MaxPool1D

class MaxPool1D(pool_size=2, strides=None, padding=0, layout='NCW', ceil_mode=False, **kwargs)

Max pooling operation for one dimensional data.

Parameters:
pool_size: int

Size of the max pooling windows.

strides: int, or None

Factor by which to downscale. E.g. 2 will halve the input size. If None, it will default to pool_size.

padding: int

If padding is non-zero, then the input is implicitly zero-padded on both sides for padding number of points.

layout : str, default ‘NCW’

Dimension ordering of data and out (‘NCW’ or ‘NWC’). ‘N’, ‘C’, ‘W’ stands for batch, channel, and width (time) dimensions respectively. Pooling is applied on the W dimension.

ceil_mode : bool, default False

When True, will use ceil instead of floor to compute the output shape.

Inputs:
  • data: 3D input tensor with shape (batch_size, in_channels, width) when layout is NCW. For other layouts shape is permuted accordingly.
Outputs:

  • out: 3D output tensor with shape (batch_size, channels, out_width) when layout is NCW. out_width is calculated as:

    out_width = floor((width+2*padding-pool_size)/strides)+1

    When ceil_mode is True, ceil will be used instead of floor in this equation.