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Multiplication layer

Since R2020b


A multiplication layer multiplies inputs from multiple neural network layers element-wise.

Specify the number of inputs to the layer when you create it. The inputs to the layer have the names 'in1','in2',...,'inN', where N is the number of inputs. Use the input names when connecting or disconnecting the layer by using connectLayers or disconnectLayers, respectively. The size of the inputs to the multiplication layer must be either same across all dimensions or same across at least one dimension with other dimensions as singleton dimensions.




layer = multiplicationLayer(numInputs) creates a multiplication layer that multiplies numInputs inputs element-wise. This function also sets the NumInputs property.


layer = multiplicationLayer(numInputs,'Name',name) also sets the Name property.


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Number of inputs to the layer, specified as a positive integer greater than or equal to 2.

The inputs have the names 'in1','in2',...,'inN', where N is NumInputs. For example, if NumInputs is 3, then the inputs have the names 'in1','in2', and 'in3'. Use the input names when connecting or disconnecting the layer using the connectLayers or disconnectLayers functions.

Layer name, specified as a character vector or a string scalar. For Layer array input, the trainnet and dlnetwork functions automatically assign names to layers with the name "".

The MultiplicationLayer object stores this property as a character vector.

Data Types: char | string

Input names, specified as {'in1','in2',...,'inN'}, where N is the number of inputs of the layer.

Data Types: cell

This property is read-only.

Number of outputs from the layer, returned as 1. This layer has a single output only.

Data Types: double

This property is read-only.

Output names, returned as {'out'}. This layer has a single output only.

Data Types: cell


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Create a multiplication layer with two inputs and the name 'mul_1'.

mul = multiplicationLayer(2,'Name','mul_1')
mul = 
  MultiplicationLayer with properties:

          Name: 'mul_1'
     NumInputs: 2
    InputNames: {'in1'  'in2'}

   Learnable Parameters
    No properties.

   State Parameters
    No properties.

Use properties method to see a list of all properties.

Create two ReLU layers.

relu_1 = reluLayer('Name','relu_1');
relu_2 = reluLayer('Name','relu_2');

Create a dlnetwork object.

net = dlnetwork;

Add them to the network and connect them to the multiplication layer. The multiplication layer multiplies the outputs from the ReLU layers.

net = addLayers(net,relu_1);
net = addLayers(net,relu_2);
net = addLayers(net,mul);

net = connectLayers(net,'relu_1','mul_1/in1');
net = connectLayers(net,'relu_2','mul_1/in2');



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Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Version History

Introduced in R2020b

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