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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def log_run_info(self, model_name):
 """Collect most of the TF runtime information for the local env. The schema of the run info follows official/benchmark/datastore/schema. Args: model_name: string, the name of the model. """

    run_info = {
        "model_name": model_name,
        "machine_config": {},
        "run_date": datetime.datetime.now().strftime(_DATE_TIME_FORMAT_PATTERN)}
    _collect_tensorflow_info(run_info)
    _collect_tensorflow_environment_variables(run_info)
    _collect_cpu_info(run_info)
    _collect_gpu_info(run_info)
    _collect_memory_info(run_info)

    with tf.gfile.GFile(os.path.join(
        self._logging_dir, BENCHMARK_RUN_LOG_FILE_NAME), "w") as f:
      try:
        json.dump(run_info, f)
        f.write("\n")
      except (TypeError, ValueError) as e:
        tf.logging.warning("Failed to dump benchmark run info to log file: %s",
                           e)