code: def parse_gemm_layer(
      reader, node, inputs_map, input_shapes, graph, config
  ):
      layer = {}
  
      layer["class_name"] = "Dense"
      layer["name"] = node.name
      layer["inputs"] = get_onnx_input_name(node, graph)
  
      tran_weight = get_onnx_attribute(node, "transB", 0)
      reader.add_input(layer["name"], node.input, tran_weight)
  
      weights_shape = reader.get_weights_data(
          layer["name"], "kernel"
      ).shape
      layer["n_in"] = weights_shape[0]
      layer["n_out"] = weights_shape[1]
  
      output_shape = input_shapes[0][:]
      output_shape[-1] = layer["n_out"]
  
      return layer, output_shape
  
label_desc: Use image node_id 1 for calling a global function with example usage: parse_gemm_layer(reader, node, inputs_map, input_shapes, graph, config) and returns: layer,  output_shape