Max pooling operation for temporal data.

Max pooling operation for temporal data.

layer_max_pooling_1d(object, pool_size = 2L, strides = NULL,
  padding = "valid", batch_size = NULL, name = NULL, trainable = NULL,
  weights = NULL)

Arguments

object

Model or layer object
pool_size

Integer, size of the max 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).
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_1d, 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_2d, layer_max_pooling_3d