Getting error while training the model

[jitender-code]

I have tried to train this model on layoutnet datasets with all default parameters mentioned here (https://github.com/sunset1995/HorizonNet).
I executed the following command
(HorizonNet) D:\HorizonNet-master>python train.py --id resnet50_rnn

I am getting the following error

Epoch: 0%| | 0/300 [00:00<?, ?ep/s]
Traceback (most recent call last):
File "train.py", line 181, in
iterator_train = iter(loader_train)
File "C:\Anaconda3\envs\HorizonNet\lib\site-packages\torch\utils\data\dataloader.py", line 279, in iter
return _MultiProcessingDataLoaderIter(self)
File "C:\Anaconda3\envs\HorizonNet\lib\site-packages\torch\utils\data\dataloader.py", line 719, in init
w.start()
File "C:\Anaconda3\envs\HorizonNet\lib\multiprocessing\process.py", line 105, in start
self._popen = self._Popen(self)
File "C:\Anaconda3\envs\HorizonNet\lib\multiprocessing\context.py", line 223, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File "C:\Anaconda3\envs\HorizonNet\lib\multiprocessing\context.py", line 322, in _Popen
return Popen(process_obj)
File "C:\Anaconda3\envs\HorizonNet\lib\multiprocessing\popen_spawn_win32.py", line 65, in init
reduction.dump(process_obj, to_child)
File "C:\Anaconda3\envs\HorizonNet\lib\multiprocessing\reduction.py", line 60, in dump
ForkingPickler(file, protocol).dump(obj)
_pickle.PicklingError: Can't pickle <function at 0x0000023358098158>: attribute lookup on main failed

(HorizonNet) D:\HorizonNet-master>Traceback (most recent call last):
File "", line 1, in
File "C:\Anaconda3\envs\HorizonNet\lib\multiprocessing\spawn.py", line 105, in spawn_main
exitcode = _main(fd)
File "C:\Anaconda3\envs\HorizonNet\lib\multiprocessing\spawn.py", line 115, in _main
self = reduction.pickle.load(from_parent)
EOFError: Ran out of input

Then I modified "train.py" at line number 114 as "num_workers=0".
I am using anaconda in which a new environment named HorizonNet is created with python version = 3.6.
Now I am getting the following error

(HorizonNet) D:\HorizonNet-master>python train.py --id resnet50_rnn --epochs 50
Train ep1: 0%| | 0/204 [00:01<?, ?it/s]
Epoch: 0%| | 0/50 [00:01<?, ?ep/s]
Traceback (most recent call last):
File "train.py", line 191, in
losses = feed_forward(net, x, y_bon, y_cor)
File "train.py", line 26, in feed_forward
y_bon_, y_cor_ = net(x)
File "C:\Anaconda3\envs\HorizonNet\lib\site-packages\torch\nn\modules\module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "D:\HorizonNet-master\model.py", line 242, in forward
feature = self.reduce_height_module(conv_list, x.shape[3]//self.step_cols)
File "C:\Anaconda3\envs\HorizonNet\lib\site-packages\torch\nn\modules\module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "D:\HorizonNet-master\model.py", line 166, in forward
for f, x, out_c in zip(self.ghc_lst, conv_list, self.cs)
File "D:\HorizonNet-master\model.py", line 166, in
for f, x, out_c in zip(self.ghc_lst, conv_list, self.cs)
File "C:\Anaconda3\envs\HorizonNet\lib\site-packages\torch\nn\modules\module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "D:\HorizonNet-master\model.py", line 138, in forward
x = self.layer(x)
File "C:\Anaconda3\envs\HorizonNet\lib\site-packages\torch\nn\modules\module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "C:\Anaconda3\envs\HorizonNet\lib\site-packages\torch\nn\modules\container.py", line 100, in forward
input = module(input)
File "C:\Anaconda3\envs\HorizonNet\lib\site-packages\torch\nn\modules\module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "D:\HorizonNet-master\model.py", line 124, in forward
return self.layers(x)
File "C:\Anaconda3\envs\HorizonNet\lib\site-packages\torch\nn\modules\module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "C:\Anaconda3\envs\HorizonNet\lib\site-packages\torch\nn\modules\container.py", line 100, in forward
input = module(input)
File "C:\Anaconda3\envs\HorizonNet\lib\site-packages\torch\nn\modules\module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "C:\Anaconda3\envs\HorizonNet\lib\site-packages\torch\nn\modules\container.py", line 100, in forward
input = module(input)
File "C:\Anaconda3\envs\HorizonNet\lib\site-packages\torch\nn\modules\module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "D:\HorizonNet-master\model.py", line 31, in forward
return lr_pad(x, self.padding)
File "D:\HorizonNet-master\model.py", line 21, in lr_pad
return torch.cat([x[..., -padding:], x, x[..., :padding]], dim=3)
RuntimeError: CUDA out of memory. Tried to allocate 66.00 MiB (GPU 0; 6.00 GiB total capacity; 4.28 GiB already allocated; 4.91 MiB free; 4.34 GiB reserved in total by PyTorch)

Please help