5/models/experimental.py", line 98, in attempt_load
model.append(ckpt['ema' if ckpt.get('ema') else 'model'].float().fuse().eval()) # FP32 model
File "/home/youda/anaconda3/envs/debug/lib/python3.6/site-packages/torch/nn/modules/module.py", line 735, in float
return self._apply(lambda t: t.float() if t.is_floating_point() else t)
File "/home/youda/workspace/yolov5/models/yolo.py", line 240, in _apply
self = super()._apply(fn)
File "/home/youda/anaconda3/envs/debug/lib/python3.6/site-packages/torch/nn/modules/module.py", line 570, in _apply
module._apply(fn)
File "/home/youda/anaconda3/envs/debug/lib/python3.6/site-packages/torch/nn/modules/module.py", line 570, in _apply
module._apply(fn)
File "/home/youda/anaconda3/envs/debug/lib/python3.6/site-packages/torch/nn/modules/module.py", line 570, in _apply
module._apply(fn)
File "/home/youda/anaconda3/envs/debug/lib/python3.6/site-packages/torch/nn/modules/module.py", line 593, in _apply
param_applied = fn(param)
File "/home/youda/anaconda3/envs/debug/lib/python3.6/site-packages/torch/nn/modules/module.py", line 735, in <lambda>
return self._apply(lambda t: t.float() if t.is_floating_point() else t)
RuntimeError: CUDA error: no kernel image is available for execution on the device
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
(debug) ✘ youda@youda-ubuntu ~/workspace/yolov5
|