From 574b4568ffc41d709d27f5882977ab6ff3fe85bd Mon Sep 17 00:00:00 2001
From: gg <fengqian1991@gmail.com>
Date: Tue, 11 Jul 2023 18:36:54 +0800
Subject: [PATCH] flake8

---
 .../finetune_speech_recognition.py            |  3 +-
 .../custom_datasets/audio/asr_dataset.py      | 35 +++++++++++--------
 2 files changed, 21 insertions(+), 17 deletions(-)

diff --git a/examples/pytorch/auto_speech_recognition/finetune_speech_recognition.py b/examples/pytorch/auto_speech_recognition/finetune_speech_recognition.py
index 2fee3a2e..1716d8a0 100644
--- a/examples/pytorch/auto_speech_recognition/finetune_speech_recognition.py
+++ b/examples/pytorch/auto_speech_recognition/finetune_speech_recognition.py
@@ -27,8 +27,7 @@ if __name__ == '__main__':
     from funasr.utils.modelscope_param import modelscope_args
 
     params = modelscope_args(
-        model=
-        'damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch'
+        model='damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch'
     )
     params.output_dir = './checkpoint'  # 模型保存路径
     params.data_path = 'speech_asr_aishell1_trainsets'  # 数据路径，可以为modelscope中已上传数据，也可以是本地数据
diff --git a/modelscope/msdatasets/dataset_cls/custom_datasets/audio/asr_dataset.py b/modelscope/msdatasets/dataset_cls/custom_datasets/audio/asr_dataset.py
index 73a40813..9e64bcb3 100644
--- a/modelscope/msdatasets/dataset_cls/custom_datasets/audio/asr_dataset.py
+++ b/modelscope/msdatasets/dataset_cls/custom_datasets/audio/asr_dataset.py
@@ -15,8 +15,8 @@ class ASRDataset(MsDataset):
 
     @classmethod
     def load_core(cls, data_dir, data_set):
-        wav_file = os.path.join(data_dir, data_set, 'wav.scp')
-        text_file = os.path.join(data_dir, data_set, 'text')
+        wav_file = os.path.join(data_dir, data_set, "wav.scp")
+        text_file = os.path.join(data_dir, data_set, "text")
         with open(wav_file) as f:
             wav_lines = f.readlines()
         with open(text_file) as f:
@@ -24,28 +24,33 @@ class ASRDataset(MsDataset):
         data_list = []
         for wav_line, text_line in zip(wav_lines, text_lines):
             item = {}
-            item['Audio:FILE'] = wav_line.strip().split()[-1]
-            item['Text:LABEL'] = ' '.join(text_line.strip().split()[1:])
+            item["Audio:FILE"] = wav_line.strip().split()[-1]
+            item["Text:LABEL"] = " ".join(text_line.strip().split()[1:])
             data_list.append(item)
         return data_list
 
     @classmethod
-    def load(cls,
-             dataset_name,
-             namespace='speech_asr',
-             train_set='train',
-             dev_set='validation',
-             download_mode=DownloadMode.REUSE_DATASET_IF_EXISTS):
+    def load(
+        cls,
+        dataset_name,
+        namespace="speech_asr",
+        train_set="train",
+        dev_set="validation",
+        download_mode=DownloadMode.REUSE_DATASET_IF_EXISTS,
+    ):
         if os.path.exists(dataset_name):
             data_dir = dataset_name
             ds_dict = {}
-            ds_dict['train'] = cls.load_core(data_dir, train_set)
-            ds_dict['validation'] = cls.load_core(data_dir, dev_set)
-            ds_dict['raw_data_dir'] = data_dir
+            ds_dict["train"] = cls.load_core(data_dir, train_set)
+            ds_dict["validation"] = cls.load_core(data_dir, dev_set)
+            ds_dict["raw_data_dir"] = data_dir
             return ds_dict
         else:
             from modelscope.msdatasets import MsDataset
+
             ds_dict = MsDataset.load(
-                dataset_name=dataset_name, namespace=namespace, download_mode=download_mode)
+                dataset_name=dataset_name,
+                namespace=namespace,
+                download_mode=download_mode,
+            )
             return ds_dict
-