Thank you @Dwight_Foster . It works.
But now it raised another error:
Traceback (most recent call last):
  File "/home/clin15/Documents/MedicalNet-Tinnitus/train.py", line 194, in <module>
    train(data_loaders, model, optimizer, scheduler, total_epochs=sets.n_epochs, save_interval=sets.save_intervals, save_folder=sets.save_folder, sets=sets) 
  File "/home/clin15/Documents/MedicalNet-Tinnitus/train.py", line 77, in train
    output = model(volumes)
  File "/home/clin15/.conda/envs/pytorch_clin/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/clin15/.conda/envs/pytorch_clin/lib/python3.7/site-packages/torch/nn/parallel/data_parallel.py", line 161, in forward
    outputs = self.parallel_apply(replicas, inputs, kwargs)
  File "/home/clin15/.conda/envs/pytorch_clin/lib/python3.7/site-packages/torch/nn/parallel/data_parallel.py", line 171, in parallel_apply
    return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)])
  File "/home/clin15/.conda/envs/pytorch_clin/lib/python3.7/site-packages/torch/nn/parallel/parallel_apply.py", line 86, in parallel_apply
    output.reraise()
  File "/home/clin15/.conda/envs/pytorch_clin/lib/python3.7/site-packages/torch/_utils.py", line 428, in reraise
    raise self.exc_type(msg)
RuntimeError: Caught RuntimeError in replica 0 on device 0.
Original Traceback (most recent call last):
  File "/home/clin15/.conda/envs/pytorch_clin/lib/python3.7/site-packages/torch/nn/parallel/parallel_apply.py", line 61, in _worker
    output = module(*input, **kwargs)
  File "/home/clin15/.conda/envs/pytorch_clin/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/clin15/Documents/MedicalNet-Tinnitus/models/resnet.py", line 210, in forward
    x = self.conv1(x)
  File "/home/clin15/.conda/envs/pytorch_clin/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/clin15/.conda/envs/pytorch_clin/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 573, in forward
    self.padding, self.dilation, self.groups)
RuntimeError: Expected 5-dimensional input for 5-dimensional weight [64, 1, 7, 7, 7], but got 4-dimensional input of size [2, 200, 300, 320] instead


Do you by any chance know how to solve this?
Thanks.