[Refactor] Move fix_id_list to Retriever (#442)

* [Refactor] Move fix_id_list to Retriever

* update

* move to base

* fix

opencompass/openicl/icl_inferencer/icl_base_inferencer.py

@@ -25,9 +25,6 @@ class BaseInferencer:
             `JSON` file.
         output_json_filename (:obj:`str`, optional): File name for output
             `JSON` file.
-        api_name (:obj:`str`, optional): Name of API service.
-        call_api (:obj:`bool`): If ``True``, an API for LM models will be used,
-            determined by :obj:`api_name`.
     """
     model = None
 
@@ -38,8 +35,15 @@ class BaseInferencer:
         batch_size: Optional[int] = 1,
         output_json_filepath: Optional[str] = './icl_inference_output',
         output_json_filename: Optional[str] = 'predictions',
+        fix_id_list: Optional[List[int]] = None,
         **kwargs,
     ) -> None:
+
+        if fix_id_list:
+            raise ValueError('Passing fix_id_list to Inferencer is no longer '
+                             'allowed. Please pass it to FixKRetriever '
+                             'instead.')
+
         self.model = model
 
         self.max_seq_len = max_seq_len

opencompass/openicl/icl_inferencer/icl_clp_inferencer.py

@@ -54,7 +54,6 @@ class CLPInferencer(BaseInferencer):
             batch_size: Optional[int] = 1,
             output_json_filepath: Optional[str] = './icl_inference_output',
             output_json_filename: Optional[str] = 'predictions',
-            fix_id_list: Optional[List[int]] = None,
             single_token: bool = True,
             **kwargs) -> None:
         super().__init__(
@@ -66,7 +65,6 @@ class CLPInferencer(BaseInferencer):
             **kwargs,
         )
 
-        self.fix_id_list = fix_id_list
         # TODO: support multiple token
         assert single_token, 'Only support single token choice currently.'
         self.single_token = single_token
@@ -103,10 +101,7 @@ class CLPInferencer(BaseInferencer):
             raise ValueError(err_msg)
 
         # 2. Get results of retrieval process
-        if self.fix_id_list:
-            ice_idx_list = retriever.retrieve(self.fix_id_list)
-        else:
-            ice_idx_list = retriever.retrieve()
+        ice_idx_list = retriever.retrieve()
 
         # 3. Generate in-context examples for testing inputs
         for idx in range(len(ice_idx_list)):

opencompass/openicl/icl_inferencer/icl_gen_inferencer.py

@@ -51,7 +51,6 @@ class GenInferencer(BaseInferencer):
             output_json_filepath: Optional[str] = './icl_inference_output',
             output_json_filename: Optional[str] = 'predictions',
             save_every: Optional[int] = None,
-            fix_id_list: Optional[List[int]] = None,
             **kwargs) -> None:
         super().__init__(
             model=model,
@@ -64,7 +63,6 @@ class GenInferencer(BaseInferencer):
 
         self.gen_field_replace_token = gen_field_replace_token
         self.max_out_len = max_out_len
-        self.fix_id_list = fix_id_list
 
         if self.model.is_api and save_every is None:
             save_every = 1
@@ -85,10 +83,7 @@ class GenInferencer(BaseInferencer):
             output_json_filename = self.output_json_filename
 
         # 2. Get results of retrieval process
-        if 'Fix' in retriever.__class__.__name__:
-            ice_idx_list = retriever.retrieve(self.fix_id_list)
-        else:
-            ice_idx_list = retriever.retrieve()
+        ice_idx_list = retriever.retrieve()
 
         # 3. Generate prompts for testing input
         prompt_list = self.get_generation_prompt_list_from_retriever_indices(
@@ -220,10 +215,7 @@ class GLMChoiceInferencer(GenInferencer):
             output_json_filename = self.output_json_filename
 
         # 2. Get results of retrieval process
-        if 'Fix' in retriever.__class__.__name__:
-            ice_idx_list = retriever.retrieve(self.fix_id_list)
-        else:
-            ice_idx_list = retriever.retrieve()
+        ice_idx_list = retriever.retrieve()
 
