ZeroPadding1D layer
ZeroPadding1D class
keras.layers.ZeroPadding1D(padding=1, data_format=None, **kwargs)
Zero-padding layer for 1D input (e.g. temporal sequence).
Example
>>> input_shape = (2, 2, 3)
>>> x = np.arange(np.prod(input_shape)).reshape(input_shape)
>>> x
[[[ 0 1 2]
[ 3 4 5]]
[[ 6 7 8]
[ 9 10 11]]]
>>> y = keras.layers.ZeroPadding1D(padding=2)(x)
>>> y
[[[ 0 0 0]
[ 0 0 0]
[ 0 1 2]
[ 3 4 5]
[ 0 0 0]
[ 0 0 0]]
[[ 0 0 0]
[ 0 0 0]
[ 6 7 8]
[ 9 10 11]
[ 0 0 0]
[ 0 0 0]]]
Arguments
- padding: Int, or tuple of int (length 2), or dictionary.
- If int: how many zeros to add at the beginning and end of the padding dimension (axis 1).
- If tuple of 2 ints: how many zeros to add at the beginning and the
end of the padding dimension (
(left_pad, right_pad)).
- data_format: A string, one of
"channels_last"(default) or"channels_first". The ordering of the dimensions in the inputs."channels_last"corresponds to inputs with shape(batch_size, axis_to_pad, channels)while"channels_first"corresponds to inputs with shape(batch_size, channels, axis_to_pad). When unspecified, usesimage_data_formatvalue found in your Keras config file at~/.keras/keras.json(if exists). Defaults to"channels_last".
Input shape
3D tensor with shape:
- If data_format is "channels_last":
(batch_size, axis_to_pad, features)
- If data_format is "channels_first":
(batch_size, features, axis_to_pad)
Output shape
3D tensor with shape:
- If data_format is "channels_last":
(batch_size, padded_axis, features)
- If data_format is "channels_first":
(batch_size, features, padded_axis)