class_docstr: A layer that transposes the dimension of a tensor.
  
  See `tf.transpose() <https://www.tensorflow.org/api_docs/python/tf/transpose>`__ .
  
  Parameters
  ----------
  perm: list of int
      The permutation of the dimensions, similar with ``numpy.transpose``.
      If None, it is set to (n-1...0), where n is the rank of the input tensor.
  conjugate: bool
      By default False. If True, returns the complex conjugate of complex numbers (and transposed)
      For example [[1+1j, 2+2j]] --> [[1-1j], [2-2j]]
  name : str
      A unique layer name.
  
  Examples
  ----------
  >>> x = tl.layers.Input([8, 4, 3], name='input')
  >>> y = tl.layers.Transpose(perm=[0, 2, 1], conjugate=False, name='trans')(x)
  (8, 3, 4)
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code: def __init__(
      self, perm=None, conjugate=False, name=None
  ):  #'transpose'):
      super(Transpose, self).__init__(name)
      self.perm = perm
      self.conjugate = conjugate
  
      logging.info(
          "Transpose  %s: perm: %s, conjugate: %s"
          % (self.name, self.perm, self.conjugate)
      )
  
      self.build()
      self._built = True
  
imports: import tensorflow
  from tensorlayer import logging
  from tensorlayer.decorators import deprecated_alias
  from tensorlayer.layers.core import Layer
  from tensorlayer.layers.utils import flatten_reshape
label_desc: Use image node_id 1 to create a new Transpose object from inherited base classes: Layer with example: obj = Transpose(perm, conjugate, name)