class brainpy.dnn.MaxPool2d(kernel_size, stride=None, padding='VALID', channel_axis=-1, mode=None, name=None)[source]#
Applies a 1D max pooling over an input signal composed of several input


  • kernel_size (int, sequence of int) – An integer, or a sequence of integers defining the window to reduce over.

  • stride (int, sequence of int) – An integer, or a sequence of integers, representing the inter-window stride (default: (1, …, 1)).

  • padding (str, int, sequence of tuple) – Either the string ‘SAME’, the string ‘VALID’, or a sequence of n (low, high) integer pairs that give the padding to apply before and after each spatial dimension.

  • channel_axis (int, optional) – Axis of the spatial channels for which pooling is skipped. If None, there is no channel axis.

  • mode (Mode) – The computation mode.

  • name (optional, str) – The object name.