layer_upsampling_2d.RdRepeats 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