0270cac779f61a879f74d9495b9156f8f4127478,official/utils/logs/logger.py,BenchmarkFileLogger,log_metric,#BenchmarkFileLogger#Any#Any#Any#Any#Any#,126

Before Change

    with tf.gfile.GFile(
        os.path.join(self._logging_dir, METRIC_LOG_FILE_NAME), "a") as f:
      metric = {
          "name": name,
          "value": float(value),
          "unit": unit,
          "global_step": global_step,
          "timestamp": datetime.datetime.utcnow().strftime(
              _DATE_TIME_FORMAT_PATTERN),
          "extras": extras}
      try:
        json.dump(metric, f)
        f.write("\n")
      except (TypeError, ValueError) as e:

After Change

      global_step: int, the global_step when the metric is logged.
      extras: map of string:string, the extra information about the metric.
    
    metric = _process_metric_to_json(name, value, unit, global_step, extras)
    if metric:
      with tf.gfile.GFile(
          os.path.join(self._logging_dir, METRIC_LOG_FILE_NAME), "a") as f:
        try:
          json.dump(metric, f)
          f.write("\n")
        except (TypeError, ValueError) as e:
          tf.logging.warning("Failed to dump metric to log file: "
                             "name %s, value %s, error %s", name, value, e)

  def log_run_info(self, model_name, dataset_name, run_params):
    Collect most of the TF runtime information for the local env.

    The schema of the run info follows official/benchmark/datastore/schema.

Instances