# tf.keras.layers.ZeroPadding3D

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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/layers/ZeroPadding3D) | [![](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/layers/convolutional.py#L2216-L2330) |

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

Inherits From: [`Layer`](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/keras/layers/Layer)

#### View aliases


**Compat aliases for migration**

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

[`tf.compat.v1.keras.layers.ZeroPadding3D`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/ZeroPadding3D), \`tf.compat.v2.keras.layers.ZeroPadding3D\`

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

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| ## Arguments ||
|---|---|
| `padding` | Int, or tuple of 3 ints, or tuple of 3 tuples of 2 ints. <br /> - If int: the same symmetric padding is applied to height and width. - If tuple of 3 ints: interpreted as two different symmetric padding values for 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, spatial_dim1, spatial_dim2, spatial_dim3, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, spatial_dim1, spatial_dim2, spatial_dim3)`. It defaults to the `image_data_format` value 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_format` is `"channels_last"`: `(batch, first_axis_to_pad, second_axis_to_pad, third_axis_to_pad,
  depth)`
- If `data_format` is `"channels_first"`: `(batch, depth, first_axis_to_pad, second_axis_to_pad,
  third_axis_to_pad)`

#### Output shape:

5D tensor with shape:

- If `data_format` is `"channels_last"`: `(batch, first_padded_axis, second_padded_axis, third_axis_to_pad,
  depth)`
- If `data_format` is `"channels_first"`: `(batch, depth, first_padded_axis, second_padded_axis,
  third_axis_to_pad)`