tf.keras.layers.ZeroPadding2D | TensorFlow v2.16.1 (original) (raw)
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 |
---|---|
Pruning for on-device inference w/ XNNPACK | pix2pix: Image-to-image translation with a conditional GAN |
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]]]]
Args | |
---|---|
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". |
Input shape |
---|
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) |
Output shape |
---|
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) |
Attributes | |
---|---|
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
@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
symbolic_call(
*args, **kwargs
)