keras: layer_upsampling_3d – R documentation

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keras

layer_upsampling_3d

Upsampling layer for 3D inputs.

Description

Repeats the 1st, 2nd and 3rd dimensions of the data by size[[0]], size[[1]] and size[[2]] respectively.

Usage

layer_upsampling_3d(
  object,
  size = c(2L, 2L, 2L),
  data_format = NULL,
  batch_size = NULL,
  name = NULL,
  trainable = NULL,
  weights = NULL
)

Arguments

`object`	Model or layer object
`size`	int, or list 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, 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".
`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

5D tensor with shape:

If data_format is "channels_last": (batch, dim1, dim2, dim3, channels)
If data_format is "channels_first": (batch, channels, dim1, dim2, dim3)

Output shape