Description Usage Arguments Input shape Output shape See Also
View source: R/layers-convolutional.R
Repeats the rows and columns of the data by size[[0]] and size[[1]] respectively.
| 1 2 3 4 5 6 7 8 9 10 | 
| 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()
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