add lint

.pre-commit-config-zh-cn.yaml

@@ -45,19 +45,18 @@ repos:
  (?x)^(
  dicts/|
  projects/.*?/dicts/|
- configs/
+ configs/.*?/.*\.txt
  )
  - id: check-yaml
  - id: end-of-file-fixer
  exclude: |
  (?x)^(
  dicts/|
  projects/.*?/dicts/|
- configs/
+ configs/.*?/.*\.txt
  )
  - id: requirements-txt-fixer
  - id: double-quote-string-fixer
- exclude: configs/
  - id: check-merge-conflict
  - id: fix-encoding-pragma
  args: ["--remove"]

.pre-commit-config.yaml

@@ -45,19 +45,18 @@ repos:
  (?x)^(
  dicts/|
  projects/.*?/dicts/|
- configs/
+ configs/.*?/.*\.txt
  )
  - id: check-yaml
  - id: end-of-file-fixer
  exclude: |
  (?x)^(
  dicts/|
  projects/.*?/dicts/|
- configs/
+ configs/.*?/.*\.txt
  )
  - id: requirements-txt-fixer
  - id: double-quote-string-fixer
- exclude: configs/
  - id: check-merge-conflict
  - id: fix-encoding-pragma
  args: ["--remove"]

configs/api_examples/eval_api_360.py

@@ -17,7 +17,7 @@
  abbr='360GPT_S2_V9',
  type=AI360GPT,
  path='360GPT_S2_V9',
- key="xxxxxxxxxxxx",
+ key='xxxxxxxxxxxx',
  generation_kwargs={
  'temperature': 0.9,
  'max_tokens': 2048,
@@ -40,4 +40,4 @@
  task=dict(type=OpenICLInferTask)),
 )
 
-work_dir ="./output/api_360GPT_S2_V9"
+work_dir ='./output/api_360GPT_S2_V9'

configs/api_examples/eval_api_baichuan.py

@@ -18,8 +18,8 @@
  type=BaiChuan,
  path='Baichuan2-53B',
  api_key='xxxxxx',
- secret_key="xxxxx",
- url="xxxxx",
+ secret_key='xxxxx',
+ url='xxxxx',
  generation_kwargs={
  'temperature': 0.3,
  'top_p': 0.85,
@@ -41,4 +41,4 @@
  task=dict(type=OpenICLInferTask)),
 )
 
-work_dir = "outputs/api_baichuan53b/"
+work_dir = 'outputs/api_baichuan53b/'

configs/api_examples/eval_api_baidu.py

@@ -39,4 +39,4 @@
  task=dict(type=OpenICLInferTask)),
 )
 
-work_dir = "outputs/api_erniebot/"
+work_dir = 'outputs/api_erniebot/'

configs/api_examples/eval_api_bytedance.py

@@ -18,8 +18,8 @@
  abbr='skylark-pro-public',
  type=ByteDance,
  path='skylark-pro-public',
- accesskey="xxxxxxx",
- secretkey="xxxxxxx",
+ accesskey='xxxxxxx',
+ secretkey='xxxxxxx',
  url='xxxxxx',
  generation_kwargs={
  'temperature': 0.7,
@@ -41,4 +41,4 @@
  task=dict(type=OpenICLInferTask)),
 )
 
-work_dir = "outputs/api_bytedance/"
+work_dir = 'outputs/api_bytedance/'

configs/api_examples/eval_api_minimax.py

@@ -34,4 +34,4 @@
  task=dict(type=OpenICLInferTask)),
 )
 
-work_dir = "outputs/api_minimax/"
+work_dir = 'outputs/api_minimax/'

configs/api_examples/eval_api_moonshot.py

@@ -37,4 +37,4 @@
  task=dict(type=OpenICLInferTask)),
 )
 
-work_dir = "outputs/api_moonshot/"
+work_dir = 'outputs/api_moonshot/'

configs/api_examples/eval_api_nanbeige.py

@@ -18,7 +18,7 @@
  abbr='nanbeige-plus',
  type=Nanbeige,
  path='nanbeige-plus',
- key="xxxxxx",
+ key='xxxxxx',
  query_per_second=1,
  max_out_len=2048,
  batch_size=8),
@@ -33,4 +33,4 @@
  task=dict(type=OpenICLInferTask)),
 )
 
