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
)What to call the new Layer instance with. Typically a keras
Model, another Layer, or a tf.Tensor/KerasTensor. If object is
missing, the Layer instance is returned, otherwise, layer(object) is
returned.
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)).
Fixed batch size for layer
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.
Whether the layer weights will be updated during training.
Initial weights for layer.
3D tensor with shape (batch, axis_to_pad, features)
3D tensor with shape (batch, padded_axis, features)
Other convolutional layers:
layer_conv_1d_transpose(),
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()