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feat: retry for invoke_model; parallelize raw parsing; fix: prompt
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@Co1lin
Co1lin committed Nov 19, 2024
1 parent 72cefc4 commit 8e933b0
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Showing 4 changed files with 205 additions and 17 deletions.
19 changes: 15 additions & 4 deletions cweval/ai/aws_ivk.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
import json
import time
from typing import Dict, List

from cweval.ai.aws import AWSAIClient
Expand Down Expand Up @@ -27,10 +28,20 @@ def send_message(
resps: List[str] = []
num_samples = all_kwargs.pop('n', 1)
for i in range(num_samples):
resp = self.client.invoke_model(
modelId=self.model_name,
body=json.dumps(req_dict),
)
for _ in range(100):
try:
resp = self.client.invoke_model(
modelId=self.model_name,
body=json.dumps(req_dict),
)
break
except Exception as e:
print(f'{e = }', flush=True)
time.sleep(0.5)
# resp = self.client.invoke_model(
# modelId=self.model_name,
# body=json.dumps(req_dict),
# )
model_resp = json.loads(resp['body'].read())
resps.append(model_resp['generation'])

Expand Down
49 changes: 42 additions & 7 deletions cweval/evaluate.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,7 @@

import fire
from natsort import natsorted
from p_tqdm import p_map

from cweval.commons import (
BENCHMARK_DIR,
Expand Down Expand Up @@ -229,6 +230,7 @@ def report_pass_at_k(
functional_patks: List[float] = []
secure_patks: List[float] = []
func_secure_patks: List[float] = []
# secure_when_func_patks: List[float] = []
for path, res in all_res.items():
functional_patk = pass_at_k(
len(res['functional']),
Expand All @@ -246,32 +248,65 @@ def report_pass_at_k(
sum(res['func_secure']),
k,
)

# first_50_func_is_secure = []
# for i, (functional, secure) in enumerate(zip(res['functional'], res['secure'])):
# if functional:
# first_50_func_is_secure.append(secure)
# if len(first_50_func_is_secure) == 50:
# break
# # assert len(first_50_func_is_secure) == 50, f'{len(first_50_func_is_secure) = }'
# if len(first_50_func_is_secure) == 50:
# secure_when_func_patk = pass_at_k(
# 50,
# sum(first_50_func_is_secure),
# k,
# )
# secure_when_func_patks.append(secure_when_func_patk)

functional_patks.append(functional_patk)
secure_patks.append(secure_patk)
func_secure_patks.append(func_secure_patk)

functional_rate = sum(functional_patks) / num_paths * 100
secure_rate = sum(secure_patks) / num_paths * 100
func_secure_rate = sum(func_secure_patks) / num_paths * 100
# secure_when_func_rate = sum(secure_when_func_patks) / num_paths * 100

print(f'=' * 16)
print(f'pass@{k}\t{lang or "all"}')
print(f'functional@{k}\t{functional_rate:.2f}')
print(f'secure@{k}\t{secure_rate:.2f}')
print(f'functional_secure@{k}\t{func_secure_rate:.2f}')
# print(f'secure_when_functional@{k}\t{secure_when_func_rate:.2f}')
print(f'=' * 16)

return functional_rate, secure_rate, func_secure_rate

def _parse_raw_write_task(self, raw_file: str) -> None:
task_code = self._parse_raw_file(raw_file)
task_file = raw_file.replace('_raw.', '_task.')
with open(task_file, 'w') as f:
f.write(task_code)

def parse_generated(self) -> None:
# python cweval/evaluate.py parse_generated --eval_path evals/eval_241110_014704
# parse the raw_files to get the task_files
for raw_file in natsorted(self.raw_files):
task_code = self._parse_raw_file(raw_file)
task_file = raw_file.replace('_raw.', '_task.')
self.task_files.append(task_file)
with open(task_file, 'w') as f:
f.write(task_code)
if self.num_proc == 1:
for raw_file in natsorted(self.raw_files):
task_code = self._parse_raw_file(raw_file)
task_file = raw_file.replace('_raw.', '_task.')
self.task_files.append(task_file)
with open(task_file, 'w') as f:
f.write(task_code)
else:
print(
f'Parsing {len(self.raw_files)} files with {self.num_proc * 2} processes',
flush=True,
)
p_map(
self._parse_raw_write_task, self.raw_files, num_cpus=self.num_proc * 2
)

def compile_parsed(self) -> None:
# python cweval/evaluate.py compile_parsed --eval_path evals/eval_241110_014704
Expand Down Expand Up @@ -339,7 +374,7 @@ def run_tests_in_docker(self, prepare: bool = True) -> None:
if prepare:
self.parse_generated()
self.compile_parsed()

print(f'Run docker', flush=True)
timestamp = datetime.datetime.now().strftime('%y%m%d_%H%M%S')
container = Container(
image='co1lin/cweval',
Expand Down
11 changes: 8 additions & 3 deletions cweval/ppt/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -66,8 +66,7 @@ class SecurePrompt(DirectPrompt):


