layer_upsampling_2d.Rd
Repeats the rows and columns of the data by size[[0]]
and size[[1]]
respectively.
layer_upsampling_2d(object, size = c(2L, 2L), data_format = NULL, interpolation = "nearest", batch_size = NULL, name = NULL, trainable = NULL, weights = NULL)
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 |
interpolation | A string, one of |
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. |
4D tensor with shape:
If data_format
is "channels_last"
: (batch, rows, cols, channels)
If data_format
is "channels_first"
: (batch, channels, rows, cols)
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)
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