[Solved] COMP590 Homework 5-Convolutional Neural Networks

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In this assignment you will practice with training Convolutional Neural Networks for digits classification tasks.

Setup

You can work on the assignment on google colab.

Pytorch neural network tutorial

https://pytorch.org/tutorials/beginner/blitz/neural_networks_tutorial.html#sphx-glr-beginn er-blitz-neural-networks-tutorial-py

1. Filling in the training code

The dataloader and network architecture classes are all given to you. To train a deep neural network, you iterate through the whole training dataset multiple times (called epochs). At each step of training,

  1. extract a mini-batch from the training dataset and give it to the network;
  2. compute the loss between the output from the network and the groundtruth label; 3. compute the gradients of network weights with respect to the loss;
  3. update the weights.

2. Answer questions

  1. How many layers are there in the neural network?
  2. How many features are there at each layer?
  3. What is the loss function? How does it penalize wrongly classified labels?
  4. If we change the input image size from 2828 to 3232, how should we modify the fc1() layer?

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[Solved] COMP590 Homework 5-Convolutional Neural Networks
$25