[Feat] add safety to collections (#185)

* [Feat] add safety to collections

* minor fix

configs/datasets/civilcomments/civilcomments_ppl.py → configs/datasets/civilcomments/civilcomments_clp.py

 from mmengine.config import read_base
 
 with read_base():
-    from .civilcomments_ppl_6a2561 import civilcomments_datasets  # noqa: F401, F403
+    from .civilcomments_clp_a3c5fd import civilcomments_datasets  # noqa: F401, F403

configs/datasets/collections/base_medium.py

@@ -53,5 +53,9 @@ with read_base():
     from ..triviaqa.triviaqa_gen_2121ce import triviaqa_datasets
     from ..flores.flores_gen_806ede import flores_datasets
     from ..crowspairs.crowspairs_ppl_e811e1 import crowspairs_datasets
+    from ..civilcomments.civilcomments_clp_a3c5fd import civilcomments_datasets
+    from ..jigsawmultilingual.jigsawmultilingual_clp_fe50d8 import jigsawmultilingual_datasets
+    from ..realtoxicprompts.realtoxicprompts_gen_7605e4 import realtoxicprompts_datasets
+    from ..truthfulqa.truthfulqa_gen_5ddc62 import truthfulqa_datasets
 
 datasets = sum((v for k, v in locals().items() if k.endswith('_datasets')), [])

configs/datasets/collections/chat_medium.py

@@ -53,5 +53,9 @@ with read_base():
     from ..triviaqa.triviaqa_gen_2121ce import triviaqa_datasets
     from ..flores.flores_gen_806ede import flores_datasets
     from ..crowspairs.crowspairs_gen_21f7cb import crowspairs_datasets
+    from ..civilcomments.civilcomments_clp_a3c5fd import civilcomments_datasets
+    from ..jigsawmultilingual.jigsawmultilingual_clp_fe50d8 import jigsawmultilingual_datasets
+    from ..realtoxicprompts.realtoxicprompts_gen_7605e4 import realtoxicprompts_datasets
+    from ..truthfulqa.truthfulqa_gen_5ddc62 import truthfulqa_datasets
 
 datasets = sum((v for k, v in locals().items() if k.endswith('_datasets')), [])

configs/datasets/jigsawmultilingual/jigsawmultilingual_ppl.py → configs/datasets/jigsawmultilingual/jigsawmultilingual_clp.py

 from mmengine.config import read_base
 
 with read_base():
-    from .jigsawmultilingual_ppl_fe50d8 import jigsawmultilingual_datasets  # noqa: F401, F403
+    from .jigsawmultilingual_clp_fe50d8 import jigsawmultilingual_datasets  # noqa: F401, F403

configs/datasets/realtoxicprompts/realtoxicprompts_gen.py

 from mmengine.config import read_base
 
 with read_base():
-    from .realtoxicprompts_gen_ac723c import realtoxicprompts_datasets  # noqa: F401, F403
+    from .realtoxicprompts_gen_7605e4 import realtoxicprompts_datasets  # noqa: F401, F403

configs/datasets/truthfulqa/truthfulqa_gen_1e7d8d.py

@@ -11,9 +11,7 @@ truthfulqa_reader_cfg = dict(
 
 # TODO: allow empty output-column
 truthfulqa_infer_cfg = dict(
-    prompt_template=dict(
-        type=PromptTemplate,
-        template='{question}'),
+    prompt_template=dict(type=PromptTemplate, template='{question}'),
     retriever=dict(type=ZeroRetriever),
     inferencer=dict(type=GenInferencer))
 
@@ -31,6 +29,7 @@ truthfulqa_eval_cfg = dict(
 
 truthfulqa_datasets = [
     dict(
+        abbr='truthful_qa',
         type=TruthfulQADataset,
         path='truthful_qa',
         name='generation',

configs/datasets/truthfulqa/truthfulqa_gen_5ddc62.py

@@ -31,6 +31,7 @@ truthfulqa_eval_cfg = dict(
 
 truthfulqa_datasets = [
     dict(
+        abbr='truthful_qa',
         type=TruthfulQADataset,
         path='truthful_qa',
         name='generation',

configs/summarizers/medium.py

@@ -10,7 +10,7 @@ with read_base():
     from .groups.jigsaw_multilingual import jigsaw_multilingual_summary_groups
 
