tf.keras.layers.ZeroPadding3D

Zero-padding layer for 3D data (spatial or spatio-temporal).

Inherits From: Layer, Operation

tf.keras.layers.ZeroPadding3D(
    padding=((1, 1), (1, 1), (1, 1)), data_format=None, **kwargs
)

Example:

input_shape = (1, 1, 2, 2, 3)
x = np.arange(np.prod(input_shape)).reshape(input_shape)
y = keras.layers.ZeroPadding3D(padding=2)(x)
y.shape
(1, 5, 6, 6, 3)

padding Int, or tuple of 3 ints, or tuple of 3 tuples of 2 ints.

  • If int: the same symmetric padding is applied to depth, height, and width.
  • If tuple of 3 ints: interpreted as three different symmetric padding values for depth, height, and width: (symmetric_dim1_pad, symmetric_dim2_pad, symmetric_dim3_pad).
  • If tuple of 3 tuples of 2 ints: interpreted as ((left_dim1_pad, right_dim1_pad), (left_dim2_pad, right_dim2_pad), (left_dim3_pad, right_dim3_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, spatial_dim1, spatial_dim2, spatial_dim3, channels) while "channels_first" corresponds to inputs with shape (batch_size, channels, spatial_dim1, spatial_dim2, spatial_dim3). When unspecified, uses image_data_format value found in your Keras config file at ~/.keras/keras.json (if exists). Defaults to "channels_last".

5D tensor with shape:

  • If data_format is "channels_last": (batch_size, first_axis_to_pad, second_axis_to_pad, third_axis_to_pad, depth)
  • If data_format is "channels_first": (batch_size, depth, first_axis_to_pad, second_axis_to_pad, third_axis_to_pad)

5D tensor with shape:

  • If data_format is "channels_last": (batch_size, first_padded_axis, second_padded_axis, third_axis_to_pad, depth)
  • If data_format is "channels_first": (batch_size, depth, first_padded_axis, second_padded_axis, third_axis_to_pad)

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

View source

@classmethod
from_config(
    config
)

Creates an operation from its config.

This method is the reverse of get_config, capable of instantiating the same operation from the config dictionary.

if "dtype" in config and isinstance(config["dtype"], dict):
    policy = dtype_policies.deserialize(config["dtype"])

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

Returns
An operation instance.