COS 429 - Computer Vision

Fall 2019

Assignment 4: Deep Learning

Part III. Learning CNNs with PyTorch

There are several open-source Convolution Neural Network packages available, including TensorFlow, PyTorch, Caffe, Theano, and MatConvNet. It is possible to define and train all the network architectures we looked at in class using most of these packages, though for large networks & data sets, an NVIDIA GPU (with CUDA) is a must. For this assignment we will be training only smaller networks, where the CPU-only implementation should be sufficient. Here we will use PyTorch. If you have not successfully installed PyTorch yet, please see assignment 0, part 2.

For this part of the assignment, follow the CNN tutorial for PyTorch , adopted from the tutorials by the Oxford Visual Geometry Group. Feel free to skip section 4.4; it requires an NVIDIA GPU and the CUDA development libraries.

Please complete and submit short answers for all of the questions labeled as "Question:". What to turn in:

• In Assignment 4 written: a section in the README.pdf containing short answers for all questions labeled "Question" in the tutorial.

• On to Part IV
• Back to the main page for Assignment 4