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