Update LightllmApi and Fix mmlu bug (#738)

* Update LightllmApi and Fix mmlu bug

* checkout mmlu_gen_a484b3.py

---------
Co-authored-by: Leymore <zfz-960727@163.com>

configs/datasets/collections/chat_medium.py

 from mmengine.config import read_base
 
 with read_base():
-    from ..mmlu.mmlu_gen_a484b3 import mmlu_datasets
+    from ..mmlu.mmlu_gen_4d595a import mmlu_datasets
     from ..ceval.ceval_gen_5f30c7 import ceval_datasets
     from ..agieval.agieval_gen_64afd3 import agieval_datasets
     from ..GaokaoBench.GaokaoBench_gen_5cfe9e import GaokaoBench_datasets

configs/datasets/collections/chat_small.py

 from mmengine.config import read_base
 
 with read_base():
-    from ..mmlu.mmlu_gen_a484b3 import mmlu_datasets
+    from ..mmlu.mmlu_gen_4d595a import mmlu_datasets
     from ..ceval.ceval_gen_5f30c7 import ceval_datasets
     from ..bbh.bbh_gen_5b92b0 import bbh_datasets
     from ..CLUE_CMRC.CLUE_CMRC_gen_1bd3c8 import CMRC_datasets

configs/datasets/collections/leaderboard/qwen_chat.py

@@ -3,7 +3,7 @@ from mmengine.config import read_base
 with read_base():
     from ...ceval.ceval_gen_5f30c7 import ceval_datasets
     from ...agieval.agieval_mixed_2f14ad import agieval_datasets
-    from ...mmlu.mmlu_gen_a484b3 import mmlu_datasets
+    from ...mmlu.mmlu_gen_4d595a import mmlu_datasets
     from ...cmmlu.cmmlu_gen_c13365 import cmmlu_datasets
     from ...GaokaoBench.GaokaoBench_gen_5cfe9e import GaokaoBench_datasets
     from ...ARC_c.ARC_c_ppl_2ef631 import ARC_c_datasets

configs/datasets/mmlu/mmlu_gen.py

 from mmengine.config import read_base
 
 with read_base():
-    from .mmlu_gen_a484b3 import mmlu_datasets  # noqa: F401, F403
+    from .mmlu_gen_4d595a import mmlu_datasets  # noqa: F401, F403

configs/datasets/mmlu/mmlu_gen_4d595a.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import FixKRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import MMLUDataset
+from opencompass.utils.text_postprocessors import first_capital_postprocess
+
+# None of the mmlu dataset in huggingface is correctly parsed, so we use our own dataset reader
+# Please download the dataset from https://people.eecs.berkeley.edu/~hendrycks/data.tar
+
+mmlu_reader_cfg = dict(
+    input_columns=["input", "A", "B", "C", "D"],
+    output_column="target",
+    train_split='dev')
+
+mmlu_all_sets = [
+    "college_biology",
+    "college_chemistry",
+    "college_computer_science",
+    "college_mathematics",
+    "college_physics",
+    "electrical_engineering",
+    "astronomy",
+    "anatomy",
+    "abstract_algebra",
+    "machine_learning",
+    "clinical_knowledge",
+    "global_facts",
+    "management",
+    "nutrition",
+    "marketing",
+    "professional_accounting",
+    "high_school_geography",
+    "international_law",
+    "moral_scenarios",
+    "computer_security",
+    "high_school_microeconomics",
+    "professional_law",
+    "medical_genetics",
+    "professional_psychology",
+    "jurisprudence",
+    "world_religions",
+    "philosophy",
+    "virology",
+    "high_school_chemistry",
+    "public_relations",
+    "high_school_macroeconomics",
+    "human_sexuality",
+    "elementary_mathematics",
+    "high_school_physics",
+    "high_school_computer_science",
+    "high_school_european_history",
+    "business_ethics",
+    "moral_disputes",
+    "high_school_statistics",
+    "miscellaneous",
+    "formal_logic",
+    "high_school_government_and_politics",
+    "prehistory",
+    "security_studies",
+    "high_school_biology",
+    "logical_fallacies",
+    "high_school_world_history",
+    "professional_medicine",
+    "high_school_mathematics",
+    "college_medicine",
+    "high_school_us_history",
+    "sociology",
+    "econometrics",
+    "high_school_psychology",
+    "human_aging",
+    "us_foreign_policy",
+    "conceptual_physics",
+]
+
+mmlu_datasets = []
+for _name in mmlu_all_sets:
+    _hint = f'There is a single choice question about {_name.replace("_", " ")}. Answer the question by replying A, B, C or D.'
+    mmlu_infer_cfg = dict(
+        ice_template=dict(
+            type=PromptTemplate,
+            template=dict(round=[
+                dict(
+                    role="HUMAN",
+                    prompt=
+                    f"{_hint}\nQuestion: {{input}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\nAnswer: "
+                ),
+                dict(role="BOT", prompt="{target}\n")
+            ]),
+        ),
+        prompt_template=dict(
+            type=PromptTemplate,
+            template=dict(
+                begin="</E>",
+                round=[
+                    dict(
+                        role="HUMAN",
+                        prompt=
+                        f"{_hint}\nQuestion: {{input}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\nAnswer: "
+                    ),
+                ],
+            ),
+            ice_token="</E>",
+        ),
+        retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]),
+        inferencer=dict(type=GenInferencer),
+    )
+
+    mmlu_eval_cfg = dict(
+        evaluator=dict(type=AccEvaluator),
+        pred_postprocessor=dict(type=first_capital_postprocess))
+
+    mmlu_datasets.append(
+        dict(
+            abbr=f"lukaemon_mmlu_{_name}",
+            type=MMLUDataset,
+            path="./data/mmlu/",
+            name=_name,
+            reader_cfg=mmlu_reader_cfg,
+            infer_cfg=mmlu_infer_cfg,
+            eval_cfg=mmlu_eval_cfg,
+        ))
+
+del _name, _hint

