# tf.keras.layers.UpSampling3D
|---|
| [ View source on GitHub](https://github.com/keras-team/keras/tree/v2.14.0/keras/layers/reshaping/up_sampling3d.py#L29-L131) |
Upsampling layer for 3D inputs.
Inherits From: [`Layer`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/keras/layers/Layer), [`Module`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/Module)
tf.keras.layers.UpSampling3D(
size=(2, 2, 2), data_format=None, **kwargs
)
Repeats the 1st, 2nd and 3rd dimensions
of the data by `size[0]`, `size[1]` and `size[2]` respectively.
#### Examples:
input_shape = (2, 1, 2, 1, 3)
x = tf.constant(1, shape=input_shape)
y = tf.keras.layers.UpSampling3D(size=2)(x)
print(y.shape)
(2, 2, 4, 2, 3)
| ## Args ||
|---|---|
| `size` | Int, or tuple of 3 integers. The upsampling factors for dim1, dim2 and dim3. |
| `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) else 'channels_last'. Defaults to 'channels_last'. |
| ## Input shape ||
|---|---|
| 5D tensor with shape:
- If `data_format` is `"channels_last"`: `(batch_size, dim1, dim2, dim3, channels)` - If `data_format` is `"channels_first"`: `(batch_size, channels, dim1, dim2, dim3)` ||
| ## Output shape ||
|---|---|
| 5D tensor with shape:
- If `data_format` is `"channels_last"`: `(batch_size, upsampled_dim1, upsampled_dim2, upsampled_dim3, channels)` - If `data_format` is `"channels_first"`: `(batch_size, channels, upsampled_dim1, upsampled_dim2, upsampled_dim3)` ||