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Unverified Commit b39f5015 authored by Fengzhe Zhou's avatar Fengzhe Zhou Committed by GitHub
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[Sync] update taco (#1030)

parent 16f29b25
Show whitespace changes
Inline Side-by-side
Showing with 107 additions and 437 deletions
opencompass/utils/prompt.py
View file @ b39f5015
...@@ -73,7 +73,7 @@ class PromptList(list): ...@@ -73,7 +73,7 @@ class PromptList(list):
Args: Args:
src (str): The string to be replaced. src (str): The string to be replaced.
dst (str or PromptList): The string or PromptList to replace with. dst (PromptType): The string or PromptList to replace with.
Returns: Returns:
PromptList: A new PromptList with 'src' replaced by 'dst'. PromptList: A new PromptList with 'src' replaced by 'dst'.
...@@ -98,7 +98,7 @@ class PromptList(list): ...@@ -98,7 +98,7 @@ class PromptList(list):
Args: Args:
src (str): The string to be replaced. src (str): The string to be replaced.
dst (str or PromptList): The string or PromptList to replace with. dst (PromptType): The string or PromptList to replace with.
Returns: Returns:
PromptList: A new PromptList with 'src' replaced by 'dst'. PromptList: A new PromptList with 'src' replaced by 'dst'.
...@@ -139,7 +139,7 @@ class PromptList(list): ...@@ -139,7 +139,7 @@ class PromptList(list):
"""Adds a string or another PromptList to this PromptList. """Adds a string or another PromptList to this PromptList.
Args: Args:
other (str or PromptList): The string or PromptList to be added. other (PromptType): The string or PromptList to be added.
Returns: Returns:
PromptList: A new PromptList that is the result of the addition. PromptList: A new PromptList that is the result of the addition.
...@@ -156,7 +156,7 @@ class PromptList(list): ...@@ -156,7 +156,7 @@ class PromptList(list):
'+' operator. '+' operator.
Args: Args:
other (str or PromptList): The string or PromptList to be added. other (PromptType): The string or PromptList to be added.
Returns: Returns:
PromptList: A new PromptList that is the result of the addition. PromptList: A new PromptList that is the result of the addition.
...@@ -172,7 +172,7 @@ class PromptList(list): ...@@ -172,7 +172,7 @@ class PromptList(list):
"""Implements in-place addition for the PromptList. """Implements in-place addition for the PromptList.
Args: Args:
other (str or PromptList): The string or PromptList to be added. other (PromptType): The string or PromptList to be added.
Returns: Returns:
PromptList: The updated PromptList. PromptList: The updated PromptList.
......
opencompass/utils/run.py
View file @ b39f5015
...@@ -48,6 +48,19 @@ def match_cfg_file(workdir: str, pattern: Union[str, List[str]]) -> List[str]: ...@@ -48,6 +48,19 @@ def match_cfg_file(workdir: str, pattern: Union[str, List[str]]) -> List[str]:
return files return files
def try_fill_in_custom_cfgs(config):
for i, dataset in enumerate(config['datasets']):
if 'type' not in dataset:
config['datasets'][i] = make_custom_dataset_config(dataset)
if 'model_dataset_combinations' not in config:
return config
for mdc in config['model_dataset_combinations']:
for i, dataset in enumerate(mdc['datasets']):
if 'type' not in dataset:
mdc['datasets'][i] = make_custom_dataset_config(dataset)
return config
def get_config_from_arg(args) -> Config: def get_config_from_arg(args) -> Config:
"""Get the config object given args. """Get the config object given args.
...@@ -58,9 +71,7 @@ def get_config_from_arg(args) -> Config: ...@@ -58,9 +71,7 @@ def get_config_from_arg(args) -> Config:
""" """
if args.config: if args.config:
config = Config.fromfile(args.config, format_python_code=False) config = Config.fromfile(args.config, format_python_code=False)
for i, dataset in enumerate(config['datasets']): config = try_fill_in_custom_cfgs(config)
if 'type' not in dataset:
config['datasets'][i] = make_custom_dataset_config(dataset)
return config return config
# parse dataset args # parse dataset args
if not args.datasets and not args.custom_dataset_path: if not args.datasets and not args.custom_dataset_path:
......
