Can you comment on the parameter choices for ResNet20?
In self_models/resnet.py the ResNet20 is defined in 4 layers with 2 basic blocks in each (num_blocks=[2,2,2,2]) with plane parameters of 64, 128, 256, 512.
In contrast the original paper of He et al. uses only 3 layers with 3 basic blocks in each with plane parameters of 16, 32, 64.
So your model will have tremendously more parameters. Can you comment on your source of the ResNet20 implementation if isn't the paper by He et al.?
Dear @nitin-rathi
Can you comment on the parameter choices for ResNet20?
In
self_models/resnet.pythe ResNet20 is defined in 4 layers with 2 basic blocks in each (num_blocks=[2,2,2,2]) with plane parameters of64, 128, 256, 512.In contrast the original paper of He et al. uses only 3 layers with 3 basic blocks in each with plane parameters of
16, 32, 64.So your model will have tremendously more parameters. Can you comment on your source of the ResNet20 implementation if isn't the paper by He et al.?