openai(openai 入门)_1
大家好!今天让创意岭的小编来大家介绍下关于openai的问题,以下是小编对此问题的归纳整理,让我们一起来看看吧。
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本文目录:
一、openai哪里下载
openai百度文库下载。
先把你下载的openal32.dll删掉,也就是c:wiindowssystem32 文件夹中的openai32.dll和游戏文件夹中的openai32.dll 。然后下载OpenAL 最后再装上OpenAL 这就行了。
入口点函数只应执行简单的初始化任务,不应调用任何其他 DLL 加载函数或终止函数。例如,在入口点函数中,不应直接或间接调用 LoadLibrary 函数或 LoadLibraryEx 函数。此外,不应在进程终止时调用 FreeLibrary 函数。
DLL 故障排除工具:
可以使用多个工具来帮助您解决 DLL 问题。以下是其中的部分工具。 Dependency WalkerDependency Walker 工具可以递归扫描以寻找程序所使用的所有依赖 DLL。
当您在 Dependency Walker 中打开程序时,Dependency Walker 会执行下列检查: Dependency Walker 检查是否丢失 DLL。 Dependency Walker 检查是否存在无效的程序文件或 DLL。
二、openai经常网络错误
ChatGPT network error怎么解决?31 人关注0 条评论
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复制下人家的回答
“网络错误”可能不是BUG。这可能是OpenAI故意设置的限制,因为OpenAI正受到ChatGPT请求的狂轰滥炸,无法响应所有请求。
如果AI的响应时间超过一分钟,它就会自动失败。
这意味着:
1. 你的浏览器、账户或网络等都没有问题。
2. 无论你我做什么都无法弥补这个错误
3.OpenAI需要改变这一限制。
然后后面发了个代码。还是报错,但是不会清除回答。
实测用汉语说的问题将一直会出现这个问题,但是你可以一直说英语,将汉语转换为英语,然后就可以用了,貌似没有限制,另外建议使用英语,英语版语料库比汉语版的强大点,汉语版的语料库总感觉不对,有股说不来的感觉。
三、openai能当爬虫使吗
你好,可以的,Spinning Up是OpenAI开源的面向初学者的深度强化学习资料,其中列出了105篇深度强化学习领域非常经典的文章, 见 Spinning Up:
博主使用Python爬虫自动爬取了所有文章,而且爬下来的文章也按照网页的分类自动分类好。
见下载资源:Spinning Up Key Papers
源码如下:
import os
import time
import urllib.request as url_re
import requests as rq
from bs4 import BeautifulSoup as bf
'''Automatically download all the key papers recommended by OpenAI Spinning Up.
See more info on: https://spinningup.openai.com/en/latest/spinningup/keypapers.html
Dependency:
bs4, lxml
'''
headers = {
'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/92.0.4515.131 Safari/537.36'
}
spinningup_url = 'https://spinningup.openai.com/en/latest/spinningup/keypapers.html'
paper_id = 1
def download_pdf(pdf_url, pdf_path):
"""Automatically download PDF file from Internet
Args:
pdf_url (str): url of the PDF file to be downloaded
pdf_path (str): save routine of the downloaded PDF file
"""
if os.path.exists(pdf_path): return
try:
with url_re.urlopen(pdf_url) as url:
pdf_data = url.read()
with open(pdf_path, "wb") as f:
f.write(pdf_data)
except: # fix link at [102]
pdf_url = r"https://is.tuebingen.mpg.de/fileadmin/user_upload/files/publications/Neural-Netw-2008-21-682_4867%5b0%5d.pdf"
with url_re.urlopen(pdf_url) as url:
pdf_data = url.read()
with open(pdf_path, "wb") as f:
f.write(pdf_data)
time.sleep(10) # sleep 10 seconds to download next
def download_from_bs4(papers, category_path):
"""Download papers from Spinning Up
Args:
papers (bs4.element.ResultSet): 'a' tags with paper link
category_path (str): root dir of the paper to be downloaded
"""
global paper_id
print("Start to ownload papers from catagory {}...".format(category_path))
for paper in papers:
paper_link = paper['href']
if not paper_link.endswith('.pdf'):
if paper_link[8:13] == 'arxiv':
# paper_link = "https://arxiv.org/abs/1811.02553"
paper_link = paper_link[:18] + 'pdf' + paper_link[21:] + '.pdf' # arxiv link
elif paper_link[8:18] == 'openreview': # openreview link
# paper_link = "https://openreview.net/forum?id=ByG_3s09KX"
paper_link = paper_link[:23] + 'pdf' + paper_link[28:]
elif paper_link[14:18] == 'nips': # neurips link
paper_link = "https://proceedings.neurips.cc/paper/2017/file/a1d7311f2a312426d710e1c617fcbc8c-Paper.pdf"
else: continue
paper_name = '[{}] '.format(paper_id) + paper.string + '.pdf'
