@smth Thanks for your reply 
But  When I do model.forward(x)  I am getting TypeError: 'NoneType' object is not callable.
The full error stack:
model.forward(t)
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-21-c3b310dc48c1> in <module>()
----> 1 model.forward(t)

/opt/python3.5/lib/python3.5/site-packages/torch/legacy/nn/Module.py in forward(self, input)
     31 
     32     def forward(self, input):
---> 33         return self.updateOutput(input)
     34 
     35     def backward(self, input, gradOutput, scale=1):

/opt/python3.5/lib/python3.5/site-packages/torch/legacy/nn/Sequential.py in updateOutput(self, input)
     34         currentOutput = input
     35         for i, module in enumerate(self.modules):
---> 36             currentOutput = module.updateOutput(currentOutput)
     37         self.output = currentOutput
     38         return self.output

TypeError: 'NoneType' object is not callable

Here are steps I do while saving the model in Lua Torch:
require 'nn'
require 'cunn'
networkd = torch.load('~/models/mlp0_ds4_gpu.t7')
networkd = networkd:cuda()

# forward once to create all the model variables 
x = torch.FloatTensor():resize(1,3,96,96):cuda()
networkd:forward(x)

# [cudnn.convert script](https://github.com/soumith/cudnn.torch/blob/master/convert.lua) 
net = cudnn.convert(networkd, cudnn)
net = net:float()
torch.save('/tmp/overfeatNet.t7', net)

Then loading in PyTorch:
import torch as th
from torch.utils.serialization import load_lua
model = load_lua('overfeatNet.t7', unknown_classes=True)
t = th.randn(3,480, 640).cuda()
model = model.cuda()
d = model.forward(t)

Could you please help me in understanding what mistake I am doing?
For now, I am doing the forward pass in Lua, saving the resulting feature maps to disk, and loading them in PyTorch. It will be nice to get this error fixed. Thanks