         # 3. Generate prompts for testing input
         prompt_list = self.get_generation_prompt_list_from_retriever_indices(

opencompass/openicl/icl_inferencer/icl_ppl_inferencer.py

@@ -41,7 +41,6 @@ class PPLInferencer(BaseInferencer):
             output_json_filepath: Optional[str] = './icl_inference_output',
             output_json_filename: Optional[str] = 'predictions',
             labels: Optional[List] = None,
-            fix_id_list: Optional[List[int]] = None,
             **kwargs) -> None:
         super().__init__(
             model=model,
@@ -53,7 +52,6 @@ class PPLInferencer(BaseInferencer):
         )
 
         self.labels = labels
-        self.fix_id_list = fix_id_list
 
     def inference(self,
                   retriever: BaseRetriever,
@@ -75,10 +73,7 @@ class PPLInferencer(BaseInferencer):
             output_json_filename = self.output_json_filename
 
         # 2. Get results of retrieval process
-        if self.fix_id_list:
-            ice_idx_list = retriever.retrieve(self.fix_id_list)
-        else:
-            ice_idx_list = retriever.retrieve()
+        ice_idx_list = retriever.retrieve()
 
         # 3. Get labels of all the classes
         if self.labels is None:

opencompass/openicl/icl_inferencer/icl_sc_inferencer.py

@@ -52,7 +52,6 @@ class SCInferencer(BaseInferencer):
             output_json_filepath: Optional[str] = './icl_inference_output',
             output_json_filename: Optional[str] = 'predictions',
             save_every: Optional[int] = None,
-            fix_id_list: Optional[List[int]] = None,
             sc_size: Optional[int] = 1,
             infer_type: Optional[str] = '',
             generation_kwargs: dict = {},
@@ -69,7 +68,6 @@ class SCInferencer(BaseInferencer):
         self.gen_field_replace_token = gen_field_replace_token
         self.generation_kwargs = generation_kwargs
         self.max_out_len = max_out_len
-        self.fix_id_list = fix_id_list
         self.sc_size = sc_size
 
         if self.model.is_api and save_every is None:
@@ -91,10 +89,7 @@ class SCInferencer(BaseInferencer):
             output_json_filename = self.output_json_filename
 
         # 2. Get results of retrieval process
-        if 'Fix' in retriever.__class__.__name__:
-            ice_idx_list = retriever.retrieve(self.fix_id_list)
-        else:
-            ice_idx_list = retriever.retrieve()
+        ice_idx_list = retriever.retrieve()
 
         # 3. Generate prompts for testing input
         prompt_list = self.get_generation_prompt_list_from_retriever_indices(

opencompass/openicl/icl_inferencer/icl_tot_inferencer.py

@@ -46,7 +46,6 @@ class ToTInferencer(GenInferencer):
             `save_every` epochs.
         generation_kwargs (:obj:`Dict`, optional): Parameters for the
             :obj:`model.generate()` method.
-        fix_id_list (:obj:`List[int]`, optional): List of indices to fix
         naive_run (:obj:`bool`): if True, run naive IO/CoT sampling instead of
             ToT + BFS.
         prompt_wrapper (:obj:`dict`): wrapper for prompts
@@ -76,7 +75,6 @@ class ToTInferencer(GenInferencer):
             output_json_filepath: Optional[str] = './icl_inference_output',
             output_json_filename: Optional[str] = 'predictions',
             save_every: Optional[int] = None,
-            fix_id_list: Optional[List[int]] = None,
             naive_run: bool = False,
             prompt_wrapper: dict = {},
             prompt_sample: str = 'standard',
@@ -97,7 +95,6 @@ class ToTInferencer(GenInferencer):
             output_json_filename=output_json_filename,
             output_json_filepath=output_json_filepath,
             save_every=save_every,
-            fix_id_list=fix_id_list,
             sc_size=n_evaluate_sample,
             **kwargs,
         )
@@ -319,10 +316,7 @@ class ToTInferencer(GenInferencer):
             output_json_filename = self.output_json_filename
 
         # 2. Get results of retrieval process
-        if 'Fix' in retriever.__class__.__name__:
-            ice_idx_list = retriever.retrieve(self.fix_id_list)
-        else:
-            ice_idx_list = retriever.retrieve()
+        ice_idx_list = retriever.retrieve()
 
