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>
This commit is contained in:
Yang Yong 2023-12-27 13:49:08 +08:00 committed by GitHub
parent 34561ececb
commit 54345c56b7
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7 changed files with 202 additions and 14 deletions

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@ -1,7 +1,7 @@
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

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@ -1,7 +1,7 @@
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

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@ -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

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@ -1,4 +1,4 @@
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

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@ -0,0 +1,124 @@
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

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@ -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),
),
)

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@ -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.')