(a, axes=None)
return utils.tensor_to_ndarray(tf.transpose(a=a.data, perm=axes))
Permutes dimensions of the array.

  Args:
    a: array_like. Could be an ndarray, a Tensor or any object that can
      be converted to a Tensor using `tf.convert_to_tensor`.
    axes: array_like. A list of ints with length rank(a) or None specifying the
      order of permutation. The i'th dimension of the output array corresponds
      to axes[i]'th dimension of the `a`. If None, the axes are reversed.

  Returns:
    An ndarray.
Permutes dimensions of the array.
Permutes dimensions of the array .
def transpose(a, axes=None):
  """Permutes dimensions of the array.

  Args:
    a: array_like. Could be an ndarray, a Tensor or any object that can
      be converted to a Tensor using `tf.convert_to_tensor`.
    axes: array_like. A list of ints with length rank(a) or None specifying the
      order of permutation. The i'th dimension of the output array corresponds
      to axes[i]'th dimension of the `a`. If None, the axes are reversed.

  Returns:
    An ndarray.
  """
  a = asarray(a)
  if axes is not None:
    axes = asarray(axes)
  return utils.tensor_to_ndarray(tf.transpose(a=a.data, perm=axes))
def transpose ( a , axes = None ) : a = asarray ( a ) if axes is not None : axes = asarray ( axes ) return utils . tensor_to_ndarray ( tf . transpose ( a = a . data , perm = axes ) )