class_docstr: It is a 1D sub-pixel up-sampling layer.
  
  Calls a TensorFlow function that directly implements this functionality.
  We assume input has dim (batch, width, r)
  
  Parameters
  ------------
  scale : int
      The up-scaling ratio, a wrong setting will lead to Dimension size error.
  act : activation function
      The activation function of this layer.
  in_channels : int
      The number of in channels.
  name : str
      A unique layer name.
  
  Examples
  ----------
  With TensorLayer
  
  >>> net = tl.layers.Input([8, 25, 32], name='input')
  >>> subpixelconv1d = tl.layers.SubpixelConv1d(scale=2, name='subpixelconv1d')(net)
  >>> print(subpixelconv1d)
  >>> output shape : (8, 50, 16)
  
  References
  -----------
  `Audio Super Resolution Implementation <https://github.com/kuleshov/audio-super-res/blob/master/src/models/layers/subpixel.py>`__.
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code: def _PS(self, I, r):
      X = tf.transpose(a=I, perm=[2, 1, 0])  # (r, w, b)
      X = tf.batch_to_space(
          input=X, block_shape=[r], crops=[[0, 0]]
      )  # (1, r*w, b)
      X = tf.transpose(a=X, perm=[2, 1, 0])
      return X
  
file_path: TensorLayer/tensorlayer/layers/convolution/super_resolution.py
imports: import tensorflow
  import tensorlayer
  from tensorlayer import logging
  from tensorlayer.decorators import deprecated_alias, private_method
  from tensorlayer.layers.core import Layer
label_desc: Use image node_id 5 for calling the SubpixelConv1d obj's underlying member method code with example usage: obj._PS(I, r) and returns: X