Hi All,
I am trying to do Udacity Computer Vision Nanodegree exercise.
The code is very long, so I have given the link to my Github.

  
      github.com
  
  
    subhobrata/Deep-Learning/blob/master/Udacity_ComputerVision_5.ipynb 1
{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Udacity_ComputerVision_5.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {


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I am getting below error
TypeError                                 Traceback (most recent call last)
 in ()
7     # forward pass to get outputs
8     # the outputs are a series of class scores
----> 9     outputs = net(images)
10
11     # get the predicted class from the maximum value in the output-list of class scores
/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in call(self, *input, **kwargs)
323         for hook in self._forward_pre_hooks.values():
324             hook(self, input)
–> 325         result = self.forward(*input, **kwargs)
326         for hook in self._forward_hooks.values():
327             hook_result = hook(self, input, result)
 in forward(self, x)
32     def forward(self, x):
33         # two conv/relu + pool layers
—> 34         x = self.pool(F.relu(self.conv1(x)))
35         x = self.pool(F.relu(self.conv2(x)))
36
/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in call(self, *input, **kwargs)
323         for hook in self._forward_pre_hooks.values():
324             hook(self, input)
–> 325         result = self.forward(*input, **kwargs)
326         for hook in self._forward_hooks.values():
327             hook_result = hook(self, input, result)
/usr/local/lib/python3.6/dist-packages/torch/nn/modules/conv.py in forward(self, input)
275     def forward(self, input):
276         return F.conv2d(input, self.weight, self.bias, self.stride,
–> 277                         self.padding, self.dilation, self.groups)
278
279
/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py in conv2d(input, weight, bias, stride, padding, dilation, groups)
88                 _pair(0), groups, torch.backends.cudnn.benchmark,
89                 torch.backends.cudnn.deterministic, torch.backends.cudnn.enabled)
—> 90     return f(input, weight, bias)
91
92
TypeError: argument 0 is not a Variable