layer_upsampling_2d {keras} | R Documentation

## Upsampling layer for 2D inputs.

### Description

Repeats the rows and columns of the data by `size[[0]]` and `size[[1]]` respectively.

### Usage

    layer_upsampling_2d(object, size = c(2L, 2L), data_format = NULL,
      interpolation = "nearest", batch_size = NULL, name = NULL,
      trainable = NULL, weights = NULL)

### Arguments

`object` | Model or layer object
`size` | int, or list 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`. Note that CNTK does not support yet the `bilinear` upscaling and that with Theano, only `size=(2, 2)` is possible.
`batch_size` | Fixed batch size for layer
`name` | An optional name string for the layer. Should be unique in a model (do not reuse the same name twice). It will be autogenerated if it isn't provided.
`trainable` | Whether the layer weights will be updated during training.
`weights` | Initial weights for layer.

### 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)`

### See Also

Other convolutional layers: `layer_conv_1d`, `layer_conv_2d_transpose`, `layer_conv_2d`, `layer_conv_3d_transpose`, `layer_conv_3d`, `layer_conv_lstm_2d`, `layer_cropping_1d`, `layer_cropping_2d`, `layer_cropping_3d`, `layer_depthwise_conv_2d`, `layer_separable_conv_1d`, `layer_separable_conv_2d`, `layer_upsampling_1d`, `layer_upsampling_3d`, `layer_zero_padding_1d`, `layer_zero_padding_2d`, `layer_zero_padding_3d`

[Package keras version 2.2.4 Index]