mirror of
https://github.com/open-compass/opencompass.git
synced 2025-05-30 16:03:24 +08:00
8142f399a8
* add needlebench * simplify needlebench 32k, 128k, 200k for eval * update act prompt * fix bug in needlebench summarizer * add needlebench intro, fix summarizer * lint summarizer * fix linting error * move readme.md * update readme for needlebench * update docs of needlebench * simplify needlebench summarizers
110 lines
3.8 KiB
Python
110 lines
3.8 KiB
Python
from opencompass.openicl.icl_prompt_template import PromptTemplate
|
|
from opencompass.openicl.icl_retriever import ZeroRetriever
|
|
from opencompass.openicl.icl_inferencer import GenInferencer
|
|
from opencompass.datasets.needlebench.parallel import NeedleBenchParallelDataset
|
|
from opencompass.datasets.needlebench.parallel import NeedleBenchParallelEvaluator
|
|
from opencompass.datasets.needlebench.origin import needlebench_postprocess
|
|
from opencompass.datasets.needlebench.origin import needlebench_dataset_postprocess
|
|
import math
|
|
|
|
|
|
def logistic(x, L=100, x0=50, k=0.1):
|
|
return round(L / (1 + math.exp(-k * (x - x0))), 3)
|
|
|
|
|
|
def generate_linear_space(start, end, num):
|
|
if num == 1:
|
|
return [start]
|
|
elif num < 1:
|
|
raise ValueError("num must be at least 1.")
|
|
step = (end - start) / (num - 1)
|
|
return [start + step * i for i in range(num)]
|
|
|
|
|
|
def generate_depth_percents(intervals, interval_type):
|
|
if interval_type == 'linear':
|
|
return generate_linear_space(0, 100, intervals)
|
|
elif interval_type == 'sigmoid':
|
|
linear_space = generate_linear_space(0, 100, intervals)
|
|
return [logistic(x) for x in linear_space]
|
|
else:
|
|
raise ValueError('Unsupported interval type')
|
|
|
|
|
|
needlebench_reader_cfg = dict(input_columns=['prompt'], output_column='answer')
|
|
|
|
needlebench_infer_cfg = dict(
|
|
prompt_template=dict(
|
|
type=PromptTemplate,
|
|
template=dict(
|
|
round=[
|
|
dict(role='HUMAN', prompt='{prompt}'),
|
|
dict(role='BOT', prompt='{answer}\n'),
|
|
]
|
|
)
|
|
),
|
|
retriever=dict(type=ZeroRetriever),
|
|
inferencer=dict(type=GenInferencer))
|
|
|
|
needlebench_eval_cfg = dict(
|
|
evaluator=dict(type=NeedleBenchParallelEvaluator),
|
|
pred_postprocessor=dict(type=needlebench_postprocess),
|
|
dataset_postprocessor=dict(type=needlebench_dataset_postprocess),
|
|
pred_role='BOT')
|
|
|
|
# context_lengths = list([16000, 32000, 48000, 64000, 80000, 96000, 112000, 128000, 144000, 160000, 176000, 192000, 200000])
|
|
context_lengths = list([16000, 48000, 80000, 112000, 128000, 144000, 176000, 200000])
|
|
document_depth_percent_intervals = 20
|
|
document_depth_percent_interval_type = "linear"
|
|
|
|
base_path = './data/needlebench'
|
|
file_list = ['PaulGrahamEssays.jsonl']
|
|
needlebench_datasets_en = []
|
|
needle_file_name = 'needles.jsonl'
|
|
depths = [0, 10, 21, 31, 42, 52, 63, 73, 84, 94, 100]
|
|
|
|
for original_context_length in context_lengths:
|
|
dataset_dict = {
|
|
'abbr': f'Length{original_context_length}'
|
|
f'_parallel_en_200k',
|
|
'type': NeedleBenchParallelDataset,
|
|
'path': base_path,
|
|
'needle_file_name': needle_file_name,
|
|
'length': original_context_length,
|
|
'depths': depths,
|
|
'tokenizer_model': 'gpt-4',
|
|
'file_list': file_list,
|
|
'num_repeats_per_file': 25,
|
|
'length_buffer': 3000,
|
|
'guide': True,
|
|
'language': 'English',
|
|
'reader_cfg': needlebench_reader_cfg,
|
|
'infer_cfg': needlebench_infer_cfg,
|
|
'eval_cfg': needlebench_eval_cfg
|
|
}
|
|
needlebench_datasets_en.append(dataset_dict)
|
|
|
|
file_list = ['zh_finance.jsonl']
|
|
needlebench_datasets_zh = []
|
|
|
|
for original_context_length in context_lengths:
|
|
dataset_dict = {
|
|
'abbr': f'Length{original_context_length}'
|
|
f'_parallel_zh_200k',
|
|
'type': NeedleBenchParallelDataset,
|
|
'path': base_path,
|
|
'needle_file_name': needle_file_name,
|
|
'length': original_context_length,
|
|
'depths': depths,
|
|
'tokenizer_model': 'gpt-4',
|
|
'file_list': file_list,
|
|
'num_repeats_per_file': 25,
|
|
'length_buffer': 200,
|
|
'guide': True,
|
|
'language': 'Chinese',
|
|
'reader_cfg': needlebench_reader_cfg,
|
|
'infer_cfg': needlebench_infer_cfg,
|
|
'eval_cfg': needlebench_eval_cfg
|
|
}
|
|
needlebench_datasets_zh.append(dataset_dict)
|