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

layer_zero_padding_1d(
object,
batch_size = NULL,
name = NULL,
trainable = NULL,
weights = NULL
)

## Arguments

object What to compose the new Layer instance with. Typically a Sequential model or a Tensor (e.g., as returned by layer_input()). The return value depends on object. If object is: missing or NULL, the Layer instance is returned. a Sequential model, the model with an additional layer is returned. a Tensor, the output tensor from layer_instance(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.

## Input shape

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

## Output shape

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()