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► Keras 3 API documentation / Layers API / Reshaping layers / ZeroPadding1D layer

ZeroPadding1D layer

[source]

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, uses image_data_format value 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)

ZeroPadding1D layer
ZeroPadding1D class