Can anyone help me in reshaping a fully connected layer output to a image?

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I am trying to make a deep layer network in which I want to connect my pretrained convolutional layer at the intermediate step? I am unable to write a custom layer for it. I am sharing the code for the custom layer, please le me know where am I going wrong in it.
classdef fullytandem < nnet.layer.Layer
properties
% (Optional) Layer properties
% Layer properties go here
end
properties (Learnable)
% (Optional) Layer learnable parameters
% Layer learnable parameters go here
W;
b;
Z;
end
methods
function layer = fullytandem(input_shape, output_shape, im_layer, name)
% (Optional) Create a myLayer
% This function must have the same name as the layer
% Layer constructor function goes here
layer.Name = name;
layer.Description = 'fully self';
layer.b = rand([im_layer,1]);
layer.W = rand([im_layer,input_shape]);
end
function Z = predict(layer, X)
load('net_28s11.mat')
% Forward input data through the layer at prediction time and
% output the result
%
% Inputs:
% layer - Layer to forward propagate through
% X - Input data
% Output:
% Z - Output of layer forward function
% Layer forward function for prediction goes here
disp('W')
size(layer.W)
disp('X')
size(X)
weights = layer.W;
bias = layer.b;
Y = fullyconnect(X,weights,bias,'DataFormat','SSCB');
% Z = layer.W*X + layer.b';
% disp(size(Z))
% outputSize = X.OutputSize;
disp('Y')
size(Y)
Z = reshape(Y, [4,7,1]);
disp('Z')
size(Z)
% Z = predict(net,dlarray(Z));
end
%
end
end

Accepted Answer

Srivardhan Gadila
Srivardhan Gadila on 2 Nov 2020
Instead of writing the code for fullyconnected layer you can make use of the existing fullyConnectedLayer & write the custom layer code only for the reshape operation as follows:
layers = [ ...
imageInputLayer([100 1 1],'Name','input','Normalization','none')
fullyConnectedLayer(100, 'Name','fc')
reshapeLayer("reshape")
convolution2dLayer(5,20,'Name','conv')];
dlnet = dlnetwork(layerGraph(layers));
analyzeNetwork(dlnet)
Custom layer code for reshape operation:
classdef reshapeLayer < nnet.layer.Layer
properties
end
properties (Learnable)
end
methods
function layer = reshapeLayer(name)
layer.Name = name;
end
function [Z] = predict(layer, X)
Z = reshape(X,10,10,1,[]);
end
end
end
  5 Comments
Atallah Baydoun
Atallah Baydoun on 2 Mar 2022
Just found the answer.
You have to add a line to the function as follows:
function [Z] = predict(layer, X)
Z = reshape(X, 8, 8, 8, []);
Z = dlarray(Z,'SSSCB');

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