Original Traceback (most recent call last):


 "/opt/conda/lib/python3.8/site-packages/torch/nn/parallel/parallel_apply.py", line 60, in _worker

output = module(*input, **kwargs)


 "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 722, in _call_impl

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


 "/mnt/nas125/SeungjunLee/Projects/stylegan2/lpips/networks_basic.py", line 78, in forward

res = [spatial_average(self.lins[kk].model(diffs[kk]), keepdim=True) for kk in range(self.L)]


 "/mnt/nas125/SeungjunLee/Projects/stylegan2/lpips/networks_basic.py", line 78, in <listcomp>

res = [spatial_average(self.lins[kk].model(diffs[kk]), keepdim=True) for kk in range(self.L)]


 "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 722, in _call_impl

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


 "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/container.py", line 117, in forward

input = module(input)


 "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 722, in _call_impl

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


 "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 419, in forward

return self._conv_forward(input, self.weight)


 "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 415, in _conv_forward

return F.conv2d(input, weight, self.bias, self.stride,
RuntimeError: Expected tensor for argument #1 'input' to have the same device as tensor for argument #2 'weight'; but device 1 does not equal 0 (while checking arguments for cudnn_convolution)

Traceback (most recent call last):


 "/home/zgz/github_code/mmdetection/tools/train.py", line 118, in <module>

main()


 "/home/zgz/github_code/mmdetection/tools/train.py", line 114, in main

logger=logger)


 "/home/zgz/github_code/mmdetection/mmdet/apis/train.py", line 60, in train_detector

_non_dist_train(model, dataset, cfg, validate=validate)


 "/home/zgz/github_code/mmdetection/mmdet/apis/train.py", line 232, in _non_dist_train

runner.run(data_loaders, cfg.workflow, cfg.total_epochs)


 "/usr/local/python37/lib/python3.7/site-packages/mmcv/runner/runner.py", line 363, in run

epoch_runner(data_loaders[i], **kwargs)


 "/usr/local/python37/lib/python3.7/site-packages/mmcv/runner/runner.py", line 267, in train

self.model, data_batch, train_mode=True, **kwargs)


 "/home/zgz/github_code/mmdetection/mmdet/apis/train.py", line 38, in batch_processor

losses = model(**data)


 "/usr/local/python37/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in __call__

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


 "/usr/local/python37/lib/python3.7/site-packages/torch/nn/parallel/data_parallel.py", line 153, in forward

outputs = self.parallel_apply(replicas, inputs, kwargs)


 "/usr/local/python37/lib/python3.7/site-packages/torch/nn/parallel/data_parallel.py", line 163, in parallel_apply

return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)])


 "/usr/local/python37/lib/python3.7/site-packages/torch/nn/parallel/parallel_apply.py", line 83, in parallel_apply

raise output


 "/usr/local/python37/lib/python3.7/site-packages/torch/nn/parallel/parallel_apply.py", line 59, in _worker

output = module(*input, **kwargs)


 "/usr/local/python37/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in __call__

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


 "/home/zgz/github_code/mmdetection/mmdet/core/fp16/decorators.py", line 75, in new_func

output = old_func(*new_args, **new_kwargs)


 "/home/zgz/github_code/mmdetection/mmdet/models/detectors/base.py", line 117, in forward

return self.forward_train(img, img_meta, **kwargs)


 "/home/zgz/github_code/mmdetection/mmdet/models/detectors/two_stage.py", line 167, in forward_train

x = self.extract_feat(img)


 "/home/zgz/github_code/mmdetection/mmdet/models/detectors/two_stage.py", line 93, in extract_feat

x = self.backbone(img)


 "/usr/local/python37/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in __call__

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


 "/home/zgz/github_code/mmdetection/mmdet/models/backbones/resnet.py", line 524, in forward

x = self.norm1(x)


 "/usr/local/python37/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in __call__

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


 "/home/zgz/github_code/mmdetection/mmdet/core/fp16/hooks.py", line 122, in new_forward

**cast_tensor_type(kwargs, src_type, dst_type))


 "/usr/local/python37/lib/python3.7/site-packages/torch/nn/modules/batchnorm.py", line 83, in forward

exponential_average_factor, self.eps)


 "/usr/local/python37/lib/python3.7/site-packages/torch/nn/functional.py", line 1697, in batch_norm

training, momentum, eps, torch.backends.cudnn.enabled
RuntimeError: Expected tensor for argument #1 'input' to have the same device as tensor for argument #2 'weight'; but device 1 does not equal 0 (while checking arguments for cudnn_batch_norm)
