pool#

ivy.pool(x, window_shape, pool_type, /, *, strides=None, padding='VALID', data_format=None, dilations=None, ceil_mode=False, out=None)[source]#

Perform an N-D pooling operation.

Parameters:

x (Union[Array, NativeArray]) – Input array to pool over.
window_shape (Union[int, Tuple[int], Tuple[int, int]]) – Shape of the pooling window.
pool_type (str) – Type of pooling operation, either ‘MAX’ or ‘AVG’.
strides (Optional[Union[int, Tuple[int], Tuple[int, int]]], default: None) – Strides of the pooling operation.
padding (str, default: 'VALID') – Padding type, either ‘VALID’ or ‘SAME’.
data_format (Optional[str], default: None) – Data format of the input and output data, either ‘NCHW’ or ‘NHWC’.
dilations (Optional[Union[int, Tuple[int], Tuple[int, int]]], default: None) – Dilation rate of the pooling operation.
ceil_mode (bool, default: False) – Whether to use ceil or floor for creating the output shape.
out (Optional[Array], default: None) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

Array

Returns:

ret – The result of the pooling operation.

Examples

>>> x = ivy.arange(12.).reshape((2, 1, 3, 2))
>>> print(ivy.pool(x, (2, 2), 'MAX', strides=(1, 1), padding='SAME'))
ivy.array([[[[ 1.,  2.],
            [ 3.,  4.],
            [ 4.,  5.]]],
        [[[ 7.,  8.],
            [ 9., 10.],
            [10., 11.]]]])
>>> x = ivy.arange(48.).reshape((2, 4, 3, 2))
>>> print(ivy.pool(x, 3, 'AVG', strides=1, padding='VALID'))
ivy.array([[[[ 8.,  9.]],
        [[14., 15.]]],
        [[[32., 33.]],
        [[38., 39.]]]])