MATLAB: Weight initialization in patternnet

Deep Learning Toolboxneural networkpatternnet

Hi.
Suppose that we create a network and use configure to design the structure after it, so we have:
Net = patternnet([3 2]);
Configure = (Net,inputs,tagets);
Now I want disable normalization of inputs and outputs in this network so I will use:
net.inputs{1}.processFcns={};
net.outputs{3}.processFcns={};
But after that when I check net.inputs{1} and net.outputs{3} all informations set to 0 and defaults like the situation that we don’t use “Configure”, We have this note in matlab help :
Side Effects:
Whenever this property is altered, the input size is set to 0 and the processSettings are set accordingly.
I want only disable normalization and don’t want 'train' function initialize network weights again. When I check network initial weights I have same weights. In this situation 'train' function initial weights again like un-configured network or use the same configured weights?, because this process set to defaults “net.inputs{1}” and “net.outputs{3}”.
Thanks.

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