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https://github.com/open-thought/reasoning-gym.git
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filtering
This commit is contained in:
Zafir Stojanovski
parent
f19498edb8
commit
8a0423f185
1 changed files with 97 additions and 67 deletions
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"source": [
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"import abc\n",
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"import asyncio\n",
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"from collections import defaultdict\n",
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"import json\n",
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"import os\n",
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"import random\n",
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"from random import Random\n",
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"import re\n",
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"import signal\n",
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"from typing import Union\n",
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"\n",
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"import aiohttp\n",
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "3a63a9127ee24e039b91c83a714ee994",
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"version_major": 2,
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"version_minor": 0
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},
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"outputs": [],
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"source": [
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Filter out invalid input generators\n",
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"\n",
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"**NOTE**: The code below is buggy because we have a memory leak (I think) - every time you run the `exec` with some code snippet, it stores the variables in the global scope. Over time, this will consume all the memory. And besides, running `exec` on untrusted code is not smart."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Example of how to execute the generated code\n",
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"# local_dict = {}\n",
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"# exec(data['input_generator'], globals(), local_dict)\n",
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"# generate_input_func = local_dict['generate_input']\n",
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"# rng = random.Random()\n",
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"# def timeout_handler(signum, frame):\n",
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"# raise TimeoutError(\"Function call timed out\")\n",
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"\n",
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"# for i in range(5):\n",
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"# random_input = generate_input_func(rng)\n",
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"# print(f\"[{i}]: {random_input}\")"
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"# def get_input_generator_func(code_sample: str, input_generator_str: str) -> dict:\n",
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"# env = globals().copy()\n",
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"# exec(code_sample, env, env)\n",
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"# exec(input_generator_str, env, env)\n",
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"# return env['generate_input']\n",
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"\n",
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"# def execute_code_sample(code_sample: str, input_dict: dict) -> dict:\n",
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"# env = globals().copy()\n",
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"# exec(code_sample, env, env)\n",
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"# main_solution = env['main_solution']\n",
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"# return main_solution(**input_dict)\n",
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"\n",
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"# NUM_INPUT_GENERATE = 1_000 # how many inputs to try and generate\n",
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"# ALARM_TOLERANCE = 1 # in seconds\n",
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"# PERCENT_UNIQUE_INPUTS = 0.30 # what fraction of generated inputs should be unique\n",
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"# PERCENT_UNIQUE_OUTPUTS = 0.30 # what fraction of generated outputs should be unique\n",
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"\n",
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"# signal.signal(signal.SIGALRM, timeout_handler)\n",
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"\n",
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"# rng = random.Random()\n",
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"# rng.seed(42)\n",
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"\n",
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"# errors = defaultdict(int)\n",
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"# total_entries = sum(1 for _ in open(\"data/codeio-pyedu-with-input-generator.jsonl\", \"r\"))\n",
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"\n",
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"# with open(\"data/codeio-pyedu-with-input-generator.jsonl\", \"r\") as f_in, \\\n",
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"# open(\"data/codeio-pyedu-with-input-generator-filtered.jsonl\", \"w+\") as f_out:\n",
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"\n",
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"# iterator = tqdm(enumerate(f_in), total=total_entries)\n",
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"\n",
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"# for i, line in iterator:\n",
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"# iterator.set_description(f\"Processing {i}/{total_entries} | \" + \" | \".join(f\"{k}: {v}\" for k, v in errors.items()) + f\" | total: {sum(errors.values())}\")\n",
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"# entry = json.loads(line)\n",
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"# # Check if input generator is present\n",
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"# if not \"input_generator\" in entry:\n",
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"# errors[\"missing_input_generator\"] += 1\n",
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"# continue\n",
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" \n",
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"# # Check if input generator is valid function\n",
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"# try:\n",
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"# input_generator_func = get_input_generator_func(entry['code_sample'], entry['input_generator'])\n",
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"# except Exception as e:\n",
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"# errors[\"cannot_instantiate_input_generator\"] += 1\n",
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"# continue\n",
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"\n",
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"# skip = False\n",
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"# seen_inputs, seen_outputs = set(), set()\n",
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"\n",
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"# for _ in range(NUM_INPUT_GENERATE):\n",
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"# try:\n",
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"# # Check if you can generate input\n",
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"# signal.alarm(ALARM_TOLERANCE)\n",
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"# random_input = input_generator_func(rng)\n",
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"# signal.alarm(0)\n",
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"# seen_inputs.add(hash(json.dumps(random_input)))\n",
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"\n",
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"# # Check if code snippet can execute with generated input\n",
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"# signal.alarm(ALARM_TOLERANCE)\n",
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"# random_output = execute_code_sample(entry[\"code_sample\"], random_input)\n",
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"# signal.alarm(0)\n",
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"# seen_outputs.add(hash(json.dumps(random_output)))\n",
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"# except Exception as e:\n",
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"# signal.alarm(0)\n",
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"# errors[\"unreliable_input_generator\"] += 1\n",
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"# skip = True\n",
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"# break\n",
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"# if skip: \n",
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"# continue\n",
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" \n",
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"# if len(seen_inputs) / NUM_INPUT_GENERATE < PERCENT_UNIQUE_INPUTS:\n",
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"# errors[\"insufficient_unique_inputs\"] += 1\n",
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"# continue\n",
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" \n",
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"# if len(seen_outputs) / NUM_INPUT_GENERATE < PERCENT_UNIQUE_OUTPUTS:\n",
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"# errors[\"insufficient_unique_outputs\"] += 1\n",
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"# continue\n",
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"\n",
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"# f_out.write(json.dumps(entry))\n",
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"# f_out.write(\"\\n\")\n",
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"\n",
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"# for k, v in errors.items():\n",
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"# print(f\"{k}: {v}\")"
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]
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},
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{
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