code: def compute_params(architecture):
      layers = [int(layer) for layer in architecture.split("-")]
      params = 0
      for i in range(len(layers) - 1):
          params += layers[i] * layers[i + 1]
      # Add bias terms
      params += sum(layers[1:])
      return params
  
file_path: singa/examples/model_selection/TRAILS-Database-Native-Model-Selection/internal/ml/model_selection/exps/nas_bench_tabular/measure_param_auc.py
imports: import numpy
  import matplotlib
  import matplotlib.pyplot
  import os
  from src.tools.io_tools import read_json
  import matplotlib.ticker
label_desc: Use image node_id 2 for calling a global function with example usage: compute_params(architecture) and returns: params