HW3 for CSE 253 (Winter 2018) at UCSD
Put in your password.
To activate the computing environment (i don't get what this does)
cs253w
Then depending on whether or not you want to use a GPU.
launch-pytorch.sh
or
launch-pytorch-gpu.sh
You should now have a Docker container where all of your stuff is accessible.
You can clone this repo into either the container started from:
launch-pytorch-gpu.sh
Or just more generally into your position on the ieng6
cluster.
python network_1.py
python network_2.py
python Network_3.py
These files will produce 2 figures each: percent accuracy and class accuracy.
'TransferLearningFinal.py'
Performs transfer learning; will produce two plots of accuracy and loss, as well as 4 data files for accuracy and loss of training and testing data
'FeatureExtractionFinal.py'
Performs feature extraction after 3rd and 4th layers; will produce 4 plots of accuracy and loss for each of the 3rd and 4th layers, as well as 8 data files for accuracy and loss of training and testing data
'PlotActivations.py'
Plots 5 image inputs as original images, after 1st conv layer, and after last conv layer. Also plots 1st layer weights. Saves all images to a folder (must change directory to run)
Credit to this repo for the validation data loader.