File size: 10,661 Bytes
fc35a48 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 |
import os
import json
import gzip
import numpy as np
import itertools
from typing import *
from tqdm.auto import tqdm
from collections import defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
from human_eval.data import stream_jsonl
from human_eval.execution import check_correctness
IMPORT_HELPER = {
"python": [
"import math",
"import re",
"import sys",
"import copy",
"import datetime",
"import itertools",
"import collections",
"import heapq",
"import functools",
"import hashlib",
"import numpy",
"import numpy as np",
"import string",
"from typing import *",
"from collections import *",
"from functools import *"
],
"go" : [
"math",
"strings",
"fmt",
"strconv",
"time",
"bytes",
"regexp",
"sort",
"math/rand",
"crypto/md5",
],
"cpp" : [
"#include<stdlib.h>",
"#include<algorithm>",
"#include<math.h>",
"#include<stdio.h>",
"#include<vector>",
"#include<string>",
"#include<climits>",
"#include<cstring>",
"#include<iostream>",
],
}
LANGUAGE_NAME = {
"cpp" : "CPP",
"go" : "Go",
"java" : "Java",
"js" : "JavaScript",
"python": "Python",
}
def read_dataset(
data_file: str = None,
dataset_type: str = "humaneval",
num_shot=None,
) -> Dict:
if num_shot is not None:
print(f"{num_shot}-shot setting...")
if "humaneval" in dataset_type.lower():
if data_file is None:
current_path = os.path.dirname(os.path.abspath(__file__))
data_file = os.path.join(current_path, "..", "humaneval-x", "python", "data", "humaneval_python.jsonl.gz")
dataset = {task["task_id"]: task for task in stream_jsonl(data_file)}
else:
raise f"Dataset: {dataset_type} not supported."
return dataset
def estimate_pass_at_k(
num_samples: Union[int, List[int], np.ndarray],
num_correct: Union[List[int], np.ndarray],
k: int
) -> np.ndarray:
"""
Estimates pass@k of each problem and returns them in an array.
"""
def estimator(n: int, c: int, k: int) -> float:
"""
Calculates 1 - comb(n - c, k) / comb(n, k).
"""
if n - c < k:
return 1.0
return 1.0 - np.prod(1.0 - k / np.arange(n - c + 1, n + 1))
if isinstance(num_samples, int):
num_samples_it = itertools.repeat(num_samples, len(num_correct))
else:
assert len(num_samples) == len(num_correct)
num_samples_it = iter(num_samples)
return np.array([estimator(int(n), int(c), k) for n, c in zip(num_samples_it, num_correct)])
def process_humaneval_test(sample, problems, example_test=False, is_mbpp=False, language="python"):
task_id = sample["task_id"]
if is_mbpp:
return sample["generation"] + "\n" + "\n".join(problems[task_id]["test"])
#language = task_id.split("/")[0].lower()
prompt = sample.get("prompt", "")
if example_test and "example_test" in problems[task_id] and problems[task_id]["example_test"] != "":
test = problems[task_id]["example_test"]
else:
test = problems[task_id]["test"]
code = sample["generation"]
# Pre-process for different languages
if language == "python":
'''code_ = []
for line in code.split("\n"):
if (len(line.strip()) > 0 and line[0] != ' ' and line[0] != '\t'):
break
code_.append(line)
code = "\n".join(code_)'''
test_setup = "\n".join(IMPORT_HELPER["python"]) + "\n"
test_string = test_setup + code + "\n" + test + "\n"
elif language == "cpp":
test_set_up = ""
for s in IMPORT_HELPER["cpp"]:
if s not in prompt:
test_set_up += s + "\n"
test_string = test_set_up + "\n" + code + "\n" + test
elif language == "java":
test_string = code + "\n" + test
elif language in ["js", "javascript", "ts", "cs", "sh"]:
test_string = code + "\n" + test
elif language == "go":
import_string = problems[task_id]["import"]
prompt = prompt.replace(import_string, "")
if example_test and "example_test" in problems[task_id]:
test = problems[task_id]["example_test"]
else:
test = problems[task_id]["test"]
test_setup = problems[task_id]["test_setup"]
other_pkgs = []
for pkg in IMPORT_HELPER["go"]:
if pkg not in test_setup:
p = pkg.split("/")[-1]
if p + "." in code:
other_pkgs.append(f"\"{pkg}\"")
if other_pkgs:
import_other_pkgs = "import (\n" + " ".join([p + "\n" for p in other_pkgs]) + ")"
test_string = test_setup + "\n" + import_other_pkgs + "\n" + prompt + code + "\n" + test
else:
test_string = test_setup + "\n" + prompt + code + "\n" + test
elif language == "rust":
main = "\nfn main(){ \n } \n"
declaration = problems[task_id]["declaration"]
test_string = main + declaration + prompt + code + test
elif language == "php":
test_string = code + "\n" + test + "?>"
return test_string
def stream_jsonl_all(filename: str) -> Iterable[Dict]:
results = []
if filename.endswith(".gz"):
fp = gzip.open(open(filename, "rb"), "rt")
else:
fp = open(filename, "r")
for line in fp:
if any(not x.isspace() for x in line):
results.append(json.loads(line))
fp.close()
return results
def evaluate_functional_correctness(
input_file: str = None,
tmp_dir: str = "./",
n_workers: int = 32,
timeout: float = 10.0,
problem_file: str = "../data/humaneval_python.jsonl.gz",
result_path: str = None,
k: List[int] = [1, 10, 100],
test_groundtruth: bool = False,
example_test: bool = False,
is_mbpp: bool = False,
language: str = "python",
):
if example_test:
print("Example test...")
