train on own dataset error : Size of tensor mismatch

I am training on my own dataset, set of images and corresponding label maps.

ran python train.py --name clayseam --batchSize 4 --label_nc 2 --no_instance --dataroot /pub2/sw5park/p2phd, where dataroot folder contains 4 folders : train_label, train_img, test_label, test_img

gives the following error :

Traceback (most recent call last): File "train.py", line 71, in Variable(data['image']), Variable(data['feat']), infer=save_fake) File "/home/sw5park/venv/lib/python3.6/site-packages/torch/nn/modules/module.py", line 722, in _call_impl result = self.forward(*input, **kwargs) File "/home/sw5park/venv/lib/python3.6/site-packages/torch/nn/parallel/data_parallel.py", line 153, in forward return self.module(*inputs[0], **kwargs[0]) File "/home/sw5park/venv/lib/python3.6/site-packages/torch/nn/modules/module.py", line 722, in _call_impl result = self.forward(*input, **kwargs) File "/home/sw5park/generative/pix2pixHD/models/pix2pixHD_model.py", line 166, in forward pred_fake_pool = self.discriminate(input_label, fake_image, use_pool=True) File "/home/sw5park/generative/pix2pixHD/models/pix2pixHD_model.py", line 145, in discriminate input_concat = torch.cat((input_label, test_image.detach()), dim=1) RuntimeError: Sizes of tensors must match except in dimension 2. Got 560 and 546 (The offending index is 0)