tf.keras.layers.ZeroPadding2D

Zero-padding layer for 2D input (e.g. picture).

Inherits From: Layer, Operation

tf.keras.layers.ZeroPadding2D(
    padding=(1, 1), data_format=None, **kwargs
)

Used in the notebooks

Used in the guide Used in the tutorials

This layer can add rows and columns of zeros at the top, bottom, left and right side of an image tensor.

Example:

input_shape = (1, 1, 2, 2)
x = np.arange(np.prod(input_shape)).reshape(input_shape)
x
[[[[0 1]
   [2 3]]]]
y = keras.layers.ZeroPadding2D(padding=1)(x)
y
[[[[0 0]
   [0 0]
   [0 0]
   [0 0]]
  [[0 0]
   [0 1]
   [2 3]
   [0 0]]
  [[0 0]
   [0 0]
   [0 0]
   [0 0]]]]

padding Int, or tuple of 2 ints, or tuple of 2 tuples of 2 ints.

  • If int: the same symmetric padding is applied to height and width.
  • If tuple of 2 ints: interpreted as two different symmetric padding values for height and width: (symmetric_height_pad, symmetric_width_pad).
  • If tuple of 2 tuples of 2 ints: interpreted as ((top_pad, bottom_pad), (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, height, width, channels) while "channels_first" corresponds to inputs with shape (batch_size, channels, height, width). When unspecified, uses image_data_format value found in your Keras config file at ~/.keras/keras.json (if exists). Defaults to "channels_last".

4D tensor with shape:

  • If data_format is "channels_last": (batch_size, height, width, channels)
  • If data_format is "channels_first": (batch_size, channels, height, width)

4D tensor with shape:

  • If data_format is "channels_last": (batch_size, padded_height, padded_width, channels)
  • If data_format is "channels_first": (batch_size, channels, padded_height, padded_width)

input Retrieves the input tensor(s) of a symbolic operation.

Only returns the tensor(s) corresponding to the first time the operation was called.

output Retrieves the output tensor(s) of a layer.

Only returns the tensor(s) corresponding to the first time the operation was called.

Methods

from_config

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@classmethod
from_config(
    config
)

Creates a layer from its config.

This method is the reverse of get_config, capable of instantiating the same layer from the config dictionary. It does not handle layer connectivity (handled by Network), nor weights (handled by set_weights).

Args
config A Python dictionary, typically the output of get_config.

Returns
A layer instance.

symbolic_call

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symbolic_call(
    *args, **kwargs
)