keras (version 2.3.0.0)

layer_average_pooling_1d: Average pooling for temporal data.

Description

Average pooling for temporal data.

Usage

layer_average_pooling_1d(
  object,
  pool_size = 2L,
  strides = NULL,
  padding = "valid",
  data_format = "channels_last",
  batch_size = NULL,
  name = NULL,
  trainable = NULL,
  weights = NULL
)

Arguments

object

Model or layer object

pool_size

Integer, size of the average pooling windows.

strides

Integer, or NULL. Factor by which to downscale. E.g. 2 will halve the input. If NULL, it will default to pool_size.

padding

One of "valid" or "same" (case-insensitive).

data_format

One of channels_last (default) or channels_first. The ordering of the dimensions in the inputs.

batch_size

Fixed batch size for layer

name

An optional name string for the layer. Should be unique in a model (do not reuse the same name twice). It will be autogenerated if it isn't provided.

trainable

Whether the layer weights will be updated during training.

weights

Initial weights for layer.

Input shape

3D tensor with shape: (batch_size, steps, features).

Output shape

3D tensor with shape: (batch_size, downsampled_steps, features).

See Also

Other pooling layers: layer_average_pooling_2d(), layer_average_pooling_3d(), layer_global_average_pooling_1d(), layer_global_average_pooling_2d(), layer_global_average_pooling_3d(), layer_global_max_pooling_1d(), layer_global_max_pooling_2d(), layer_global_max_pooling_3d(), layer_max_pooling_1d(), layer_max_pooling_2d(), layer_max_pooling_3d()