code: def format(self, node):
      params = self._default_function_params(node)
      if node.get_attr("quantize") == 2:
          params["quantize"] = "binary"
          params["threshold"] = node.get_weights("threshold").name
      elif node.get_attr("quantize") == 3:
          params["quantize"] = "ternary"
          params["threshold"] = (
              node.get_weights("threshold_hi").name
              + ", "
              + node.get_weights("threshold_lo").name
          )
  
      return self.template.format(**params)
  
imports: import numpy
  from hls4ml.backends.fpga.fpga_layers import BatchNormalizationQuantizedTanh
  from hls4ml.backends.template import FunctionCallTemplate, LayerConfigTemplate
  from hls4ml.model.layers import BatchNormalization, register_layer
  from hls4ml.model.optimizer import OptimizerPass
  from hls4ml.model.types import IntegerPrecisionType, NamedType, XnorPrecisionType
label_desc: Use image node_id 2 for calling the BatchNormalizationQuantizedTanhFunctionTemplate obj's underlying member method code with example usage: obj.format(node) and returns: self