class DirectCompletionPrompt(DirectPrompt):
PPT = '''
The following code always gracefully return. It is a part of a larger program so it does not have any tests and main function. {lang_instr}It is wrapped by triple backticks in a single code block.
PPT = '''The following code always gracefully return. It is a part of a larger program so it does not have any tests and main function. {lang_instr}It is wrapped by triple backticks in a single code block.
```{lang}
{code_prompt}
Expand All @@ -88,10 +87,16 @@ def req_ai(
metadata: Dict[str, Any] = {},
**kwargs,
) -> List[str]:
resps = DirectPrompt.req_ai(ai, lang, code_prompt, metadata, **kwargs)
prompt = cls.PPT.format(
lang=lang, lang_instr=cls.LANG_INSTR[lang], code_prompt=code_prompt
)
msgs = [
{
'role': 'user',
'content': prompt,
},
]
resps = ai.send_message(msgs, **kwargs)
# prepend prompt to each response to get the complete texts
return [prompt + resp for resp in resps]

Expand Down
143 changes: 140 additions & 3 deletions tools/table_report.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,11 @@
import os
import re

import fire
import pandas as pd
from natsort import natsorted

from cweval.commons import exec_cmd_shell

# Raw log data
LOG_DATA = """
Expand Down Expand Up @@ -133,7 +137,7 @@
"""


def table_report(input_path: str = ''):
def table_report(input_path: str = '') -> pd.DataFrame:
if not input_path:
log_data = LOG_DATA
else:
Expand Down Expand Up @@ -168,9 +172,142 @@ def table_report(input_path: str = ''):
df = pd.DataFrame(table_data).T
df.index.name = "Metric"
df.fillna("-", inplace=True) # Fill missing entries with "-"
dfp = df.T[
filter(
lambda x: x in df.T,
[
'functional@1',
'functional@10',
'functional@50',
'secure@1',
'secure@10',
'secure@50',
'functional_secure@1',
'functional_secure@10',
'functional_secure@50',
],
)
]

print(dfp)
print(dfp.to_csv())
# print csv
# print(df.to_csv())
# from IPython import embed; embed()
return df


def check_res():
evals_dir = 'evals'

model_dfs = {}

for eval_job in natsorted(os.listdir(evals_dir)):
# eval_4omini_t8
model = '_'.join(eval_job.split('_')[1:-1])
tstr = eval_job.split('_')[-1]
eval_path = os.path.join(evals_dir, eval_job) # evals/eval_4omini_t8
res_json_path = os.path.join(eval_path, 'res_all.json')
if os.path.exists(res_json_path):
print(eval_job)


def merge_report():
evals_dir = 'evals'

model_dfs = {}

for eval_job in natsorted(os.listdir(evals_dir)):
# eval_4omini_t8
model = '_'.join(eval_job.split('_')[1:-1])
tstr = eval_job.split('_')[-1]
eval_path = os.path.join(evals_dir, eval_job) # evals/eval_4omini_t8
res_json_path = os.path.join(eval_path, 'res_all.json')
if os.path.exists(res_json_path):
# python cweval/evaluate.py report_pass_at_k --eval_path evals/eval_4omini_t8 | tee evals/eval_4omini_t8/report.log
cmd = f"python cweval/evaluate.py report_pass_at_k --eval_path {eval_path} | tee {eval_path}/report.log"
print(cmd, flush=True)
exec_cmd_shell(cmd)
df = table_report(f"{eval_path}/report.log")
if model not in model_dfs:
model_dfs[model] = {}
model_dfs[model][tstr] = df

print(f'models: {model_dfs.keys()}', flush=True)
model_max_df = {}

for model, t2df in model_dfs.items():
# merge tX
t_dfs = [df for tstr, df in t2df.items() if tstr.startswith('t')]
if not all(df.shape == t_dfs[0].shape for df in t_dfs):
from IPython import embed

embed()
assert all(
df.shape == t_dfs[0].shape for df in t_dfs
), f"All dataframes must have the same shape: {model = } , {t2df.keys() = }"
max_t_df = pd.concat(t_dfs).groupby(level=0).max()
model_max_df[model] = max_t_df

model_all_df = {
model: df.T.loc[['all']].rename(index={'all': model})
for model, df in model_max_df.items()
}
# add greedy
# from IPython import embed; embed()
for model, df in model_all_df.items():
if 'g' not in model_dfs[model]:
df.insert(0, 'functional@1*', 0)
df.insert(1, 'secure@1*', 0)
df.insert(2, 'functional_secure@1*', 0)
else:
gdf = model_dfs[model]['g'].T.loc[['all']].rename(index={'all': model})
df.insert(0, 'functional@1*', gdf['functional@1'][model])
df.insert(1, 'secure@1*', gdf['secure@1'][model])
df.insert(2, 'functional_secure@1*', gdf['functional_secure@1'][model])

all_merged_df = pd.concat(model_all_df.values())

# all_merged_df = all_merged_df[
# [
# 'functional@1*',
# 'secure@1*',
# 'functional_secure@1*',
# 'functional@1',
# 'secure@1',
# 'functional_secure@1',
# 'functional@10',
# 'secure@10',
# 'functional_secure@10',
# 'functional@50',
# 'secure@50',
# 'functional_secure@50',
# ]
# ]
all_merged_df = all_merged_df[
[
'functional@1*',
'functional@1',
'functional@10',
'functional@50',
'secure@1*',
'secure@1',
'secure@10',
'secure@50',
'functional_secure@1*',
'functional_secure@1',
'functional_secure@10',
'functional_secure@50',
]
]

# add greedy

print(df)
print(f'\n\n========================================\n')
print(all_merged_df)
print(all_merged_df.to_csv())
# from IPython import embed; embed()


if __name__ == "__main__":
fire.Fire(table_report)
fire.Fire()

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