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import os
import sys
with open(sys.argv[0]) as f:
    code = f.read() # read the code of this file ASAP, for logging

with open('optimizer.py', 'r', encoding='utf-8') as f:
    source_code = f.read()
    code += source_code

with open('model.py', 'r', encoding='utf-8') as f:

lapp0

import os
import sys
with open(sys.argv[0]) as f:
    code = f.read() # read the code of this file ASAP, for logging
import uuid
import time
import contextlib
from dataclasses import dataclass
import math
from pathlib import Path

lapp0

import os
import sys
with open(sys.argv[0]) as f:
    code = f.read() # read the code of this file ASAP, for logging
import uuid
import time
import contextlib
from dataclasses import dataclass
import math
from pathlib import Path

lapp0

import os
import sys
with open(sys.argv[0]) as f:
    code = f.read() # read the code of this file ASAP, for logging
import uuid
import time
import contextlib
from dataclasses import dataclass
from pathlib import Path

lapp0

import os
import sys
with open(sys.argv[0]) as f:
    code = f.read() # read the code of this file ASAP, for logging
import uuid
import glob
import time
import contextlib
from dataclasses import dataclass
from typing import Optional

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Running pytorch 2.6.0.dev20241126+cu124 compiled for CUDA 12.4
nvidia-smi:
Fri Nov 29 00:54:16 2024       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 550.76                 Driver Version: 550.76         CUDA Version: 12.4     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|

lapp0

Remove evil parts of answer.

Code

import outlines

qwen_model = outlines.models.transformers("Qwen/Qwen2.5-14B-Instruct", model_kwargs=dict(load_in_8bit=True))


def ask_non_evil_question(prompt, pattern, model=qwen_model, max_tokens=100):

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import random
import collections


def trial(first_to=2):
    flips = [random.choice([True, False]) for _ in range(100)]
    alice_flip_checks = flips
    bob_flip_checks = [flips[i] for i in range(1, len(flips), 2)] + [flips[i] for i in range(0, len(flips), 2)]
    # get second_head
    try:

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from datasets import Dataset, load_from_disk
from transformers import TrainingArguments
from transformers.trainer_utils import EvalLoopOutput
from unsloth import FastLanguageModel
import random
from huggingface_hub import create_repo

from scipy.spatial.distance import cosine
from sentence_transformers import SentenceTransformer
import statistics

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# Huge Pattern
`0(0(0([1235679]-(0(2-(0[1-9]|1\\d|2[0-8])|[13578]-(0[1-9]|3[01]|[12]\\d)|[469]-(0[1-9]|30|[12]\\d))|1(1-(0[1-9]|30|[12]\\d)|[02]-(0[1-9]|3[01]|[12]\\d)))|[48]-(0(2-(0[1-9]|[12]\\d)|[13578]-(0[1-9]|3[01]|[12]\\d)|[469]-(0[1-9]|30|[12]\\d))|1(1-(0[1-9]|30|[12]\\d)|[02]-(0[1-9]|3[01]|[12]\\d))))|[13579]([01345789]-(0(2-(0[1-9]|1\\d|2[0-8])|[13578]-(0[1-9]|3[01]|[12]\\d)|[469]-(0[1-9]|30|[12]\\d))|1(1-(0[1-9]|30|[12]\\d)|[02]-(0[1-9]|3[01]|[12]\\d)))|[26]-(0(2-(0[1-9]|[12]\\d)|[13578]-(0[1-9]|3[01]|[12]\\d)|[469]-(0[1-9]|30|[12]\\d))|1(1-(0[1-9]|30|[12]\\d)|[02]-(0[1-9]|3[01]|[12]\\d))))|[2468]([048]-(0(2-(0[1-9]|[12]\\d)|[13578]-(0[1-9]|3[01]|[12]\\d)|[469]-(0[1-9]|30|[12]\\d))|1(1-(0[1-9]|30|[12]\\d)|[02]-(0[1-9]|3[01]|[12]\\d)))|[1235679]-(0(2-(0[1-9]|1\\d|2[0-8])|[13578]-(0[1-9]|3[01]|[12]\\d)|[469]-(0[1-9]|30|[12]\\d))|1(1-(0[1-9]|30|[12]\\d)|[02]-(0[1-9]|3[01]|[12]\\d)))))|[1235679](0([0-35679]-(0(2-(0[1-9]|1\\d|2[0-8])|[13578]-(0[1-9]|3[01]|[12]\\d)|[469]-(0[1-9]|30|[12]\\d))|1(1-(0[1-9]|30