I want to suggest a simple testcase for fully-connected neural network module.
AutoEncoder is not only able to test NN performance without any data, but also is used for pre-training stage for some NN.
Let assume that we use three-layer NN whose size is 65536 x 16 x 65536. During training, we can choose any number n (0 <= n <= 65536) and set one node as 1.0 in both input/output layers identically. The internal layer should eventually be saturated as a binary form of that number.
Here, I just mentioned one hidden layer, but we can use more hidden layers, too.
I want to suggest a simple testcase for fully-connected neural network module.
AutoEncoder is not only able to test NN performance without any data, but also is used for pre-training stage for some NN.
Let assume that we use three-layer NN whose size is 65536 x 16 x 65536. During training, we can choose any number n (0 <= n <= 65536) and set one node as 1.0 in both input/output layers identically. The internal layer should eventually be saturated as a binary form of that number.
Here, I just mentioned one hidden layer, but we can use more hidden layers, too.