I keep getting an error “Expected 3D tensor” when trying to classify image with a model saved by @smth ImageNet example.  What am I doing wrong?  Model was trained on GPU with CUDA and saved in the pth.tar format.
# Bunch of imports go here

# Convert image to Variable
def Torchify( aImage ):
    ptLoader = transforms.Compose([transforms.ToTensor()])
    aImage = ptLoader( aImage ).float()
    aImage = Variable( aImage, volatile=True  )
    return aImage.cuda()

# Load model from Checkpoint
print("=> Loading Network")
ptModelAxial = densenet.__dict__['densenet161'](pretrained=False, num_classes=5)
ptModelAxial.classifier = nn.Linear(8832, 5)
ptModelAxial = torch.nn.DataParallel(ptModelAxial).cuda()
dTemp = torch.load("best.pth.tar")
ptModelAxial.load_state_dict(dTemp['state_dict'])
for p in ptModelAxial.parameters():
    p.requires_grad = False
ptModelAxial.eval()

InputImg = skimage.img_as_float(skimage.io.imread(sFileName))
ptModelPreds = ptModelAxial( Torchify(InputImg) )
print( ptModelPreds )

Error:
Traceback (most recent call last):
  File "extract.py", line 298
      ptModelPreds = ptModelAxial( Torchify(InputImg) )
File "/conda3/envs/idp/lib/python3.5/site-packages/torch/nn/modules/module.py", line 206, in __call__
    result = self.forward(*input, **kwargs)
  File "/conda3/envs/idp/lib/python3.5/site-packages/torch/nn/parallel/data_parallel.py", line 61, in forward
    outputs = self.parallel_apply(replicas, inputs, kwargs)
  File "/conda3/envs/idp/lib/python3.5/site-packages/torch/nn/parallel/data_parallel.py", line 71, in parallel_apply
    return parallel_apply(replicas, inputs, kwargs)
  File "/conda3/envs/idp/lib/python3.5/site-packages/torch/nn/parallel/parallel_apply.py", line 45, in parallel_apply
    raise output
  File "/conda3/envs/idp/lib/python3.5/site-packages/torch/nn/parallel/parallel_apply.py", line 25, in _worker
    output = module(*input, **kwargs)
  File "/conda3/envs/idp/lib/python3.5/site-packages/torch/nn/modules/module.py", line 206, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/keyur/kaggle/densenet.py", line 153, in forward
    features = self.features(x)
  File "/conda3/envs/idp/lib/python3.5/site-packages/torch/nn/modules/module.py", line 206, in __call__
    result = self.forward(*input, **kwargs)
  File "/conda3/envs/idp/lib/python3.5/site-packages/torch/nn/modules/container.py", line 64, in forward
    input = module(input)
  File "/conda3/envs/idp/lib/python3.5/site-packages/torch/nn/modules/module.py", line 206, in __call__
    result = self.forward(*input, **kwargs)
  File "/conda3/envs/idp/lib/python3.5/site-packages/torch/nn/modules/conv.py", line 237, in forward
    self.padding, self.dilation, self.groups)
  File "/conda3/envs/idp/lib/python3.5/site-packages/torch/nn/functional.py", line 39, in conv2d
    return f(input, weight, bias)
RuntimeError: expected 3D tensor