adaptive_avg_pool1d#
- ivy.adaptive_avg_pool1d(input, output_size)[source]#
Apply a 1D adaptive average pooling over an input signal composed of several input planes.
- Parameters:
input (
Union[Array,NativeArray]) – Input array. Must have shape (N, C, L_in) or (C, L_in) where N is the batch dimension, C is the feature dimension, and L_in is the spatial dimension.output_size (
int) – Spatial output size.
- Return type:
- Returns:
The result of the pooling operation. Will have shape (N, C, L_out) or (C, L_out), where L_out = output_size
- Array.adaptive_avg_pool1d(self, output_size)[source]#
Apply a 1D adaptive average pooling over an input signal composed of several input planes.
- Parameters:
self (
Array) – Input array. Must have shape (N, C, L_in) or (C, L_in) where N is the batch dimension, C is the feature dimension, and L_in is the spatial dimension.output_size (
int) – Spatial output size.
- Return type:
Array- Returns:
The result of the pooling operation. Will have shape (N, C, L_out) or
(C, L_out), where L_out = output_size
- Container.adaptive_avg_pool1d(self, output_size, *, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False)[source]#
Apply a 1D adaptive average pooling over an input signal composed of several input planes.
- Parameters:
self (
Container) – Input container.output_size (
Union[int,Container]) – Spatial output size.
- Return type:
Container- Returns:
The result of the pooling operation.