layer_average_pooling_1d: Average pooling for temporal data.

In keras: R Interface to 'Keras'

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	What to compose the new Layer instance with. Typically a Sequential model or a Tensor (e.g., as returned by layer_input()). The return value depends on object. If object is: missing or NULL, the Layer instance is returned. a Sequential model, the model with an additional layer is returned. a Tensor, the output tensor from layer_instance(object) is returned.
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()

keras documentation built on May 29, 2024, 3:20 a.m.