Global Max Pooling 1D Layer
R2026bLibraries:
Deep Learning Toolbox /
Deep Learning Layers /
Pooling Layers
Description
The Global Max Pooling 1D Layer block performs downsampling by outputting the maximum of the time or spatial dimensions of the input.
The dimension that the layer pools over depends on the layer input:
For time series and vector sequence input in the
CTformat (two dimensions corresponding to channels and time steps, in that order), the layer pools over the time dimension.For 1-D image input in the
SCformat (two dimensions corresponding to spatial pixels and channels, in that order), the layer pools over the spatial dimension.
The exportNetworkToSimulink function generates this block to represent a globalMaxPooling1dLayer object.
Examples
Ports
Input
Output
Parameters
Programmatic Use: Add Block
To add the block programmatically, use the add_block function with one of these library block paths as the source.
"dlpoolinglib/Global Max Pooling 1D Layer"
Example: add_block("dlpoolinglib/Global Max Pooling 1D Layer","myModel/myBlock",MakeNameUnique="on")
For information about programmatic access to individual block parameters, see the Programmatic Use section of parameter descriptions on this page.


