class_docstr: UpSampling layer for 1D inputs.
  Repeats each temporal step 'length' times along the time axis.
  The input of this layer should be 3D.
  
  When you use this layer as the first layer of a model, you need to provide the argument
  input_shape (a shape tuple, does not include the batch dimension).
  
  # Arguments
  length: Int. UpSampling factor. Default is 2.
  input_shape: A shape tuple, not including batch.
  name: String to set the name of the layer.
        If not specified, its name will by default to be a generated string.
  
  >>> upsampling1d = UpSampling1D(length=3, input_shape=(3, 12))
  creating: createZooKerasUpSampling1D
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code: def __init__(self, length=2, input_shape=None, **kwargs):
      super(UpSampling1D, self).__init__(
          None,
          length,
          list(input_shape) if input_shape else None,
          **kwargs,
      )
  
imports: import sys
  from ..engine.topology import ZooKerasLayer
  from bigdl.dllib.utils.log4Error import *
label_desc: Use image node_id 1 to create a new UpSampling1D object from inherited base classes: ZooKerasLayer with example: obj = UpSampling1D(length, input_shape)