code: def parse_reshape_layer(
      reader, node, inputs_map, input_shapes, graph, config
  ):
      layer = {}
      layer["name"] = node.name
      layer["class_name"] = "Reshape"
      layer["inputs"] = get_onnx_input_name(node, graph)
  
      target_shape = list(
          [x for x in graph.initializer if x.name == node.input[1]][
              0
          ].int64_data
      )[1:]
  
      if -1 in target_shape:  # Need to infer shape for -1
          print("WARNING: Inferring -1 shape ... ")
          dummy_x = np.ones(input_shapes[0][1:])
          dummy_y = np.reshape(dummy_x, target_shape)
          target_shape = list(dummy_y.shape)
  
      layer["target_shape"] = target_shape
      output_shape = input_shapes[0][:1] + layer["target_shape"]
  
      return layer, output_shape
  
label_desc: Use image node_id 2 for calling a global function with example usage: parse_reshape_layer(reader, node, inputs_map, input_shapes, graph, config) and returns: layer,  output_shape