code: def get_benchmark_params(root_dir, file_path):
      match = re.match(
          rf"{root_dir}\/(.+?)_(fp\d+)_(true|false)_(true|false)_(\d+)gpus_v(\d+)\/",
          file_path,
      )
      if match is None:
          return False
      else:
          model, dtype, graphs, kernel, gpus, version = match.groups()
          bool_dict = {"true": True, "false": False}
          return {
              "model": model,
              "dtype": dtype,
              "graphs": bool_dict[graphs.lower()],
              "kernel": bool_dict[kernel.lower()],
              "gpus": int(gpus),
              "version": int(version),
          }
  
file_path: H2O/h2o_flexgen/benchmark/third_party/DeepSpeed/benchmarks/inference/collect_results.py
imports: import os
  import re
  import argparse
  import pandas
label_desc: Use image node_id 2 for calling a global function with example usage: get_benchmark_params(root_dir, file_path) and returns: False, dict