featureInputLayer — Create a feature input layer compatibility object.
featureInputLayer(inputSize) creates host metadata for feature-input network definitions.
Syntax
layer = featureInputLayer(inputSize)
layer = featureInputLayer(inputSize, Name, Value)How featureInputLayer works
inputSizemay be a positive integer scalar or numeric vector of positive integers.Name,Description,Normalization, and other common name-value options are stored as properties.
GPU memory and residency
Layer construction is host metadata work and has no provider kernel.
Example
Create Feature Input
layer = featureInputLayer(4, 'Name', 'features')Expected output:
`layer.InputSize` stores `4`.Using featureInputLayer with coding agents
Open a RunMat example with live inputs, then ask the agent to explain how featureInputLayer changes the result.
Run a small featureInputLayer example, explain the result, then change one input and compare the output.
Related Deep Learning functions
adamupdate · analyzeNetwork · bilstmLayer · classificationLayer · combvec · convolution1dLayer · crossentropy · dlarray · dlfeval · dlgradient · dlnetwork · dlupdate · eluLayer · exportONNXNetwork · forward · fullyConnectedLayer · globalAveragePooling1dLayer · layerGraph · layerNormalizationLayer · lstmLayer · padsequences · regressionLayer · reluLayer · sequenceInputLayer · softmaxLayer · trainingOptions · trainnet · trainNetwork
About RunMat
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