I have noticed that the funtional supports the res-net structure by simply set res_net argument to True, but did not explain how to modify the shortcut connections.
(res_net: (True, False). Constructs a resnet architecture. Defaulted to False.)
I am wondering how to define a network with multiple residual blocks with different hidden layers and designs.
For example, I want to build a network with the following design:
number of input: 1
residual block 1: 2 layers, with [30, 30] hidden neurons
residual block 2: 3 layers, with [40, 30, 20] hidden neurons
number of output: 2
Any suggestions / examples would be highly appreciated.
Dear SciANN community,
I have noticed that the funtional supports the res-net structure by simply set res_net argument to True, but did not explain how to modify the shortcut connections. (res_net: (True, False). Constructs a resnet architecture. Defaulted to False.)
I am wondering how to define a network with multiple residual blocks with different hidden layers and designs.
For example, I want to build a network with the following design: number of input: 1 residual block 1: 2 layers, with [30, 30] hidden neurons residual block 2: 3 layers, with [40, 30, 20] hidden neurons number of output: 2
Any suggestions / examples would be highly appreciated.
Thank you!