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from __future__ import annotations
import os
import sys
from pathlib import Path
import numpy as np
import tokenizers
import torch
from packaging.version import parse as parse_version
from lm_eval import tasks
from lm_eval.api.instance import Instance
from lm_eval.models.huggingface import HFLM
os.environ["TOKENIZERS_PARALLELISM"] = "false"
task_manager = tasks.TaskManager()
TEST_STRING = "foo bar"
class Test_HFLM:
torch.use_deterministic_algorithms(True)
task_list = task_manager.load_task_or_group(["arc_easy", "gsm8k", "wikitext"])
version_minor = sys.version_info.minor
multiple_choice_task = task_list["arc_easy"] # type: ignore
multiple_choice_task.build_all_requests(limit=10, rank=0, world_size=1)
MULTIPLE_CH: list[Instance] = multiple_choice_task.instances
generate_until_task = task_list["gsm8k"] # type: ignore
generate_until_task._config.generation_kwargs["max_gen_toks"] = 10
generate_until_task.set_fewshot_seed(1234) # fewshot random generator seed
generate_until_task.build_all_requests(limit=10, rank=0, world_size=1)
generate_until: list[Instance] = generate_until_task.instances
rolling_task = task_list["wikitext"] # type: ignore
rolling_task.build_all_requests(limit=10, rank=0, world_size=1)
ROLLING: list[Instance] = rolling_task.instances
MULTIPLE_CH_RES = [
-41.902435302734375,
-42.939308166503906,
-33.914180755615234,
-37.07139205932617,
-22.95258331298828,
-20.342208862304688,
-14.818366050720215,
-27.942853927612305,
-15.80704116821289,
-15.936427116394043,
-13.052018165588379,
-18.04828453063965,
-13.345029830932617,
-13.366025924682617,
-12.127134323120117,
-11.872495651245117,
-47.10598373413086,
-47.76410675048828,
-36.4406852722168,
-50.0289421081543,
-16.72093963623047,
-18.535587310791016,
-26.46993637084961,
-20.355995178222656,
-17.757919311523438,
-21.80595588684082,
-33.1990852355957,
-39.28636932373047,
-14.759679794311523,
-16.753942489624023,
-11.486852645874023,
-15.42177677154541,
-13.15798282623291,
-15.887393951416016,
-15.28614616394043,
-12.339089393615723,
-44.59441375732422,
-55.40888214111328,
-52.70050811767578,
-56.25089645385742,
]
generate_until_RES = [
" The average of $2.50 each is $",
" A robe takes 2 bolts of blue fiber and half",
" $50,000 in repairs.\n\nQuestion",
" He runs 1 sprint 3 times a week.",
" They feed each of her chickens three cups of mixed",
" The price of the glasses is $5, but",
" The total percentage of students who said they like to",
" Carla is downloading a 200 GB file. Normally",
" John drives for 3 hours at a speed of 60",
" Eliza sells 4 tickets to 5 friends so she",
]
ROLLING_RES = [
-3603.6328125,
-19779.23974609375,
-8834.16455078125,
-27967.591796875,
-7636.794982910156,
-9491.93505859375,
-41043.4248046875,
-8397.689819335938,
-45969.47155761719,
-7158.90625,
]
LM = HFLM(pretrained="EleutherAI/pythia-70m", device="cpu", dtype="float32")
def test_logliklihood(self) -> None:
res = self.LM.loglikelihood(self.MULTIPLE_CH)
_RES, _res = self.MULTIPLE_CH_RES, [r[0] for r in res]
# log samples to CI
dir_path = Path("test_logs")
dir_path.mkdir(parents=True, exist_ok=True)
file_path = dir_path / f"outputs_log_{self.version_minor}.txt"
file_path = file_path.resolve()
with open(file_path, "w", encoding="utf-8") as f:
f.write("\n".join(str(x) for x in _res))
assert np.allclose(_res, _RES, atol=1e-2)
# check indices for Multiple Choice
argmax_RES, argmax_res = (
np.argmax(np.array(_RES).reshape(-1, 4), axis=1),
np.argmax(np.array(_res).reshape(-1, 4), axis=1),
)
assert (argmax_RES == argmax_res).all()
def test_generate_until(self) -> None:
res = self.LM.generate_until(self.generate_until)
assert res == self.generate_until_RES
def test_logliklihood_rolling(self) -> None:
res = self.LM.loglikelihood_rolling(self.ROLLING)
assert np.allclose(res, self.ROLLING_RES, atol=1e-1)
def test_toc_encode(self) -> None:
res = self.LM.tok_encode(TEST_STRING)
assert res == [12110, 2534]
def test_toc_decode(self) -> None:
res = self.LM.tok_decode([12110, 2534])
assert res == TEST_STRING
def test_batch_encode(self) -> None:
res = self.LM.tok_batch_encode([TEST_STRING, "bar foo"])[0].tolist()
assert res == [[12110, 2534], [2009, 17374]]
def test_model_generate(self) -> None:
context = self.LM.tok_batch_encode([TEST_STRING])[0]
res = self.LM._model_generate(context, max_length=10, stop=["\n\n"])
res = self.LM.tok_decode(res[0])
if parse_version(tokenizers.__version__) >= parse_version("0.20.0"):
assert res == "foo bar\n<bazhang> !info bar"
else:
assert res == "foo bar\n<bazhang>!info bar"
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