# tf.keras.backend.spatial_3d_padding

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|---|---|
| [![](https://www.tensorflow.org/images/tf_logo_32px.png) TensorFlow 2 version](https://www.tensorflow.org/api_docs/python/tf/keras/backend/spatial_3d_padding) | [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/keras/backend.py#L3031-L3072) |

Pads 5D tensor with zeros along the depth, height, width dimensions.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.keras.backend.spatial_3d_padding`](https://www.tensorflow.org/api_docs/python/tf/keras/backend/spatial_3d_padding), \`tf.compat.v2.keras.backend.spatial_3d_padding\`

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    tf.keras.backend.spatial_3d_padding(
        x, padding=((1, 1), (1, 1), (1, 1)), data_format=None
    )

Pads these dimensions with respectively
"padding\[0\]", "padding\[1\]" and "padding\[2\]" zeros left and right.

For 'channels_last' data_format,
the 2nd, 3rd and 4th dimension will be padded.
For 'channels_first' data_format,
the 3rd, 4th and 5th dimension will be padded.

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| ## Arguments ||
|---|---|
| `x` | Tensor or variable. |
| `padding` | Tuple of 3 tuples, padding pattern. |
| `data_format` | One of `channels_last` or `channels_first`. |

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| ## Returns ||
|---|---|
| A padded 5D tensor. ||

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| ## Raises ||
|---|---|
| `ValueError` | if `data_format` is neither `channels_last` or `channels_first`. |

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