Hi,
As per my understanding, you want to examine initial value of encoder weights.
The ‘trainAutoencoder’ function internally includes calls to the following lines of code (accessible via the "edit trainAutoencoder.m" command) which create a network based on the passed parameters and then train the network on input data:
% ... (other code)
paramsStruct = Autoencoder.parseInputArguments(varargin{:});
autonet = Autoencoder.createNetwork(paramsStruct);
autoenc = Autoencoder.train(X, autonet, paramsStruct.UseGPU);
% ... (other code)
The ‘createNetwork’ function is responsible for setting up the network topology and initializing the weights. Here is a snippet of the code:
function net = createNetwork(paramsStruct)
net = network;
% Define topology
% ... (other code)
% Set up initialization options
net.layers{1}.initFcn = 'initwb';
net.inputWeights{1,1}.initFcn = 'randsmall';
net.biases{1}.initFcn = 'randsmall';
net.layers{2}.initFcn = 'initwb';
net.layerWeights{2,1}.initFcn = 'randsmall';
net.biases{2}.initFcn = 'randsmall';
net.initFcn = 'initlay';
% ... (other code)
Based on the above code, we can observe that the weights are initialized using 'randsmall', which means they are set to small random numbers between -0.1 to 0.1.
Please refer to the following MathWorks documentation link to know more about ‘randsmall’:
I hope you find this resolves your query.
Best Regards,
Lokesh
