Perform CIFAR-10 classification with residual networks implementation based on Lasagne.

Deep_Residual_Learning_CIFAR-10

Please follow this guide to setup your environment.

Configuration of ~/.theanorc

[global]
device = gpu
floatX = float32
[cuda]
root = /usr/local/cuda-7.5/
[lib]
cnmem = 1

Clarification

• An epoch represents all the processes divide all the data equally and go through them once together.
• A barrier is used at the end of each epoch.
• This experiment doesn't use warm start in ASGD.
• The time to load the data is not considered in the time of the experiment.

The results of 3 experiments with different configurations are shown as following.