         # 3. Generate prompts for testing input
         prompt_list = self.get_generation_prompt_list_from_retriever_indices(

opencompass/openicl/icl_retriever/icl_fix_k_retriever.py

@@ -19,6 +19,8 @@ class FixKRetriever(BaseRetriever):
     Args:
         dataset (`BaseDataset`): Any BaseDataset instances.
             Attributes of ``reader``, ``train`` and ``test`` will be used.
+        fix_id_list (List[int]): List of in-context example indices for every
+            test prompts.
         ice_separator (`Optional[str]`): The separator between each in-context
             example template when origin `PromptTemplate` is provided. Defaults
             to '\n'.
@@ -31,22 +33,19 @@ class FixKRetriever(BaseRetriever):
 
     def __init__(self,
                  dataset,
+                 fix_id_list: List[int],
                  ice_separator: Optional[str] = '\n',
                  ice_eos_token: Optional[str] = '\n',
                  ice_num: Optional[int] = 1) -> None:
         super().__init__(dataset, ice_separator, ice_eos_token, ice_num)
+        self.fix_id_list = fix_id_list
 
-    def retrieve(self, id_list: List[int]):
-        """Retrieve the in-context example index for each test example.
-
-        Args:
-            id_list (List[int]): List of in-context example indices for every
-                test prompts.
-        """
+    def retrieve(self):
+        """Retrieve the in-context example index for each test example."""
         num_idx = len(self.index_ds)
-        for idx in id_list:
+        for idx in self.fix_id_list:
             assert idx < num_idx, f'Index {idx} is out of range of {num_idx}'
         rtr_idx_list = []
         for _ in trange(len(self.test_ds), disable=not self.is_main_process):
-            rtr_idx_list.append(id_list)
+            rtr_idx_list.append(self.fix_id_list)
         return rtr_idx_list

opencompass/utils/prompt.py

@@ -56,6 +56,10 @@ def get_prompt_hash(dataset_cfg: Union[ConfigDict, List[ConfigDict]]) -> str:
                 'test_split'] = dataset_cfg.infer_cfg.reader_cfg.test_split
         for k, v in dataset_cfg.infer_cfg.items():
             dataset_cfg.infer_cfg[k]['type'] = v['type'].split('.')[-1]
+    # A compromise for the hash consistency
+    if 'fix_id_list' in dataset_cfg.infer_cfg.retriever:
+        fix_id_list = dataset_cfg.infer_cfg.retriever.pop('fix_id_list')
+        dataset_cfg.infer_cfg.inferencer['fix_id_list'] = fix_id_list
     d_json = json.dumps(dataset_cfg.infer_cfg.to_dict(), sort_keys=True)
     hash_object = hashlib.sha256(d_json.encode())
     return hash_object.hexdigest()

tools/prompt_viewer.py

@@ -61,7 +61,6 @@ def print_prompts(model_cfg, dataset_cfg, count=1):
 
     infer_cfg = dataset_cfg.get('infer_cfg')
 
-    fix_id_list = infer_cfg.inferencer.get('fix_id_list', [])
     dataset = build_dataset_from_cfg(dataset_cfg)
 
     ice_template = None
@@ -76,10 +75,7 @@ def print_prompts(model_cfg, dataset_cfg, count=1):
     infer_cfg['retriever']['dataset'] = dataset
     retriever = ICL_RETRIEVERS.build(infer_cfg['retriever'])
 
-    if fix_id_list:
-        ice_idx_list = retriever.retrieve(fix_id_list)
-    else:
-        ice_idx_list = retriever.retrieve()
+    ice_idx_list = retriever.retrieve()
 
     assert infer_cfg.inferencer.type in [PPLInferencer, GenInferencer], \
         'Only PPLInferencer and GenInferencer are supported'

tools/update_dataset_suffix.py

@@ -45,6 +45,10 @@ def get_prompt_hash(dataset_cfg: Union[ConfigDict, List[ConfigDict]]) -> str:
                 'test_split'] = dataset_cfg.infer_cfg.reader_cfg.test_split
         for k, v in dataset_cfg.infer_cfg.items():
             dataset_cfg.infer_cfg[k]['type'] = v['type'].split('.')[-1]
+    # A compromise for the hash consistency
+    if 'fix_id_list' in dataset_cfg.infer_cfg.retriever:
+        fix_id_list = dataset_cfg.infer_cfg.retriever.pop('fix_id_list')
+        dataset_cfg.infer_cfg.inferencer['fix_id_list'] = fix_id_list
     d_json = json.dumps(dataset_cfg.infer_cfg.to_dict(), sort_keys=True)
     hash_object = hashlib.sha256(d_json.encode())
     return hash_object.hexdigest()