[Format] Add config lints (#892)

configs/eval_subjective_mtbench.py

@@ -24,8 +24,8 @@ api_meta_template = dict(
 
 _meta_template = dict(
     round=[
-        dict(role="HUMAN", begin='\n<|im_start|>user\n', end='<|im_end|>'),
-        dict(role="BOT", begin="\n<|im_start|>assistant\n", end='<|im_end|>', generate=True),
+        dict(role='HUMAN', begin='\n<|im_start|>user\n', end='<|im_end|>'),
+        dict(role='BOT', begin='\n<|im_start|>assistant\n', end='<|im_end|>', generate=True),
     ],
 )
 # -------------Inference Stage ----------------------------------------
@@ -34,7 +34,7 @@ models = [
     dict(
         type=HuggingFaceCausalLM,
         abbr='qwen-7b-chat-hf',
-        path="Qwen/Qwen-7B-Chat",
+        path='Qwen/Qwen-7B-Chat',
         tokenizer_path='Qwen/Qwen-7B-Chat',
         model_kwargs=dict(
             device_map='auto',

configs/eval_teval.py

@@ -16,7 +16,7 @@ meta_template_system_patches = {
     'internlm2-chat-20b-hf': dict(role='SYSTEM', begin='<|im_start|>system\n', end='<|im_end|>\n'),
 }
 
-_origin_models = sum([v for k, v in locals().items() if k.endswith("_model")], [])
+_origin_models = sum([v for k, v in locals().items() if k.endswith('_model')], [])
 models = []
 for m in _origin_models:
     m = deepcopy(m)

configs/models/accessory/accessory_llama2_7b.py

@@ -6,7 +6,7 @@ from opencompass.models import LLaMA2AccessoryModel
 
 models = [
     dict(
-        abbr="Accessory_llama2_7b",
+        abbr='Accessory_llama2_7b',
         type=LLaMA2AccessoryModel,
 
         # additional_stop_symbols=["###"],  # for models tuned with chat template  # noqa
@@ -18,10 +18,10 @@ models = [
         #   - consolidated.00.pth
         #   - params.json
         #   - tokenizer.model
-        pretrained_path="path/to/Llama-2-7b/",
-        llama_type="llama",
-        llama_config="path/to/Llama-2-7b/params.json",
-        tokenizer_path="path/to/Llama-2-7b/tokenizer.model",
+        pretrained_path='path/to/Llama-2-7b/',
+        llama_type='llama',
+        llama_config='path/to/Llama-2-7b/params.json',
+        tokenizer_path='path/to/Llama-2-7b/tokenizer.model',
         with_visual=False,
         max_seq_len=4096,
         quant=False,

configs/models/accessory/accessory_mixtral_8x7b.py

@@ -6,7 +6,7 @@ from opencompass.models import LLaMA2AccessoryModel
 
 models = [
     dict(
-        abbr="Accessory_mixtral_8x7b",
+        abbr='Accessory_mixtral_8x7b',
         type=LLaMA2AccessoryModel,
 
         # additional_stop_symbols=["###"],  # for models tuned with chat template  # noqa
@@ -15,7 +15,7 @@ models = [
         # <begin> kwargs for accessory.MetaModel.from_pretrained
         # download from https://huggingface.co/Alpha-VLLM/MoE-Mixtral-7B-8Expert/tree/main/converted_sparse  # noqa
         # see https://llama2-accessory.readthedocs.io/en/latest/projects/mixtral-8x7b.html for more details  # noqa
-        pretrained_path="path/to/MoE-Mixtral-7B-8Expert/converted_sparse",
+        pretrained_path='path/to/MoE-Mixtral-7B-8Expert/converted_sparse',
         llama_type=None,  # None for automatic probe from pretrained_path
         llama_config=None,  # None for automatic probe from pretrained_path
         tokenizer_path=None,  # None for automatic probe from pretrained_path

configs/models/accessory/accessory_sphinx_v2_1k.py

@@ -6,14 +6,14 @@ from opencompass.models import LLaMA2AccessoryModel
 
 models = [
     dict(
-        abbr="Accessory_sphinx_v2_1k",
+        abbr='Accessory_sphinx_v2_1k',
         type=LLaMA2AccessoryModel,
 
-        additional_stop_symbols=["###"],  # for models tuned with chat template
+        additional_stop_symbols=['###'],  # for models tuned with chat template
 
         # <begin> kwargs for accessory.MetaModel.from_pretrained
         # download from https://huggingface.co/Alpha-VLLM/LLaMA2-Accessory/tree/main/finetune/mm/SPHINX/SPHINX-v2-1k  # noqa
-        pretrained_path="path/to/sphinx_v2_1k",
+        pretrained_path='path/to/sphinx_v2_1k',
         llama_type=None,  # None for automatic probe from pretrained_path
         llama_config=None,  # None for automatic probe from pretrained_path
         tokenizer_path=None,  # None for automatic probe from pretrained_path

configs/models/alaya/alaya.py

@@ -5,7 +5,7 @@ models = [
     dict(
         type=AlayaLM,
         abbr='alaya-7b-hf',
-        path="DataCanvas/Alaya-7B-Base",
+        path='DataCanvas/Alaya-7B-Base',
         tokenizer_path='DataCanvas/Alaya-7B-Base',
         tokenizer_kwargs=dict(padding_side='left',
                         truncation_side='left',

