keras: layer_upsampling_2d – R documentation

Pricing

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

Get Started for Free

Documentation

keras

layer_upsampling_2d

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