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This is a barely functional wrapper for running "test suites", which are just a list of preconfigured tasks. You can specify prompt and model. This needs more testing and UI cleanup.
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# This is the standard eight-task eval suite. | ||
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[tasks.mgsm] | ||
version = 1.0 | ||
fewshot = 5 | ||
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[tasks.xwinograd_ja] | ||
# this has no version | ||
fewshot = 0 | ||
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[tasks.xlsum_ja] | ||
version = 1.0 | ||
fewshot = 1 | ||
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[tasks.jaqket_v2] | ||
version = 0.1 | ||
fewshot = 1 | ||
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[tasks.marc_ja] | ||
version = 1.1 | ||
fewshot = 3 | ||
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[tasks.jnli] | ||
version = 1.1 | ||
fewshot = 3 | ||
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[tasks.jcommonsenseqa] | ||
version = 1.1 | ||
fewshot = 3 | ||
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[tasks.jsquad] | ||
version = 1.1 | ||
fewshot = 2 |
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#!/usr/bin/env python | ||
# Run a suite of tests | ||
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import argparse | ||
import configparser | ||
from dataclasses import dataclass | ||
from typing import Optional | ||
import os | ||
from pathlib import Path | ||
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from lm_eval import tasks, evaluator | ||
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# get path of current file | ||
FILE_PATH = Path(os.path.dirname(os.path.realpath(__file__))) | ||
# Path to suite configs | ||
SUITE_DIR = FILE_PATH / "../lm_eval/suites" | ||
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# names for prompts | ||
# TODO move this into lm_eval | ||
PROMPT_CODES = { | ||
"user": "0.0", | ||
"jgpt": "0.1", | ||
"fintan": "0.2", | ||
"fintan2": "0.2.1", | ||
"ja-alpaca": "0.3", | ||
"rinna-sft": "0.4", | ||
"rinna-bilingual": "0.5", | ||
"llama2": "0.6", | ||
} | ||
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@dataclass | ||
class TaskSpec: | ||
"""Specification of a task in an eval suite. | ||
A suite is a list of these specs, plus a prompt.""" | ||
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# The real arguments have to be massaged into messy strings and parallel | ||
# lists, but this is a more reasonable structure - we can handle conversion | ||
# separately. | ||
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name: str | ||
fewshot: int | ||
version: Optional[str] | ||
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def build_eval_args(specs: list[TaskSpec], prompt: str) -> tuple[list[str], list[int]]: | ||
"""Convert list of TaskSpecs into args for simple_evaluate.""" | ||
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tasks = [] | ||
fewshot = [] | ||
prompt_code = PROMPT_CODES[prompt] | ||
for spec in specs: | ||
task_name = spec.name | ||
if spec.version is not None: | ||
task_name += "-" + spec.version + "-" + prompt_code | ||
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tasks.append(task_name) | ||
fewshot.append(spec.fewshot) | ||
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return (tasks, fewshot) | ||
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def load_suite(name): | ||
"""Read in configuration for a test suite. | ||
A suite will have a config file named something like `my_suite.conf`. For | ||
each task in the file, a version, fewshot config, and any other details | ||
will be specified. | ||
Example entry: | ||
[tasks.mgsm] | ||
version = 1.0 | ||
fewshot = 5 | ||
""" | ||
conf = configparser.ConfigParser() | ||
conf.read(SUITE_DIR / (name + ".conf")) | ||
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specs = [] | ||
for key, val in conf.items(): | ||
if not key.startswith("tasks."): | ||
continue | ||
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spec = TaskSpec( | ||
name=key.split(".", 1)[1], | ||
version=val.get("version", None), | ||
fewshot=int(val["fewshot"]), | ||
) | ||
specs.append(spec) | ||
return specs | ||
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def run_suite( | ||
model_args, suite, prompt, *, model_type="hf-causal", output=None, verbose=False | ||
): | ||
# Confusing detail: in the "simple evaluate", "model" is the HF model type, | ||
# which is almost always hf-causal or hf-causal-experimental. `model_args` | ||
# looks like this: | ||
# | ||
# pretrained=hoge/piyo,tokenizer=...,asdf=... | ||
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# device never changes in practice | ||
device = "cuda" | ||
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print("suite", suite) | ||
specs = load_suite(suite) | ||
print(specs) | ||
tasks, num_fewshot = build_eval_args(specs, prompt) | ||
print(tasks) | ||
print(num_fewshot) | ||
print(model_args) | ||
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evaluator.simple_evaluate( | ||
model=model_type, | ||
model_args=model_args, | ||
tasks=tasks, | ||
num_fewshot=num_fewshot, | ||
device=device, | ||
verbose=verbose, | ||
) | ||
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def main(): | ||
parser = argparse.ArgumentParser( | ||
prog="run_suite.py", description="Run a test suite with a model" | ||
) | ||
parser.add_argument("model", help="Model path (or HF spec)") | ||
parser.add_argument("suite", help="Test suite to run") | ||
parser.add_argument("prompt", help="Prompt to use") | ||
parser.add_argument("-m", "--model_args", help="Additional model arguments") | ||
parser.add_argument( | ||
"-t", "--model_type", default="hf-causal-experimental", help="Model type" | ||
) | ||
parser.add_argument("-o", "--output", help="Output file") | ||
parser.add_argument("-v", "--verbose", action="store_true") | ||
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args = parser.parse_args() | ||
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margs = f"pretrained={args.model}" | ||
if args.model_args: | ||
margs = args.model + "," + args.model_args | ||
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run_suite( | ||
margs, | ||
args.suite, | ||
args.prompt, | ||
model_type=args.model_type, | ||
output=args.output, | ||
verbose=args.verbose, | ||
) | ||
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if __name__ == "__main__": | ||
main() |