Zero-padding layer for 1D input (e.g. temporal sequence).

Zero-padding layer for 1D input (e.g. temporal sequence).

layer_zero_padding_1d(object, padding = 1L, batch_size = NULL,
  name = NULL, trainable = NULL, weights = NULL)

Arguments

object

Model or layer object
padding

int, or list of int (length 2)

  • If int: How many zeros to add at the beginning and end of the padding dimension (axis 1).

  • If list of int (length 2): How many zeros to add at the beginning and at the end of the padding dimension ((left_pad, right_pad)).
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, axis_to_pad, features)

Output shape

3D tensor with shape (batch, padded_axis, features)

See also

Other convolutional layers: layer_conv_1d, layer_conv_2d_transpose, layer_conv_2d, layer_conv_3d_transpose, layer_conv_3d, layer_conv_lstm_2d, layer_cropping_1d, layer_cropping_2d, layer_cropping_3d, layer_depthwise_conv_2d, layer_separable_conv_1d, layer_separable_conv_2d, layer_upsampling_1d, layer_upsampling_2d, layer_upsampling_3d, layer_zero_padding_2d, layer_zero_padding_3d