class_docstr: 1D upscaling layer
  
  Performs 1D upscaling over the trailing axis of a 3D input tensor.
  
  Parameters
  ----------
  incoming : a :class:`Layer` instance or tuple
      The layer feeding into this layer, or the expected input shape.
  
  scale_factor : integer or iterable
      The scale factor. If an iterable, it should have one element.
  
  mode : {'repeat', 'dilate'}
      Upscaling mode: repeat element values or upscale leaving zeroes between
      upscaled elements. Default is 'repeat'.
  
  **kwargs
      Any additional keyword arguments are passed to the :class:`Layer`
      superclass.
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code: def __init__(self, incoming, scale_factor, mode="repeat", **kwargs):
      super(Upscale1DLayer, self).__init__(incoming, **kwargs)
  
      self.scale_factor = as_tuple(scale_factor, 1)
  
      if self.scale_factor[0] < 1:
          raise ValueError(
              "Scale factor must be >= 1, not {0}".format(
                  self.scale_factor
              )
          )
  
      if mode not in {"repeat", "dilate"}:
          msg = "Mode must be either 'repeat' or 'dilate', not {0}"
          raise ValueError(msg.format(mode))
      self.mode = mode
  
imports: import theano.tensor
  from .base import Layer
  from ..utils import as_tuple
label_desc: Use image node_id 1 to create a new Upscale1DLayer object from inherited base classes: Layer with example: obj = Upscale1DLayer(incoming, scale_factor, mode)