-work_dir ="./output/nanbeige-plus"
+work_dir ='./output/nanbeige-plus'

configs/api_examples/eval_api_pangu.py

@@ -17,13 +17,13 @@
  abbr='pangu',
  type=PanGu,
  path='pangu',
- access_key="xxxxxx",
- secret_key="xxxxxx",
- url = "xxxxxx",
+ access_key='xxxxxx',
+ secret_key='xxxxxx',
+ url = 'xxxxxx',
  # url of token sever, used for generate token, like "https://xxxxxx.myhuaweicloud.com/v3/auth/tokens",
- token_url = "xxxxxx",
+ token_url = 'xxxxxx',
  # scope-project-name, used for generate token
- project_name = "xxxxxx",
+ project_name = 'xxxxxx',
  query_per_second=1,
  max_out_len=2048,
  max_seq_len=2048,
@@ -39,4 +39,4 @@
  task=dict(type=OpenICLInferTask)),
 )
 
-work_dir = "outputs/api_pangu/"
+work_dir = 'outputs/api_pangu/'

configs/api_examples/eval_api_qwen.py

@@ -37,4 +37,4 @@
  task=dict(type=OpenICLInferTask)),
 )
 
-work_dir = "outputs/api_qwen/"
+work_dir = 'outputs/api_qwen/'

configs/api_examples/eval_api_sensetime.py

@@ -24,17 +24,17 @@
  max_seq_len=2048,
  batch_size=8,
  parameters={
- "temperature": 0.8,
- "top_p": 0.7,
- "max_new_tokens": 1024,
- "repetition_penalty": 1.05,
- "know_ids": [],
- "stream": True,
- "user": "#*#***TestUser***#*#",
- "knowledge_config": {
- "control_level": "normal",
- "knowledge_base_result": False,
- "online_search_result": False
+ 'temperature': 0.8,
+ 'top_p': 0.7,
+ 'max_new_tokens': 1024,
+ 'repetition_penalty': 1.05,
+ 'know_ids': [],
+ 'stream': True,
+ 'user': '#*#***TestUser***#*#',
+ 'knowledge_config': {
+ 'control_level': 'normal',
+ 'knowledge_base_result': False,
+ 'online_search_result': False
  }
  }
  )
@@ -49,4 +49,4 @@
  task=dict(type=OpenICLInferTask)),
 )
 
-work_dir = "outputs/api_sensetime/"
+work_dir = 'outputs/api_sensetime/'

configs/api_examples/eval_api_xunfei.py

@@ -17,22 +17,22 @@
  dict(
  abbr='Spark-v1-1',
  type=XunFei,
- appid="xxxx",
+ appid='xxxx',
  path='ws://spark-api.xf-yun.com/v1.1/chat',
- api_secret = "xxxxxxx",
- api_key = "xxxxxxx",
+ api_secret = 'xxxxxxx',
+ api_key = 'xxxxxxx',
  query_per_second=1,
  max_out_len=2048,
  max_seq_len=2048,
  batch_size=8),
  dict(
  abbr='Spark-v3-1',
  type=XunFei,
- appid="xxxx",
+ appid='xxxx',
  domain='generalv3',
  path='ws://spark-api.xf-yun.com/v3.1/chat',
- api_secret = "xxxxxxxx",
- api_key = "xxxxxxxxx",
+ api_secret = 'xxxxxxxx',
+ api_key = 'xxxxxxxxx',
  query_per_second=1,
  max_out_len=2048,
  max_seq_len=2048,
@@ -48,4 +48,4 @@
  task=dict(type=OpenICLInferTask)),
 )
 
-work_dir = "outputs/api_xunfei/"
+work_dir = 'outputs/api_xunfei/'

configs/api_examples/eval_api_zhipu.py

@@ -29,7 +29,7 @@
  abbr='chatglm_pro',
  type=ZhiPuAI,
  path='chatglm_pro',
- key='xxxxxxxxxxxx', 
+ key='xxxxxxxxxxxx',
  query_per_second=1,
  max_out_len=2048,
  max_seq_len=2048,
@@ -45,4 +45,4 @@
  task=dict(type=OpenICLInferTask)),
 )
 
-work_dir = "outputs/api_zhipu/"
+work_dir = 'outputs/api_zhipu/'

configs/api_examples/eval_api_zhipu_v2.py

@@ -64,4 +64,4 @@
  task=dict(type=OpenICLInferTask)),
 )
 
-work_dir = "outputs/api_zhipu_v2/"
+work_dir = 'outputs/api_zhipu_v2/'

configs/dataset_collections/chat_OC15.py

@@ -19,4 +19,4 @@
  from ..datasets.gpqa.gpqa_gen_4baadb import gpqa_datasets
  from ..datasets.IFEval.IFEval_gen_3321a3 import ifeval_datasets
 
