Kuo-Hsin Tu NTU-P04922004

I am no longer abe to monitor this post , I have decided to move everything to my personal blog for better monitoring.

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update 完整版迁移至：https://github.com/yanring/jianzhi-Offer-Leetcode

确定性卷积：（把所有操作的seed=0，以便重现，会变慢） torch.backends.cudnn.deterministic https://oldpan.me/archives/pytorch-conmon-problem-in-training

添加torch.cuda.get_device_name和torch.cuda.get_device_capability实现如下功能。例：

torch.cuda.get_device_name(0) 'Quadro GP100' torch.cuda.get_device_capability(0) (6, 0)

	You are Manus, an AI agent created by the Manus team.

	You excel at the following tasks:
	1. Information gathering, fact-checking, and documentation
	2. Data processing, analysis, and visualization
	3. Writing multi-chapter articles and in-depth research reports
	4. Creating websites, applications, and tools
	5. Using programming to solve various problems beyond development
	6. Various tasks that can be accomplished using computers and the internet

	import base64
	import json
	import time

	import pyjson5
	import textwrap

	import pymongo
	from pyboy import PyBoy, WindowEvent
	from rich.pretty import pprint

	# coding=utf-8
	# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software

	from tqdm import tqdm
	from time import sleep
	import psutil

	with tqdm(total=100, desc='cpu%', position=1) as cpubar, tqdm(total=100, desc='ram%', position=0) as rambar:
	while True:
	rambar.n=psutil.virtual_memory().percent
	cpubar.n=psutil.cpu_percent()
	rambar.refresh()
	cpubar.refresh()

	# -- coding: utf-8 --
	"""
	Created on 2019-08-22 09:37:36

	@author: fmiorell
	"""

	# This script registers the "turbo" colormap to matplotlib, and the reversed version as "turbo_r"
	# Reference: https://ai.googleblog.com/2019/08/turbo-improved-rainbow-colormap-for.html

	from multiprocessing.dummy import Pool as ThreadPool
	import time
	import tqdm


	def _square(number):
	time.sleep(.5)
	return number * number

	from graphviz import Digraph
	import torch
	from torch.autograd import Variable, Function

	def iter_graph(root, callback):
	queue = [root]
	seen = set()
	while queue:
	fn = queue.pop()
	if fn in seen: