Traceback (most recent call last):


 "/home/youssef/.local/lib/python3.6/site-packages/detectron2/engine/train_loop.py", line 134, in train

self.run_step()


 "/home/youssef/.local/lib/python3.6/site-packages/detectron2/engine/defaults.py", line 423, in run_step

self._trainer.run_step()


 "/home/youssef/.local/lib/python3.6/site-packages/detectron2/engine/train_loop.py", line 228, in run_step

loss_dict = self.model(data)


 "/home/youssef/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 727, in _call_impl

result = self.forward(*input, **kwargs)


 "/home/youssef/.local/lib/python3.6/site-packages/detectron2/modeling/meta_arch/retinanet.py", line 260, in forward

losses = self.losses(anchors, pred_logits, gt_labels, pred_anchor_deltas, gt_boxes)


 "/home/youssef/.local/lib/python3.6/site-packages/detectron2/modeling/meta_arch/retinanet.py", line 323, in losses

reduction="sum",
RuntimeError: nvrtc: error: invalid value for --gpu-architecture (-arch)

Traceback (most recent call last):


 "scripts/validate.py", line 154, in <module>

gt_AP = validate_gt(m, cfg, heatmap_to_coord, opt.batch)


 "scripts/validate.py", line 109, in validate_gt

output = m(inps)


 "A:\Python\lib\site-packages\torch\nn\modules\module.py", line 532, in __call__

result = self.forward(*input, **kwargs)


 "A:\Python\lib\site-packages\torch\nn\parallel\data_parallel.py", line 150, in forward

return self.module(*inputs[0], **kwargs[0])


 "A:\Python\lib\site-packages\torch\nn\modules\module.py", line 532, in __call__

result = self.forward(*input, **kwargs)


 "f:\alphapose-master\alphapose\models\fastpose.py", line 48, in forward

out = self.preact(x)


 "A:\Python\lib\site-packages\torch\nn\modules\module.py", line 532, in __call__

result = self.forward(*input, **kwargs)


 "f:\alphapose-master\alphapose\models\layers\SE_Resnet.py", line 183, in forward

x = self.maxpool(self.relu(self.bn1(self.conv1(x))))
# 64 * h/4 * w/4


 "A:\Python\lib\site-packages\torch\nn\modules\module.py", line 532, in __call__

result = self.forward(*input, **kwargs)


 "A:\Python\lib\site-packages\torch\nn\modules\conv.py", line 345, in forward

return self.conv2d_forward(input, self.weight)


 "A:\Python\lib\site-packages\torch\nn\modules\conv.py", line 342, in conv2d_forward

self.padding, self.dilation, self.groups)
RuntimeError: Expected 4-dimensional input for 4-dimensional weight 64 3 7 7, but got 3-dimensional input of size [3, 256, 192] instead