if ':' in paper_name:
paper_name = paper_name.replace(':', '_')
if '?' in paper_name:
paper_name = paper_name.replace('?', '')
paper_path = os.path.join(category_path, paper_name)
download_pdf(paper_link, paper_path)
print("Successfully downloaded {}!".format(paper_name))
paper_id += 1
print("Successfully downloaded all the papers from catagory {}!".format(category_path))
def _save_html(html_url, html_path):
"""Save requested HTML files
Args:
html_url (str): url of the HTML page to be saved
html_path (str): save path of HTML file
"""
html_file = rq.get(html_url, headers=headers)
with open(html_path, "w", encoding='utf-8') as h:
h.write(html_file.text)
def download_key_papers(root_dir):
"""Download all the key papers, consistent with the categories listed on the website
Args:
root_dir (str): save path of all the downloaded papers
"""
# 1. Get the html of Spinning Up
spinningup_html = rq.get(spinningup_url, headers=headers)
# 2. Parse the html and get the main category ids
soup = bf(spinningup_html.content, 'lxml')
# _save_html(spinningup_url, 'spinningup.html')
# spinningup_file = open('spinningup.html', 'r', encoding="UTF-8")
# spinningup_handle = spinningup_file.read()
# soup = bf(spinningup_handle, features='lxml')
category_ids = []
categories = soup.find(name='div', attrs={'class': 'section', 'id': 'key-papers-in-deep-rl'}).\
find_all(name='div', attrs={'class': 'section'}, recursive=False)
for category in categories:
category_ids.append(category['id'])
# 3. Get all the categories and make corresponding dirs
category_dirs = []
if not os.path.exitis(root_dir):
os.makedirs(root_dir)
for category in soup.find_all(name='h4'):
category_name = list(category.children)[0].string
if ':' in category_name: # replace ':' with '_' to get valid dir name
category_name = category_name.replace(':', '_')
category_path = os.path.join(root_dir, category_name)
category_dirs.append(category_path)
if not os.path.exists(category_path):
os.makedirs(category_path)
# 4. Start to download all the papers
print("Start to download key papers...")
for i in range(len(category_ids)):
category_path = category_dirs[i]
category_id = category_ids[i]
content = soup.find(name='div', attrs={'class': 'section', 'id': category_id})
inner_categories = content.find_all('div')
if inner_categories != []:
for category in inner_categories:
category_id = category['id']
inner_category = category.h4.text[:-1]
inner_category_path = os.path.join(category_path, inner_category)
if not os.path.exists(inner_category_path):
os.makedirs(inner_category_path)
content = soup.find(name='div', attrs={'class': 'section', 'id': category_id})
papers = content.find_all(name='a',attrs={'class': 'reference external'})
download_from_bs4(papers, inner_category_path)
else:
papers = content.find_all(name='a',attrs={'class': 'reference external'})
download_from_bs4(papers, category_path)
print("Download Complete!")
if __name__ == "__main__":
root_dir = "key-papers"
download_key_papers(root_dir)
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四、openai公司上市了吗
openai公司没有·上市。根据查询相关资料信息,OpenAI是一家通用人工智能(AGI)的研究公司,为了确保AI能够造福全人类,OpenAI提供了一个基于AI的开发和研究框架,这也是其名字的来源(开放AI能力),目前还没有上市。
以上就是关于openai相关问题的回答。希望能帮到你,如有更多相关问题,您也可以联系我们的客服进行咨询,客服也会为您讲解更多精彩的知识和内容。
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