code: def match(self, node):
      is_dense = node.class_name == "Dense"
      input_node = node.get_input_node()
      is_input_bnqt = (
          input_node is not None
          and input_node.class_name == "BatchNormalizationQuantizedTanh"
      )
      quantizer = node.get_attr("weight_quantizer")
      is_binary_ternary = quantizer is not None and (
          quantizer.__class__.__name__ == "BinaryQuantizer"
          or quantizer.__class__.__name__ == "TernaryQuantizer"
      )
      return is_dense and is_input_bnqt and is_binary_ternary
  
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 1 for calling the QuantizeDenseOutput obj's underlying member method code with example usage: obj.match(node) and returns: unknown