def METHOD_NAME(outs):
    """Schedule for batch_norm
    Parameters
    ----------
    outs: Array of Tensor
          The computation graph description of batch_norm
          in the format of an array of tensors.
    Returns
    -------
    sch: Schedule
        The computation schedule for the op.
    """
    s = te.create_schedule([x.op for x in outs])
    # only parallelize outer dimensions up to axis
    output_op = outs[0].op
    axis = output_op.axis
    outer_axes = [output_op.axis[i] for i in range(0, len(axis) - 1)]
    fused_outer_axes = s[output_op].fuse(*outer_axes)
    s[output_op].parallel(fused_outer_axes)
    # when scale or center is enabled
    if "divide" not in output_op.name:
        div = output_op.input_tensors[0]
        substract = s[div].op.input_tensors[0]
        s[div].compute_inline()
        s[substract].compute_inline()
    return s