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tf.keras.layers.ZeroPadding3D
Zero-padding layer for 3D data (spatial or spatio-temporal).
tf.keras.layers.ZeroPadding3D(
    padding=(1, 1, 1), data_format=None, **kwargs
)
Examples:
input_shape = (1, 1, 2, 2, 3)
x = np.arange(np.prod(input_shape)).reshape(input_shape)
y = tf.keras.layers.ZeroPadding3D(padding=2)(x)
print(y.shape)
(1, 5, 6, 6, 3)
| Arguments | |
|---|---|
| padding | Int, or tuple of 3 ints, or tuple of 3 tuples of 2 ints. 
 | 
| data_format | A string, one of channels_last(default) orchannels_first. The ordering of the dimensions in the inputs.channels_lastcorresponds to inputs with shape(batch_size, spatial_dim1, spatial_dim2, spatial_dim3, channels)whilechannels_firstcorresponds to inputs with shape(batch_size, channels, spatial_dim1, spatial_dim2, spatial_dim3). It defaults to theimage_data_formatvalue found in your Keras config file at~/.keras/keras.json. If you never set it, then it will be "channels_last". | 
Input shape:
5D tensor with shape:
- If data_formatis"channels_last":(batch_size, first_axis_to_pad, second_axis_to_pad, third_axis_to_pad, depth)
- If data_formatis"channels_first":(batch_size, depth, first_axis_to_pad, second_axis_to_pad, third_axis_to_pad)
Output shape:
5D tensor with shape:
- If data_formatis"channels_last":(batch_size, first_padded_axis, second_padded_axis, third_axis_to_pad, depth)
- If data_formatis"channels_first":(batch_size, depth, first_padded_axis, second_padded_axis, third_axis_to_pad)
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
 https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/keras/layers/ZeroPadding3D