Modify the implementation and comments accroding to the suggestions by reviewer

.

Author: hylin2002

src/run_benchmark.py

@@ -217,11 +217,12 @@ def write_to_csv(csv_path: str, calculate_metrics_results: List[Dict[str, Any]])
  if not isinstance(calculate_metrics_results[0], dict):
  raise ValueError("metrics result is not a dict.")
 
- def flatten_dict(current_dict: Dict, output_dict: Dict) -> Dict:
+ def flatten_dict(current_dict: Dict) -> Dict:
  """Recursively flattens a nested dictionary."""
+ output_dict = {}
  for key, val in current_dict.items():
  if isinstance(val, Dict):
- output_dict = flatten_dict(val, output_dict)
+ output_dict.update(flatten_dict(val))
  else:
  # Try to evaluate string-formatted literals (e.g., "[1, 2, 3]")
  try:
@@ -233,10 +234,7 @@ def flatten_dict(current_dict: Dict, output_dict: Dict) -> Dict:
 
  def convert_dict_to_df(target_dict: Dict) -> pd.DataFrame:
  """Converts a single benchmark result dictionary to a pandas DataFrame."""
- flattened_dict = flatten_dict(target_dict, {})
-
- # TODO(user): Generalize this hard-coded value if needed.
- flattened_dict["dtype"] = "bfloat16"
+ flattened_dict = flatten_dict(target_dict)
 
  # This section is specific to collective benchmarks that produce
  # 'ici_average_time_ms_list'.
@@ -249,7 +247,6 @@ def convert_dict_to_df(target_dict: Dict) -> pd.DataFrame:
  for key, val in ici_average_time_ms_statistics.items():
  flattened_dict["ici_average_time_ms_" + key] = val
 
-
  # Convert list to JSON string for CSV storage.
  flattened_dict["ici_average_time_ms_list"] = json.dumps(
  flattened_dict["ici_average_time_ms_list"]
@@ -258,7 +255,6 @@ def convert_dict_to_df(target_dict: Dict) -> pd.DataFrame:
  df = pd.DataFrame(flattened_dict, index=[0])
  return df
 
- # Create a list of DataFrames and concatenate them once for efficiency.
  # TODO(hylin2002@)
  # This is a temporary workaround to generate a properly formatted CSV file for the output metrics.
  # We should revert this PR and refactor the code such that metrics object is a flatten dict that can be easily exported as a CSV.