-datasets = sum((v for k, v in locals().items() if k.endswith("_datasets")), [])
+datasets = sum((v for k, v in locals().items() if k.endswith('_datasets')), [])

configs/datasets/ARC_c/ARC_c_clean_ppl.py

@@ -12,29 +12,29 @@
  prompt_template=dict(
  type=PromptTemplate,
  template={
- "A":
+ 'A':
  dict(
  round=[
- dict(role="HUMAN", prompt="Question: {question}\nAnswer: "),
- dict(role="BOT", prompt="{textA}")
+ dict(role='HUMAN', prompt='Question: {question}\nAnswer: '),
+ dict(role='BOT', prompt='{textA}')
  ], ),
- "B":
+ 'B':
  dict(
  round=[
- dict(role="HUMAN", prompt="Question: {question}\nAnswer: "),
- dict(role="BOT", prompt="{textB}")
+ dict(role='HUMAN', prompt='Question: {question}\nAnswer: '),
+ dict(role='BOT', prompt='{textB}')
  ], ),
- "C":
+ 'C':
  dict(
  round=[
- dict(role="HUMAN", prompt="Question: {question}\nAnswer: "),
- dict(role="BOT", prompt="{textC}")
+ dict(role='HUMAN', prompt='Question: {question}\nAnswer: '),
+ dict(role='BOT', prompt='{textC}')
  ], ),
- "D":
+ 'D':
  dict(
  round=[
- dict(role="HUMAN", prompt="Question: {question}\nAnswer: "),
- dict(role="BOT", prompt="{textD}")
+ dict(role='HUMAN', prompt='Question: {question}\nAnswer: '),
+ dict(role='BOT', prompt='{textD}')
  ], ),
  }),
  retriever=dict(type=ZeroRetriever),

configs/datasets/ARC_c/ARC_c_gen_1e0de5.py

@@ -6,18 +6,18 @@
 from opencompass.utils.text_postprocessors import first_option_postprocess
 
 ARC_c_reader_cfg = dict(
- input_columns=["question", "textA", "textB", "textC", "textD"],
- output_column="answerKey")
+ input_columns=['question', 'textA', 'textB', 'textC', 'textD'],
+ output_column='answerKey')
 
 ARC_c_infer_cfg = dict(
  prompt_template=dict(
  type=PromptTemplate,
  template=dict(
  round=[
  dict(
- role="HUMAN",
+ role='HUMAN',
  prompt=
- "Question: {question}\nA. {textA}\nB. {textB}\nC. {textC}\nD. {textD}\nAnswer:"
+ 'Question: {question}\nA. {textA}\nB. {textB}\nC. {textC}\nD. {textD}\nAnswer:'
  )
  ], ),
  ),
@@ -27,15 +27,15 @@
 
 ARC_c_eval_cfg = dict(
  evaluator=dict(type=AccEvaluator),
- pred_role="BOT",
+ pred_role='BOT',
  pred_postprocessor=dict(type=first_option_postprocess, options='ABCD'),
 )
 
 ARC_c_datasets = [
  dict(
- abbr="ARC-c",
+ abbr='ARC-c',
  type=ARCDataset,
- path="./data/ARC/ARC-c/ARC-Challenge-Dev.jsonl",
+ path='./data/ARC/ARC-c/ARC-Challenge-Dev.jsonl',
  reader_cfg=ARC_c_reader_cfg,
  infer_cfg=ARC_c_infer_cfg,
  eval_cfg=ARC_c_eval_cfg,

configs/datasets/ARC_c/ARC_c_ppl_2ef631.py

@@ -14,10 +14,10 @@
  template={
  opt: dict(
  round=[
- dict(role="HUMAN", prompt=f"{{question}}\nA. {{textA}}\nB. {{textB}}\nC. {{textC}}\nD. {{textD}}"),
- dict(role="BOT", prompt=f"Answer: {opt}"),
+ dict(role='HUMAN', prompt=f'{{question}}\nA. {{textA}}\nB. {{textB}}\nC. {{textC}}\nD. {{textD}}'),
+ dict(role='BOT', prompt=f'Answer: {opt}'),
  ]
- ) for opt in ["A", "B", "C", "D"]
+ ) for opt in ['A', 'B', 'C', 'D']
  },
  ),
  retriever=dict(type=ZeroRetriever),