Use Python 3.9 syntax in examples (#37279)

Signed-off-by: cyy <cyyever@outlook.com>

examples/legacy/seq2seq/run_distributed_eval.py

@@ -19,7 +19,6 @@ import time
 from json import JSONDecodeError
 from logging import getLogger
 from pathlib import Path
-from typing import Dict, List
 
 import torch
 from torch.utils.data import DataLoader
@@ -55,10 +54,10 @@ def eval_data_dir(
     task="summarization",
     local_rank=None,
     num_return_sequences=1,
-    dataset_kwargs: Dict = None,
+    dataset_kwargs: dict = None,
     prefix="",
     **generate_kwargs,
-) -> Dict:
+) -> dict:
     """Run evaluation on part of the data for one gpu and save to {save_dir}/rank_{rank}_output.json"""
     model_name = str(model_name)
     assert local_rank is not None
@@ -211,7 +210,7 @@ def run_generate():
         calc_bleu = "translation" in args.task
         score_fn = calculate_bleu if calc_bleu else calculate_rouge
         metric_name = "bleu" if calc_bleu else "rouge"
-        metrics: Dict = score_fn(preds, labels)
+        metrics: dict = score_fn(preds, labels)
         metrics["n_obs"] = len(preds)
         runtime = time.time() - start_time
         metrics["seconds_per_sample"] = round(runtime / metrics["n_obs"], 4)
@@ -227,7 +226,7 @@ def run_generate():
             shutil.rmtree(json_save_dir)
 
 
-def combine_partial_results(partial_results) -> List:
+def combine_partial_results(partial_results) -> list:
     """Concatenate partial results into one file, then sort it by id."""
     records = []
     for partial_result in partial_results:
@@ -237,7 +236,7 @@ def combine_partial_results(partial_results) -> List:
     return preds
 
 
-def gather_results_from_each_node(num_replicas, save_dir, timeout) -> List[Dict[str, List]]:
+def gather_results_from_each_node(num_replicas, save_dir, timeout) -> list[dict[str, list]]:
     # WAIT FOR lots of .json files
     start_wait = time.time()
     logger.info("waiting for all nodes to finish")