opencompass/utils/text_postprocessors.py
View file @ b39f5015
...@@ -94,11 +94,11 @@ def first_option_postprocess(text: str, options: str, cushion=True) -> str: ...@@ -94,11 +94,11 @@ def first_option_postprocess(text: str, options: str, cushion=True) -> str:
f'答案是\s?(\S+)(?:。|$)', f'答案是\s?(\S+)(?:。|$)',
f'答案应该是\s?(\S+)(?:。|$)', f'答案应该是\s?(\S+)(?:。|$)',
f'答案为\s?(\S+)(?:。|$)', f'答案为\s?(\S+)(?:。|$)',
f'[Tt]he answer is ([{options}])', f'[Tt]he answer is \(?([{options}])\)?',
f'[Tt]he answer is option ([{options}])', f'[Tt]he answer is option \(?([{options}])\)?',
f'[Tt]he correct answer is ([{options}])', f'[Tt]he correct answer is \(?([{options}])\)?',
f'[Tt]he correct answer is option ([{options}])', f'[Tt]he correct answer is option \(?([{options}])\)?',
f'[Tt]he answer to the question is ([{options}])', f'[Tt]he answer to the question is \(?([{options}])\)?',
f'^选项\s?([{options}])', f'^选项\s?([{options}])',
f'^([{options}])\s?选?项', f'^([{options}])\s?选?项',
f'(\s|^)[{options}][\s。，,：:\.$]', f'(\s|^)[{options}][\s。，,：:\.$]',
......
requirements/runtime.txt
View file @ b39f5015
...@@ -21,6 +21,7 @@ OpenCC ...@@ -21,6 +21,7 @@ OpenCC
opencv-python-headless opencv-python-headless
pandas<2.0.0 pandas<2.0.0
prettytable prettytable
pyext
pypinyin pypinyin
python-Levenshtein python-Levenshtein
rank_bm25==0.2.2 rank_bm25==0.2.2
......
run.py
View file @ b39f5015
import argparse from opencompass.cli.main import main
import getpass
import os
import os.path as osp
from datetime import datetime
from mmengine.config import Config, DictAction
from opencompass.partitioners import MultimodalNaivePartitioner
from opencompass.registry import PARTITIONERS, RUNNERS, build_from_cfg
from opencompass.runners import SlurmRunner
from opencompass.summarizers import DefaultSummarizer
from opencompass.utils import LarkReporter, get_logger
from opencompass.utils.run import (exec_mm_infer_runner, fill_eval_cfg,
fill_infer_cfg, get_config_from_arg)
def parse_args():
parser = argparse.ArgumentParser(description='Run an evaluation task')
parser.add_argument('config', nargs='?', help='Train config file path')
# add mutually exclusive args `--slurm` `--dlc`, defaults to local runner
# if "infer" or "eval" not specified
launch_method = parser.add_mutually_exclusive_group()
launch_method.add_argument('--slurm',
action='store_true',
default=False,
help='Whether to force tasks to run with srun. '
'If True, `--partition(-p)` must be set. '
'Defaults to False')
launch_method.add_argument('--dlc',
action='store_true',
default=False,
help='Whether to force tasks to run on dlc. If '
'True, `--aliyun-cfg` must be set. Defaults'
' to False')
# multi-modal support
parser.add_argument('--mm-eval',
help='Whether or not enable multimodal evaluation',
action='store_true',
default=False)
# Add shortcut parameters (models, datasets and summarizer)
parser.add_argument('--models', nargs='+', help='', default=None)
parser.add_argument('--datasets', nargs='+', help='', default=None)
parser.add_argument('--summarizer', help='', default=None)
# add general args
parser.add_argument('--debug',
help='Debug mode, in which scheduler will run tasks '
'in the single process, and output will not be '
'redirected to files',
action='store_true',
default=False)
parser.add_argument('--dry-run',
help='Dry run mode, in which the scheduler will not '
'actually run the tasks, but only print the commands '
'to run',
action='store_true',
default=False)
parser.add_argument('-m',
'--mode',
help='Running mode. You can choose "infer" if you '
'only want the inference results, or "eval" if you '
'already have the results and want to evaluate them, '
'or "viz" if you want to visualize the results.',
choices=['all', 'infer', 'eval', 'viz'],
default='all',
type=str)
parser.add_argument('-r',
'--reuse',
nargs='?',
type=str,
const='latest',
help='Reuse previous outputs & results, and run any '
'missing jobs presented in the config. If its '
'argument is not specified, the latest results in '
'the work_dir will be reused. The argument should '
'also be a specific timestamp, e.g. 20230516_144254'),
parser.add_argument('-w',
'--work-dir',
help='Work path, all the outputs will be '
'saved in this path, including the slurm logs, '
'the evaluation results, the summary results, etc.'
