zhangfaen

## SimpleHTTPServerWithUpload.py
#!/usr/bin/env python

"""Simple HTTP Server With Upload.

This module builds on BaseHTTPServer by implementing the standard GET
and HEAD requests in a fairly straightforward manner.

"""

## cnn ocr
# pylint: disable=C0111,too-many-arguments,too-many-instance-attributes,too-many-locals,redefined-outer-name,fixme
# pylint: disable=superfluous-parens, no-member, invalid-name
import sys
sys.path.insert(0, "../../python")
import mxnet as mx
import numpy as np
import cv2, random

from io import BytesIO
from captcha.image import ImageCaptcha

## pg-pong.py
""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward

## prover_verifier.py
"""
Quick and dirty replication of
"Winning Gold at IMO 2025 with a Model-Agnostic Verification-and-Refinement Pipeline" (https://arxiv.org/abs/2507.15855)
using LangGraph.

Export GOOGLE_API_KEY to run.
Change the model, question and constants directly in the code (no CLI).
"""

import asyncio
	#!/usr/bin/env python

	"""Simple HTTP Server With Upload.

	This module builds on BaseHTTPServer by implementing the standard GET
	and HEAD requests in a fairly straightforward manner.

	"""
	# pylint: disable=C0111,too-many-arguments,too-many-instance-attributes,too-many-locals,redefined-outer-name,fixme
	# pylint: disable=superfluous-parens, no-member, invalid-name
	import sys
	sys.path.insert(0, "../../python")
	import mxnet as mx
	import numpy as np
	import cv2, random

	from io import BytesIO
	from captcha.image import ImageCaptcha
	""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
	import numpy as np
	import cPickle as pickle
	import gym

	# hyperparameters
	H = 200 # number of hidden layer neurons
	batch_size = 10 # every how many episodes to do a param update?
	learning_rate = 1e-4
	gamma = 0.99 # discount factor for reward
	"""
	Quick and dirty replication of
	"Winning Gold at IMO 2025 with a Model-Agnostic Verification-and-Refinement Pipeline" (https://arxiv.org/abs/2507.15855)
	using LangGraph.

	Export GOOGLE_API_KEY to run.
	Change the model, question and constants directly in the code (no CLI).
	"""

	import asyncio