# tf.keras.layers.UpSampling2D
|---|---|
| [ TensorFlow 1 version](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/keras/layers/UpSampling2D) | [ View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.0.0/tensorflow/python/keras/layers/convolutional.py#L1917-L1996) |
Upsampling layer for 2D inputs.
Inherits From: [`Layer`](https://www.tensorflow.org/versions/r2.0/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.UpSampling2D`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/UpSampling2D)
tf.keras.layers.UpSampling2D(
size=(2, 2), data_format=None, interpolation='nearest', **kwargs
)
Repeats the rows and columns of the data
by `size[0]` and `size[1]` respectively.
| ## Arguments ||
|---|---|
| `size` | Int, or tuple of 2 integers. The upsampling factors for rows and columns. |
| `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, height, width, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, height, width)`. 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". |
| `interpolation` | A string, one of `nearest` or `bilinear`. |
#### Input shape:
4D tensor with shape:
- If `data_format` is `"channels_last"`: `(batch, rows, cols, channels)`
- If `data_format` is `"channels_first"`: `(batch, channels, rows, cols)`
#### Output shape:
4D tensor with shape:
- If `data_format` is `"channels_last"`: `(batch, upsampled_rows, upsampled_cols, channels)`
- If `data_format` is `"channels_first"`: `(batch, channels, upsampled_rows, upsampled_cols)`