'If not specified, the work_dir will be set to '
'./outputs/default.',
default=None,
type=str)
parser.add_argument(
'--config-dir',
default='configs',
help='Use the custom config directory instead of config/ to '
'search the configs for datasets, models and summarizers',
type=str)
parser.add_argument('-l',
'--lark',
help='Report the running status to lark bot',
action='store_true',
default=False)
parser.add_argument('--max-partition-size',
help='The maximum size of an infer task. Only '
'effective when "infer" is missing from the config.',
type=int,
default=40000),
parser.add_argument(
'--gen-task-coef',
help='The dataset cost measurement coefficient for generation tasks, '
'Only effective when "infer" is missing from the config.',
type=int,
default=20)
parser.add_argument('--max-num-workers',
help='Max number of workers to run in parallel. '
'Will be overrideen by the "max_num_workers" argument '
'in the config.',
type=int,
default=32)
parser.add_argument('--max-workers-per-gpu',
help='Max task to run in parallel on one GPU. '
'It will only be used in the local runner.',
type=int,
default=1)
parser.add_argument(
'--retry',
help='Number of retries if the job failed when using slurm or dlc. '
'Will be overrideen by the "retry" argument in the config.',
type=int,
default=2)
parser.add_argument(
'--dump-eval-details',
help='Whether to dump the evaluation details, including the '
'correctness of each sample, bpb, etc.',
action='store_true',
)
# set srun args
slurm_parser = parser.add_argument_group('slurm_args')
parse_slurm_args(slurm_parser)
# set dlc args
dlc_parser = parser.add_argument_group('dlc_args')
parse_dlc_args(dlc_parser)
# set hf args
hf_parser = parser.add_argument_group('hf_args')
parse_hf_args(hf_parser)
# set custom dataset args
custom_dataset_parser = parser.add_argument_group('custom_dataset_args')
parse_custom_dataset_args(custom_dataset_parser)
args = parser.parse_args()
if args.slurm:
assert args.partition is not None, (
'--partition(-p) must be set if you want to use slurm')
if args.dlc:
assert os.path.exists(args.aliyun_cfg), (
'When launching tasks using dlc, it needs to be configured '
'in "~/.aliyun.cfg", or use "--aliyun-cfg $ALiYun-CFG_Path"'
' to specify a new path.')
return args
def parse_slurm_args(slurm_parser):
"""These args are all for slurm launch."""
slurm_parser.add_argument('-p',
'--partition',
help='Slurm partition name',
default=None,
type=str)
slurm_parser.add_argument('-q',
'--quotatype',
help='Slurm quota type',
default=None,
type=str)
slurm_parser.add_argument('--qos',
help='Slurm quality of service',
default=None,
type=str)
def parse_dlc_args(dlc_parser):
"""These args are all for dlc launch."""
dlc_parser.add_argument('--aliyun-cfg',
help='The config path for aliyun config',
default='~/.aliyun.cfg',
type=str)
def parse_hf_args(hf_parser):
"""These args are all for the quick construction of HuggingFace models."""
hf_parser.add_argument('--hf-path', type=str)
hf_parser.add_argument('--peft-path', type=str)
hf_parser.add_argument('--tokenizer-path', type=str)
hf_parser.add_argument('--model-kwargs',
nargs='+',
action=DictAction,
default={})
hf_parser.add_argument('--tokenizer-kwargs',
nargs='+',
action=DictAction,
default={})
hf_parser.add_argument('--max-out-len', type=int)
hf_parser.add_argument('--max-seq-len', type=int)
hf_parser.add_argument('--no-batch-padding',
action='store_true',
default=False)
hf_parser.add_argument('--batch-size', type=int)
hf_parser.add_argument('--num-gpus', type=int)
hf_parser.add_argument('--pad-token-id', type=int)
def parse_custom_dataset_args(custom_dataset_parser):
"""These args are all for the quick construction of custom datasets."""
