reshape fully connected layer in matlab

To reshape a fully connected layer in Matlab, you first need to have the Neural Network Toolbox. Within the toolbox, you can use the fullyConnectedLayer function to create a fully connected layer object.

Once you have a fully connected layer object, you can use the inputSize method to get the size of the input to the layer. Then, you can use the reshape function to reshape the weights and biases of the layer to the desired size.

Here's an example:

main.m
% create a fully connected layer with 10 input features and 5 output features
fc_layer = fullyConnectedLayer(5);

% get the input size of the layer
input_size = fc_layer.inputSize;

% reshape the weights and biases of the layer
fc_layer_weights = fc_layer.Weights;
fc_layer_biases = fc_layer.Bias;
fc_layer_weights_reshaped = reshape(fc_layer_weights, [input_size, fc_layer.NumNeurons]);
fc_layer_biases_reshaped = reshape(fc_layer_biases, [1, fc_layer.NumNeurons]);

% set the new weights and biases of the layer
fc_layer.Weights = fc_layer_weights_reshaped;
fc_layer.Bias = fc_layer_biases_reshaped;
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In this example, fc_layer is a fully connected layer object with 10 input features and 5 output features. We use the inputSize method to get the input size of the layer, which is 10. Then, we reshape the weights of the layer from a (10 x 5) matrix to a (10 x 5) matrix using the reshape function. We also reshape the biases from a (1 x 5) matrix to a (1 x 5) matrix.

Finally, we set the new weights and biases of the layer using the Weights and Bias properties of the layer object.