Upsampling layer for 1D inputs.


Repeats each temporal step size times along the time axis.


  size = 2L, 
  batch_size = NULL, 
  name = NULL, 
  trainable = NULL, 
  weights = NULL 


Arguments Description
object What to compose the new Layer instance with. Typically a Sequential model or a Tensor (e.g., as returned by layer_input()). The return value depends on object. If object is:
- missing or NULL, the Layer instance is returned.
- a Sequential model, the model with an additional layer is returned.
- a Tensor, the output tensor from layer_instance(object) is returned.
size integer. Upsampling factor.
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

3D tensor with shape: (batch, steps, features).

Output shape

3D tensor with shape: (batch, upsampled_steps, features).

See Also

Other convolutional layers: layer_conv_1d_transpose(), 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_1d(), layer_depthwise_conv_2d(), layer_separable_conv_1d(), layer_separable_conv_2d(), layer_upsampling_2d(), layer_upsampling_3d(), layer_zero_padding_1d(), layer_zero_padding_2d(), layer_zero_padding_3d()