custom_dataset_parser.add_argument('--custom-dataset-path', type=str)
custom_dataset_parser.add_argument('--custom-dataset-meta-path', type=str)
custom_dataset_parser.add_argument('--custom-dataset-data-type',
type=str,
choices=['mcq', 'qa'])
custom_dataset_parser.add_argument('--custom-dataset-infer-method',
type=str,
choices=['gen', 'ppl'])
def main():
args = parse_args()
if args.dry_run:
args.debug = True
# initialize logger
logger = get_logger(log_level='DEBUG' if args.debug else 'INFO')
cfg = get_config_from_arg(args)
if args.work_dir is not None:
cfg['work_dir'] = args.work_dir
else:
cfg.setdefault('work_dir', './outputs/default/')
# cfg_time_str defaults to the current time
cfg_time_str = dir_time_str = datetime.now().strftime('%Y%m%d_%H%M%S')
if args.reuse:
if args.reuse == 'latest':
if not os.path.exists(cfg.work_dir) or not os.listdir(
cfg.work_dir):
logger.warning('No previous results to reuse!')
else:
dirs = os.listdir(cfg.work_dir)
dir_time_str = sorted(dirs)[-1]
else:
dir_time_str = args.reuse
logger.info(f'Reusing experiements from {dir_time_str}')
elif args.mode in ['eval', 'viz']:
raise ValueError('You must specify -r or --reuse when running in eval '
'or viz mode!')
# update "actual" work_dir
cfg['work_dir'] = osp.join(cfg.work_dir, dir_time_str)
os.makedirs(osp.join(cfg.work_dir, 'configs'), exist_ok=True)
# dump config
output_config_path = osp.join(cfg.work_dir, 'configs',
f'{cfg_time_str}.py')
cfg.dump(output_config_path)
# Config is intentally reloaded here to avoid initialized
# types cannot be serialized
cfg = Config.fromfile(output_config_path, format_python_code=False)
# report to lark bot if specify --lark
if not args.lark:
cfg['lark_bot_url'] = None
elif cfg.get('lark_bot_url', None):
content = f'{getpass.getuser()}\'s task has been launched!'
LarkReporter(cfg['lark_bot_url']).post(content)
if args.mode in ['all', 'infer']:
# When user have specified --slurm or --dlc, or have not set
# "infer" in config, we will provide a default configuration
# for infer
if (args.dlc or args.slurm) and cfg.get('infer', None):
logger.warning('You have set "infer" in the config, but '
'also specified --slurm or --dlc. '
'The "infer" configuration will be overridden by '
'your runtime arguments.')
# Check whether run multimodal evaluation
if args.mm_eval:
partitioner = MultimodalNaivePartitioner(
osp.join(cfg['work_dir'], 'predictions/'))
tasks = partitioner(cfg)
exec_mm_infer_runner(tasks, args, cfg)
return
if args.dlc or args.slurm or cfg.get('infer', None) is None:
fill_infer_cfg(cfg, args)
if args.partition is not None:
if RUNNERS.get(cfg.infer.runner.type) == SlurmRunner:
cfg.infer.runner.partition = args.partition
cfg.infer.runner.quotatype = args.quotatype
else:
logger.warning('SlurmRunner is not used, so the partition '
'argument is ignored.')
if args.debug:
cfg.infer.runner.debug = True
if args.lark:
cfg.infer.runner.lark_bot_url = cfg['lark_bot_url']
cfg.infer.partitioner['out_dir'] = osp.join(cfg['work_dir'],
'predictions/')
partitioner = PARTITIONERS.build(cfg.infer.partitioner)
tasks = partitioner(cfg)
if args.dry_run:
return
runner = RUNNERS.build(cfg.infer.runner)
# Add extra attack config if exists
if hasattr(cfg, 'attack'):
for task in tasks:
cfg.attack.dataset = task.datasets[0][0].abbr
task.attack = cfg.attack
runner(tasks)
# evaluate
if args.mode in ['all', 'eval']:
# When user have specified --slurm or --dlc, or have not set
# "eval" in config, we will provide a default configuration
# for eval
if (args.dlc or args.slurm) and cfg.get('eval', None):
logger.warning('You have set "eval" in the config, but '
'also specified --slurm or --dlc. '
'The "eval" configuration will be overridden by '
'your runtime arguments.')
