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