problems = read_dataset(problem_file, dataset_type="humaneval")
sample_jsonl = stream_jsonl_all(input_file)
with ThreadPoolExecutor(max_workers=n_workers) as executor:
futures = []
completion_id = Counter()
n_samples = 0
results = defaultdict(list)
if test_groundtruth:
print("Testing ground truth...")
for sample in tqdm(problems.values()):
task_id = sample["task_id"]
lang = task_id.split("/")[0].lower()
if lang == "javascript":
lang = "js"
tmp_dir_ = os.path.join(tmp_dir, lang, "evaluation")
sample["generation"] = sample["canonical_solution"]
sample["test_code"] = process_humaneval_test(sample, problems, example_test, language)
if sample["test_code"] is None:
continue
args = (task_id, sample, lang, timeout, tmp_dir_, completion_id[task_id])
future = executor.submit(check_correctness, *args)
futures.append(future)
completion_id[task_id] += 1
n_samples += 1
else:
print("Reading Samples...")
id2samples = {}
for sample in tqdm(sample_jsonl):
task_id = sample["task_id"]
if not is_mbpp:
lang = language
if not is_mbpp and lang == "javascript":
lang = "js"
if is_mbpp:
lang = "python"
tmp_dir_ = os.path.join(tmp_dir, lang, "evaluation")
sample["task_id"] = task_id
sample["test_code"] = process_humaneval_test(sample, problems, example_test, is_mbpp, language)
if sample["test_code"] is None:
continue
if "completion_id" in sample:
completion_id_ = sample["completion_id"]
else:
completion_id_ = completion_id[task_id]
args = (task_id, sample, lang, timeout, tmp_dir_, completion_id_)
id2samples[(task_id, completion_id_)] = sample
future = executor.submit(check_correctness, *args)
futures.append(future)
completion_id[task_id] += 1
n_samples += 1
if len(completion_id) == len(problems):
evaluate_pass_at_k = True
else:
evaluate_pass_at_k = False
print("Running test suites...")
sample_with_results = []
for future in tqdm(as_completed(futures), total=len(futures)):
result = future.result()
results[result["task_id"]].append((result["completion_id"], result))
sample = id2samples[(result["task_id"], result["completion_id"])]
sample_with_results.append({
'task_id': result['task_id'],
'completion_id': result["completion_id"],
'passed': result['passed'],
'generation': sample['generation']
})
for key in sample:
if key not in sample_with_results[-1]:
sample_with_results[-1][key] = sample[key]
# Calculate pass@k.
total, correct = [], []
for result in results.values():
passed = [r[1]["passed"] for r in result]
total.append(len(passed))
correct.append(sum(passed))
total = np.array(total)
correct = np.array(correct)
if evaluate_pass_at_k:
ks = k
pass_at_k = {
f"pass@{k}": estimate_pass_at_k(total, correct, k).mean()
for k in ks if (total >= k).all()
}
print(pass_at_k)
else:
print("Total:", np.sum(total))
print("Correct:", np.sum(correct))
if result_path is not None:
with open(result_path, 'w', encoding='utf-8') as fw:
for sample_with_result in sample_with_results:
fw.write(json.dumps(sample_with_result) + '\n')
print("Save evaluation results to\n{}".format(result_path))
return pass_at_k
|