if args.dlc or args.slurm or cfg.get('eval', None) is None:
fill_eval_cfg(cfg, args)
if args.dump_eval_details:
cfg.eval.runner.task.dump_details = True
if args.partition is not None:
if RUNNERS.get(cfg.eval.runner.type) == SlurmRunner:
cfg.eval.runner.partition = args.partition
cfg.eval.runner.quotatype = args.quotatype
else:
logger.warning('SlurmRunner is not used, so the partition '
'argument is ignored.')
if args.debug:
cfg.eval.runner.debug = True
if args.lark:
cfg.eval.runner.lark_bot_url = cfg['lark_bot_url']
cfg.eval.partitioner['out_dir'] = osp.join(cfg['work_dir'], 'results/')
partitioner = PARTITIONERS.build(cfg.eval.partitioner)
tasks = partitioner(cfg)
if args.dry_run:
return
runner = RUNNERS.build(cfg.eval.runner)
# For meta-review-judge in subjective evaluation
if isinstance(tasks, list) and len(tasks) != 0 and isinstance(
tasks[0], list):
for task_part in tasks:
runner(task_part)
else:
runner(tasks)
# visualize
if args.mode in ['all', 'eval', 'viz']:
summarizer_cfg = cfg.get('summarizer', {})
if not summarizer_cfg or summarizer_cfg.get('type', None) is None:
summarizer_cfg['type'] = DefaultSummarizer
summarizer_cfg['config'] = cfg
summarizer = build_from_cfg(summarizer_cfg)
summarizer.summarize(time_str=cfg_time_str)
if __name__ == '__main__': if __name__ == '__main__':
main() main()
setup.py
View file @ b39f5015
...@@ -103,7 +103,8 @@ def get_version(): ...@@ -103,7 +103,8 @@ def get_version():
def do_setup(): def do_setup():
setup(name='opencompass', setup(
name='opencompass',
author='OpenCompass Contributors', author='OpenCompass Contributors',
version=get_version(), version=get_version(),
description='A comprehensive toolkit for large model evaluation', description='A comprehensive toolkit for large model evaluation',
...@@ -114,7 +115,7 @@ def do_setup(): ...@@ -114,7 +115,7 @@ def do_setup():
cmdclass={'download_nltk': DownloadNLTK}, cmdclass={'download_nltk': DownloadNLTK},
setup_requires=['nltk==3.8'], setup_requires=['nltk==3.8'],
python_requires='>=3.8.0', python_requires='>=3.8.0',
install_requires=parse_requirements('requirements/runtime.txt'), # install_requires=parse_requirements('requirements/runtime.txt'),
license='Apache License 2.0', license='Apache License 2.0',
packages=find_packages(exclude=[ packages=find_packages(exclude=[
'test*', 'test*',
...@@ -135,7 +136,13 @@ def do_setup(): ...@@ -135,7 +136,13 @@ def do_setup():
'Intended Audience :: Developers', 'Intended Audience :: Developers',
'Intended Audience :: Education', 'Intended Audience :: Education',
'Intended Audience :: Science/Research', 'Intended Audience :: Science/Research',
]) ],
entry_points={
'console_scripts': [
'opencompass = opencompass.cli.main:main',
],
},
)
if __name__ == '__main__': if __name__ == '__main__':
......
tools/prediction_merger.py
View file @ b39f5015
import argparse import argparse
import copy import copy
import json import json
import os.path as osp import os
import mmengine import mmengine
from mmengine.config import Config, ConfigDict from mmengine.config import Config, ConfigDict
...@@ -13,24 +13,16 @@ def parse_args(): ...@@ -13,24 +13,16 @@ def parse_args():
parser = argparse.ArgumentParser( parser = argparse.ArgumentParser(
description='Merge patitioned predictions') description='Merge patitioned predictions')
parser.add_argument('config', help='Train config file path') parser.add_argument('config', help='Train config file path')
parser.add_argument('-w', parser.add_argument('-w', '--work-dir', default=None, type=str)
'--work-dir', parser.add_argument('-r', '--reuse', default='latest', type=str)
help='Work path, all the outputs will be ' parser.add_argument('-c', '--clean', action='store_true')
'saved in this path, including the slurm logs, '
'the evaluation results, the summary results, etc.'
