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

Question

Aggraj Gupta 2020-10-26

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/626393-can-anyone-help-me-in-reshaping-a-fully-connected-layer-output-to-a-image

评论： Atallah Baydoun 2022-3-2

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

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Answer 1

Srivardhan Gadila 2020-11-2

0
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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/626393-can-anyone-help-me-in-reshaping-a-fully-connected-layer-output-to-a-image#answer_531674

在 MATLAB Online 中打开

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