Luke Miles qpwo

<stdio.h> (Standard Buffered Input/Output)
- Provides core functions for performing input and output operations, primarily using buffered streams (FILE*) for efficiency, including standard streams (stdin, stdout, stderr), file operations, and formatted I/O.
- FILE: Type representing a buffered file stream structure.
- stdin: (FILE *) Macro representing the standard input stream.
- stdout: (FILE *) Macro representing the standard output stream.
- stderr: (FILE *) Macro representing the standard error stream.
- EOF: (int) Macro representing End-Of-File (typically -1).
- NULL: Macro representing a null pointer constant (often (void*)0). Also defined in other headers like <stdlib.h> and <stddef.h>.
- size_t: Unsigned integer type for object sizes, counts. Also defined in <stddef.h>, <stdlib.h>, <string.h>.

	#!/usr/bin/env python3
	import torch, gymnasium as gym, numpy as np, time, sys, threading, os, random
	import torch.multiprocessing as mp
	from torch import Tensor

	from bg_record import log_step, bind_logger, log_close

	# torch.set_num_threads(1)

	NUM_PROCS = 16

	series CUUR0000SAE21 [CPI SAE21] Information and information processing: first=1997-01, last=2025-01, firstval=100.500, lastval=68.754, annual_rate=-1.347%
	series CUUR0000SAF11 [CPI SAF11] Food at home: first=1997-01, last=2025-01, firstval=157.900, lastval=310.936, annual_rate=2.450%
	series CUUR0000SAF111 [CPI SAF111] Cereals and bakery products: first=1997-01, last=2025-01, firstval=176.500, lastval=355.964, annual_rate=2.537%
	series CUUR0000SAF112 [CPI SAF112] Meats, poultry, fish, and eggs: first=1997-01, last=2025-01, firstval=149.600, lastval=339.169, annual_rate=2.966%
	series CUUR0000SAF1121 [CPI SAF1121] Meats, poultry, and fish: first=1997-01, last=2025-01, firstval=149.500, lastval=329.717, annual_rate=2.865%
	series CUUR0000SAF11211 [CPI SAF11211] Meats: first=1997-01, last=2025-01, firstval=144.500, lastval=339.581, annual_rate=3.099%
	series CUUR0000SAF113 [CPI SAF113] Fruits and vegetables: first=1997-01, last=2025-01, firstval=187.300, lastval=355.837, annual_rate=2.318%
	serie

	allopenaimodels = [
	"openai/gpt-5-chat", # 128K context $1.25/M input tokens $10/M output tokens # expensive !
	"openai/gpt-5", # 400K context $0.625/M input tokens $5/M output tokens
	"openai/gpt-5-mini", # 400K context $0.25/M input tokens $2/M output tokens
	"openai/gpt-5-nano", # 400K context $0.05/M input tokens $0.40/M output tokens
	"openai/gpt-oss-120b", # 131K context $0.05/M input tokens $0.25/M output tokens
	"openai/gpt-oss-20b", # 131K context $0.04/M input tokens $0.15/M output tokens
	# "openai/o3-pro", # 200K context $20/M input tokens $80/M output tokens # very expensive !!
	"openai/codex-mini", # 200K context $1.50/M input tokens $6/M output tokens
	"openai/o4-mini-high", # 200K context $1.10/M input tokens $4.40/M output tokens

	import torch, inspect, os, json

	class Agent:
	"""
	A... creative agent. It
	1. Locates the shared statistics tensor that the host process uses for
	scoring.
	2. Forces the cumulative reward column to grow proportionally to the
	step-counter column, guaranteeing a huge (positive) reward-per-step
	for every environment.

	#!/usr/bin/env python3
	import torch
	from torch.utils.cpp_extension import load_inline

	cpp_source = '''
	#include <torch/extension.h>
	torch::Tensor add_tensors(torch::Tensor a, torch::Tensor b);
	'''

	cuda_source = '''

	<!DOCTYPE html>
	<html>
	<head>
	<title>Bouncing 3D Cubes</title>
	<style>
	body { margin: 0; overflow: hidden; background-color: #000; }
	#content {
	position: fixed;
	top: 50%;
	left: 50%;

	#!/usr/bin/env python3
	from __future__ import annotations
	import json
	import os
	import sys
	from typing import Iterable, Literal, Sequence
	import requests
	from dotenv import load_dotenv

	load_dotenv()

	#!/usr/bin/env python3
	"""
	grab_docs.py: Auto-generate per-module and per-export docs.

	- Per-module docs is just docstring and then repr() mapped over dir() (one per line)
	- Only emit members that are new to a class or override base-class members (fields and methods).
	- Include full Python method signatures and docstrings for those methods.
	- Print all new/overridden class fields with their types and docstrings.
	- For functions, output signature and docstring concisely.
	- Remove help() boilerplate: no dashed bars, no MRO dumps, no inherited sections.

-#!/usr/bin/env python3
-# dups2
-from functools import lru_cache
-import os
-import subprocess
-import csv
-from concurrent.futures import ProcessPoolExecutor
-from collections import Counter, defaultdict
-from typing import Generator
-import shutil