'If not specified, the work_dir will be set to '
'./outputs/default.',
default=None,
type=str)
args = parser.parse_args() args = parser.parse_args()
return args return args
class PredictionMerger: class PredictionMerger:
""""""
def __init__(self, cfg: ConfigDict) -> None: def __init__(self, cfg: ConfigDict) -> None:
self.cfg = cfg self.cfg = cfg
self.model_cfg = copy.deepcopy(self.cfg['model']) self.model_cfg = copy.deepcopy(self.cfg['model'])
self.dataset_cfg = copy.deepcopy(self.cfg['dataset']) self.dataset_cfg = copy.deepcopy(self.cfg['dataset'])
...@@ -39,26 +31,23 @@ class PredictionMerger: ...@@ -39,26 +31,23 @@ class PredictionMerger:
def run(self): def run(self):
filename = get_infer_output_path( filename = get_infer_output_path(
self.model_cfg, self.dataset_cfg, self.model_cfg, self.dataset_cfg,
osp.join(self.work_dir, 'predictions')) os.path.join(self.work_dir, 'predictions'))
root, ext = osp.splitext(filename) root, ext = os.path.splitext(filename)
partial_filename = root + '_0' + ext partial_filename = root + '_0' + ext
if osp.exists(osp.realpath(filename)): if os.path.exists(os.path.realpath(filename)):
return return
if not osp.exists(osp.realpath(partial_filename)): if not os.path.exists(os.path.realpath(partial_filename)):
print(f'{filename} not found') print(f'{filename} not found')
return return
# Load predictions # Load predictions
partial_filenames = [] partial_filenames = []
if osp.exists(osp.realpath(filename)):
preds = mmengine.load(filename)
else:
preds, offset = {}, 0 preds, offset = {}, 0
i = 1 i = 1
while osp.exists(osp.realpath(partial_filename)): while os.path.exists(os.path.realpath(partial_filename)):
partial_filenames.append(osp.realpath(partial_filename)) partial_filenames.append(os.path.realpath(partial_filename))
_preds = mmengine.load(partial_filename) _preds = mmengine.load(partial_filename)
partial_filename = root + f'_{i}' + ext partial_filename = root + f'_{i}' + ext
i += 1 i += 1
...@@ -75,6 +64,11 @@ class PredictionMerger: ...@@ -75,6 +64,11 @@ class PredictionMerger:
with open(filename, 'w', encoding='utf-8') as f: with open(filename, 'w', encoding='utf-8') as f:
json.dump(preds, f, indent=4, ensure_ascii=False) json.dump(preds, f, indent=4, ensure_ascii=False)
if self.cfg['clean']:
for partial_filename in partial_filenames:
print(f'Remove {partial_filename}')
os.remove(partial_filename)
def dispatch_tasks(cfg): def dispatch_tasks(cfg):
for model in cfg['models']: for model in cfg['models']:
...@@ -82,7 +76,8 @@ def dispatch_tasks(cfg): ...@@ -82,7 +76,8 @@ def dispatch_tasks(cfg):
PredictionMerger({ PredictionMerger({
'model': model, 'model': model,
'dataset': dataset, 'dataset': dataset,
'work_dir': cfg['work_dir'] 'work_dir': cfg['work_dir'],
'clean': cfg['clean']
}).run() }).run()
...@@ -94,6 +89,22 @@ def main(): ...@@ -94,6 +89,22 @@ def main():
cfg['work_dir'] = args.work_dir cfg['work_dir'] = args.work_dir
else: else:
cfg.setdefault('work_dir', './outputs/default') cfg.setdefault('work_dir', './outputs/default')
if args.reuse:
if args.reuse == 'latest':
if not os.path.exists(cfg.work_dir) or not os.listdir(
cfg.work_dir):
print('No previous results to reuse!')
return
else:
dirs = os.listdir(cfg.work_dir)
dir_time_str = sorted(dirs)[-1]
else:
dir_time_str = args.reuse
cfg['work_dir'] = os.path.join(cfg.work_dir, dir_time_str)
cfg['clean'] = args.clean
dispatch_tasks(cfg) dispatch_tasks(cfg)
......
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