configs/eval_lightllm.py

@@ -14,11 +14,12 @@ models = [
         abbr='LightllmAPI',
         type=LightllmAPI,
         url='http://localhost:8080/generate',
-        max_out_len=1024,
-        batch_size=8,
+        max_seq_len=2048,
+        batch_size=32,
         generation_kwargs=dict(
             do_sample=False,
             ignore_eos=False,
+            max_new_tokens=1024
         ),
     ),
 ]
@@ -27,7 +28,7 @@ infer = dict(
     partitioner=dict(type=NaivePartitioner),
     runner=dict(
         type=LocalRunner,
-        max_num_workers=8,
+        max_num_workers=32,
         task=dict(type=OpenICLInferTask),
     ),
 )

opencompass/models/lightllm_api.py

@@ -2,6 +2,7 @@ import json
 from concurrent.futures import ThreadPoolExecutor
 from typing import Dict, List, Optional
 
+import numpy as np
 import requests
 
 from opencompass.registry import MODELS
@@ -32,8 +33,8 @@ class LightllmAPI(BaseAPIModel):
                          generation_kwargs=generation_kwargs)
         self.logger = get_logger()
         self.url = url
-        self.do_sample = self.generation_kwargs.get('do_sample', False)
-        self.ignore_eos = self.generation_kwargs.get('ignore_eos', False)
+        self.generation_kwargs = generation_kwargs
+        self.max_out_len = self.generation_kwargs.get('max_new_tokens', 1024)
 
     def generate(self, inputs: List[str], max_out_len: int,
                  **kwargs) -> List[str]:
@@ -52,7 +53,7 @@ class LightllmAPI(BaseAPIModel):
         with ThreadPoolExecutor() as executor:
             results = list(
                 executor.map(self._generate, inputs,
-                             [max_out_len] * len(inputs)))
+                             [self.max_out_len] * len(inputs)))
         return results
 
     def _generate(self, input: str, max_out_len: int) -> str:
@@ -61,10 +62,7 @@ class LightllmAPI(BaseAPIModel):
             self.wait()
             header = {'content-type': 'application/json'}
             try:
-                data = dict(inputs=input,
-                            parameters=dict(do_sample=self.do_sample,
-                                            ignore_eos=self.ignore_eos,
-                                            max_new_tokens=max_out_len))
+                data = dict(inputs=input, parameters=self.generation_kwargs)
                 raw_response = requests.post(self.url,
                                              headers=header,
                                              data=json.dumps(data))
@@ -85,3 +83,68 @@ class LightllmAPI(BaseAPIModel):
         raise RuntimeError('Calling LightllmAPI failed after retrying for '
                            f'{max_num_retries} times. Check the logs for '
                            'details.')
+
+    def get_ppl(self, inputs: List[str], max_out_len: int,
+                **kwargs) -> List[float]:
+        """Generate results given a list of inputs.
+
+        Args:
+            inputs (List[str]): A list of strings or PromptDicts.
+                The PromptDict should be organized in OpenCompass'
+                API format.
+            max_out_len (int): The maximum length of the output.
+
+        Returns:
+            List[str]: A list of generated strings.
+        """
+
+        with ThreadPoolExecutor() as executor:
+            results = list(
+                executor.map(self._get_ppl, inputs,
+                             [self.max_out_len] * len(inputs)))
+        return np.array(results)
+
+    def _get_ppl(self, input: str, max_out_len: int) -> float:
+        max_num_retries = 0
+        if max_out_len is None:
+            max_out_len = 1
+        while max_num_retries < self.retry:
+            self.wait()
+            header = {'content-type': 'application/json'}
+            try:
+                data = dict(inputs=input, parameters=self.generation_kwargs)
+                raw_response = requests.post(self.url,
+                                             headers=header,
+                                             data=json.dumps(data))
+            except requests.ConnectionError:
+                self.logger.error('Got connection error, retrying...')
+                continue
+            try:
+                response = raw_response.json()
+
+                assert ('prompt_token_ids' in response and 'prompt_logprobs'
+                        in response), 'prompt_token_ids and prompt_logprobs \
+                    must be in the output. \
+                    Please consider adding \
+                    --return_all_prompt_logprobs argument \
+                    when starting your lightllm service.'
+
+                prompt_token_ids = response['prompt_token_ids'][1:]
+                prompt_logprobs = [
+                    item[1] for item in response['prompt_logprobs']
+                ]
+                logprobs = [
+                    item[str(token_id)] for token_id, item in zip(
+                        prompt_token_ids, prompt_logprobs)
+                ]
+                if len(logprobs) == 0:
+                    return 0.0
+                ce_loss = -sum(logprobs) / len(logprobs)
+                return ce_loss
+            except requests.JSONDecodeError:
+                self.logger.error('JsonDecode error, got',
+                                  str(raw_response.content))
+            max_num_retries += 1
+        raise RuntimeError('Calling LightllmAPI failed after retrying for '
+                           f'{max_num_retries} times. Check the logs for '
+                           'details.')