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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def asarray(self, out=None):
 """Extract the data of this array as a ``numpy.ndarray``. This method is invoked when calling `numpy.asarray` on this tensor. Parameters out : `numpy.ndarray`, optional Array in which the result should be written in-place. Has to be contiguous and of the correct dtype. Returns ------- asarray : `numpy.ndarray` Numpy array with the same data type as ``self``. If ``out`` was given, the returned object is a reference to it. Examples -------- array([ 1., 2., 3.], dtype=float32) True array([ 1., 2., 3.], dtype=float32) True array([[ 1., 1., 1.], [ 1., 1., 1.]]) """

        if out is None:
            return self.data
        else:
            out[:] = self.data
            return out