mlx.nn.MaxPool1d

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mlx.nn.MaxPool1d#

class MaxPool1d(kernel_size: int | Tuple[int], stride: int | Tuple[int] | None = None, padding: int | Tuple[int] = 0)#

Applies 1-dimensional max pooling.

Spatially downsamples the input by taking the maximum of a sliding window of size kernel_size and sliding stride stride.

Parameters:

  • kernel_size (int or tuple(int)) – The size of the pooling window kernel.

  • stride (int or tuple(int), optional) – The stride of the pooling window. Default: kernel_size.

  • padding (int or tuple(int), optional) – How much negative infinity padding to apply to the input. The padding amount is applied to both sides of the spatial axis. Default: 0.

Examples

>>> import mlx.core as mx
>>> import mlx.nn.layers as nn
>>> x = mx.random.normal(shape=(4, 16, 5))
>>> pool = nn.MaxPool1d(kernel_size=2, stride=2)
>>> pool(x)

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