Traceback (most recent call last):
File "/data2/zixuan/DSRL-subpixel/train.py", line 313, in
main()
File "/data2/zixuan/DSRL-subpixel/train.py", line 306, in main
trainer.training(epoch)
File "/data2/zixuan/DSRL-subpixel/train.py", line 110, in training
output,output_sr,fea_seg,fea_sr = self.model(input_img)
File "/home/zixuan/anaconda3/envs/DSRL/lib/python3.6/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/zixuan/anaconda3/envs/DSRL/lib/python3.6/site-packages/torch/nn/parallel/data_parallel.py", line 159, in forward
return self.module(*inputs[0], **kwargs[0])
File "/home/zixuan/anaconda3/envs/DSRL/lib/python3.6/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/data2/zixuan/DSRL-subpixel/modeling/deeplab.py", line 46, in forward
x = self.aspp(x)
File "/home/zixuan/anaconda3/envs/DSRL/lib/python3.6/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/data2/zixuan/DSRL-subpixel/modeling/aspp.py", line 70, in forward
x5 = self.global_avg_pool(x)
File "/home/zixuan/anaconda3/envs/DSRL/lib/python3.6/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/zixuan/anaconda3/envs/DSRL/lib/python3.6/site-packages/torch/nn/modules/container.py", line 117, in forward
input = module(input)
File "/home/zixuan/anaconda3/envs/DSRL/lib/python3.6/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/zixuan/anaconda3/envs/DSRL/lib/python3.6/site-packages/torch/nn/modules/batchnorm.py", line 136, in forward
self.weight, self.bias, bn_training, exponential_average_factor, self.eps)
File "/home/zixuan/anaconda3/envs/DSRL/lib/python3.6/site-packages/torch/nn/functional.py", line 2054, in batch_norm
_verify_batch_size(input.size())
File "/home/zixuan/anaconda3/envs/DSRL/lib/python3.6/site-packages/torch/nn/functional.py", line 2037, in _verify_batch_size
raise ValueError('Expected more than 1 value per channel when training, got input size {}'.format(size))
ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 256, 1, 1])
May I ask if there is an error downloading my data or if there is an issue with my model parameter settings? Can you please refer to your format for storing Cityscapes data?