configs/models/aquila/hf_aquilachat2_34b.py

@@ -11,7 +11,7 @@ models = [
     dict(
         type=HuggingFaceCausalLM,
         abbr='aquilachat2-34b-hf',
-        path="BAAI/AquilaChat2-34B",
+        path='BAAI/AquilaChat2-34B',
         tokenizer_path='BAAI/AquilaChat2-34B',
         model_kwargs=dict(
             device_map='auto',

configs/models/aquila/hf_aquilachat2_34b_16k.py

@@ -12,7 +12,7 @@ models = [
     dict(
         type=HuggingFaceCausalLM,
         abbr='aquilachat2-34b-16k-hf',
-        path="BAAI/AquilaChat2-34B-16K",
+        path='BAAI/AquilaChat2-34B-16K',
         tokenizer_path='BAAI/AquilaChat2-34B-16K',
         model_kwargs=dict(
             device_map='auto',

configs/models/aquila/hf_aquilachat2_7b.py

@@ -11,7 +11,7 @@ models = [
     dict(
         type=HuggingFaceCausalLM,
         abbr='aquilachat2-7b-hf',
-        path="BAAI/AquilaChat2-7B",
+        path='BAAI/AquilaChat2-7B',
         tokenizer_path='BAAI/AquilaChat2-7B',
         model_kwargs=dict(
             device_map='auto',

configs/models/aquila/hf_aquilachat2_7b_16k.py

@@ -12,7 +12,7 @@ models = [
     dict(
         type=HuggingFaceCausalLM,
         abbr='aquilachat2-7b-16k-hf',
-        path="BAAI/AquilaChat2-7B-16K",
+        path='BAAI/AquilaChat2-7B-16K',
         tokenizer_path='BAAI/AquilaChat2-7B-16K',
         model_kwargs=dict(
             device_map='auto',

configs/models/baichuan/hf_baichuan2_13b_chat.py

@@ -11,7 +11,7 @@ models = [
     dict(
         type=HuggingFaceCausalLM,
         abbr='baichuan2-13b-chat-hf',
-        path="baichuan-inc/Baichuan2-13B-Chat",
+        path='baichuan-inc/Baichuan2-13B-Chat',
         tokenizer_path='baichuan-inc/Baichuan2-13B-Chat',
         tokenizer_kwargs=dict(
             padding_side='left',

configs/models/baichuan/hf_baichuan2_7b_chat.py

@@ -11,7 +11,7 @@ models = [
     dict(
         type=HuggingFaceCausalLM,
         abbr='baichuan2-7b-chat-hf',
-        path="baichuan-inc/Baichuan2-7B-Chat",
+        path='baichuan-inc/Baichuan2-7B-Chat',
         tokenizer_path='baichuan-inc/Baichuan2-7B-Chat',
         tokenizer_kwargs=dict(
             padding_side='left',

configs/models/baichuan/hf_baichuan_13b_base.py

@@ -5,7 +5,7 @@ models = [
     dict(
         type=HuggingFaceCausalLM,
         abbr='baichuan-13b-base-hf',
-        path="baichuan-inc/Baichuan-13B-Base",
+        path='baichuan-inc/Baichuan-13B-Base',
         tokenizer_path='baichuan-inc/Baichuan-13B-Base',
         tokenizer_kwargs=dict(padding_side='left',
                               truncation_side='left',

configs/models/baichuan/hf_baichuan_13b_chat.py

@@ -5,7 +5,7 @@ models = [
     dict(
         type=HuggingFaceCausalLM,
         abbr='baichuan-13b-chat-hf',
-        path="baichuan-inc/Baichuan-13B-Chat",
+        path='baichuan-inc/Baichuan-13B-Chat',
         tokenizer_path='baichuan-inc/Baichuan-13B-Chat',
         tokenizer_kwargs=dict(padding_side='left',
                               truncation_side='left',

configs/models/baichuan/hf_baichuan_7b.py

@@ -5,7 +5,7 @@ models = [
     dict(
         type=HuggingFaceCausalLM,
         abbr='baichuan-7b-hf',
-        path="baichuan-inc/baichuan-7B",
+        path='baichuan-inc/baichuan-7B',
         tokenizer_path='baichuan-inc/baichuan-7B',
         tokenizer_kwargs=dict(padding_side='left',
                               truncation_side='left',

configs/models/bluelm/hf_bluelm_7b_chat.py

@@ -11,7 +11,7 @@ models = [
     dict(
         type=HuggingFaceCausalLM,
         abbr='bluelm-7b-chat-hf',
-        path="vivo-ai/BlueLM-7B-Chat",
+        path='vivo-ai/BlueLM-7B-Chat',
         tokenizer_path='vivo-ai/BlueLM-7B-Chat',
         model_kwargs=dict(
             device_map='auto',

configs/models/bluelm/hf_bluelm_7b_chat_32k.py

@@ -11,7 +11,7 @@ models = [
     dict(
         type=HuggingFaceCausalLM,
         abbr='bluelm-7b-chat-32k-hf',
-        path="vivo-ai/BlueLM-7B-Chat-32K",
+        path='vivo-ai/BlueLM-7B-Chat-32K',
         tokenizer_path='vivo-ai/BlueLM-7B-Chat-32K',
         model_kwargs=dict(
             device_map='auto',

configs/models/gemini/gemini_pro.py

@@ -13,7 +13,7 @@ models = [
     type=Gemini,
     path='gemini-pro',
     key='your keys',  # The key will be obtained from Environment, but you can write down your key here as well
-    url = "your url",
+    url = 'your url',
     meta_template=api_meta_template,
     query_per_second=16,
     max_out_len=100,