 summarizer = dict(
-    dataset_abbrs = [
+    dataset_abbrs=[
         '--------- 考试 Exam ---------',  # category
         # 'Mixed', # subcategory
         "ceval",
@@ -87,8 +87,17 @@ summarizer = dict(
         '--------- 安全 Safety ---------',  # category
         # '偏见', # subcategory
         'crows_pairs',
+        # '有毒性（判别）', # subcategory
+        'civil_comments',
+        # '有毒性（判别）多语言', # subcategory
+        'jigsaw_multilingual',
+        # '有毒性（生成）', # subcategory
+        'real-toxicity-prompts',
+        # '真实性/有用性', # subcategory
+        'truthful_qa',
     ],
-    summary_groups=sum([v for k, v in locals().items() if k.endswith("_summary_groups")], []),
+    summary_groups=sum(
+        [v for k, v in locals().items() if k.endswith("_summary_groups")], []),
     prompt_db=dict(
         database_path='configs/datasets/log.json',
         config_dir='configs/datasets',

opencompass/openicl/icl_inferencer/icl_base_inferencer.py

@@ -147,6 +147,23 @@ class PPLInferencerOutputHandler:
         self.results_dict[str(idx)]['label: ' + str(label)]['prompt'] = prompt
         self.results_dict[str(idx)]['label: ' + str(label)]['PPL'] = ppl
 
+
+class CLPInferencerOutputHandler:
+    results_dict = {}
+
+    def __init__(self) -> None:
+        self.results_dict = {}
+
+    def write_to_json(self, save_dir: str, filename: str):
+        """Dump the result to a json file."""
+        dump_results_dict(self.results_dict, Path(save_dir) / filename)
+
+    def save_ice(self, ice):
+        for idx, example in enumerate(ice):
+            if str(idx) not in self.results_dict.keys():
+                self.results_dict[str(idx)] = {}
+            self.results_dict[str(idx)]['in-context examples'] = example
+
     def save_prompt_and_condprob(self, input, prompt, cond_prob, idx, choices):
         if str(idx) not in self.results_dict.keys():
             self.results_dict[str(idx)] = {}

opencompass/openicl/icl_inferencer/icl_clp_inferencer.py

@@ -13,7 +13,7 @@ from opencompass.registry import ICL_INFERENCERS
 from ..icl_prompt_template import PromptTemplate
 from ..icl_retriever import BaseRetriever
 from ..utils import get_logger
-from .icl_base_inferencer import BaseInferencer, PPLInferencerOutputHandler
+from .icl_base_inferencer import BaseInferencer, CLPInferencerOutputHandler
 
 logger = get_logger(__name__)
 
@@ -79,7 +79,7 @@ class CLPInferencer(BaseInferencer):
                   output_json_filename: Optional[str] = None,
                   normalizing_str: Optional[str] = None) -> List:
         # 1. Preparation for output logs
-        output_handler = PPLInferencerOutputHandler()
+        output_handler = CLPInferencerOutputHandler()
 
         ice = []
 
@@ -88,6 +88,20 @@ class CLPInferencer(BaseInferencer):
         if output_json_filename is None:
             output_json_filename = self.output_json_filename
 
+        # CLP cannot infer with log probability for api models
+        # unless model provided such options which needs specific
+        # implementation, open an issue if you encounter the case.
+        if self.model.is_api:
+            # Write empty file in case always rerun for this model
+            if self.is_main_process:
+                os.makedirs(output_json_filepath, exist_ok=True)
+                err_msg = 'API model is not supported for conditional log '\
+                    'probability inference and skip this exp.'
+                output_handler.results_dict = {'error': err_msg}
+                output_handler.write_to_json(output_json_filepath,
+                                             output_json_filename)
+            raise ValueError(err_msg)
+
         # 2. Get results of retrieval process
         if self.fix_id_list:
             ice_idx_list = retriever.retrieve(self.fix_id_list)
@@ -117,7 +131,7 @@ class CLPInferencer(BaseInferencer):
                 choice_ids = [self.model.tokenizer.encode(c) for c in choices]
                 if self.model.tokenizer.__class__.__name__ == 'ChatGLMTokenizer':  # noqa
                     choice_ids = [c[2:] for c in choice_ids]
-                else:
+                elif hasattr(self.model.tokenizer, 'add_bos_token'):
                     if self.model.tokenizer.add_bos_token:
                         choice_ids = [c[1:] for c in choice_ids]
                     if self.model.tokenizer.add_eos_token:
@@ -135,6 +149,7 @@ class CLPInferencer(BaseInferencer):
                     ice[idx],
                     ice_template=ice_template,
                     prompt_template=prompt_template)
+                prompt = self.model.parse_template(prompt, mode='ppl')
                 if self.max_seq_len is not None:
                     prompt_token_num = get_token_len(prompt)
                     # add one because additional token will be added in the end