text: # Copyright (c) 2020, Xilinx
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  #   this software without specific prior written permission.
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  import numpy as np
  from onnx import helper as oh
  
  from finn.core.datatype import DataType
  from finn.transformation import Transformation
  
  
  class ConvertSignToThres(Transformation):
      """Convert Sign node instances to MultiThreshold with threshold at 0."""
  
      def apply(self, model):
          graph = model.graph
          graph_modified = False
          node_ind = 0
          for n in graph.node:
              node_ind += 1
              if n.op_type == "Sign":
                  sign_in_name = n.input[0]
                  sign_out_name = n.output[0]
                  # find consumer
                  consumer = model.find_consumer(sign_out_name)
                  assert (
                      consumer is not None
                  ), """There is no consumer of the
                  sign_out tensor."""
                  # create thresholds
                  thres_param_name = model.make_new_valueinfo_name()
                  thres_param = np.asarray([[0]], dtype=np.float32)
                  model.set_initializer(thres_param_name, thres_param)
                  # create a new node
                  mt_node = oh.make_node(
                      "MultiThreshold",
                      [sign_in_name, thres_param_name],
                      [sign_out_name],
                      domain="finn",
                      out_scale=2.0,
                      out_bias=-1.0,
                      out_dtype="BIPOLAR",
                  )
                  # remove old node, add new node to graph at correct position
                  graph.node.insert(node_ind, mt_node)
                  graph.node.remove(n)
                  # add quantization annotations
                  model.set_tensor_datatype(sign_out_name, DataType.BIPOLAR)
                  graph_modified = True
          return (model, graph_modified)
  