windbg

#!/usr/bin/env python
#coding=utf-8
import datetime
import os
import sys

from tornado.curl_httpclient import CurlAsyncHTTPClient as AsyncHTTPClient
from tornado import ioloop

ROOT_PATH = os.path.join(os.path.realpath(os.path.dirname(__file__)), '..')

windbg

# encoding: utf-8

"""
A python logging Handler that use ZeroMQ (ØMQ).

            +------+      +------+      +-------+
            | app1 |      | app2 |      | app X |
            +------+      +------+      +-------+
                | PUSH       |  PUSH        |   PUSH
                |            |              |

windbg

setenv SSH_ENV $HOME/.ssh/environment

if [ -n "$SSH_AGENT_PID" ] 
    ps -ef | grep $SSH_AGENT_PID | grep ssh-agent > /dev/null
    if [ $status -eq 0 ]
        test_identities
    end  
else
    if [ -f $SSH_ENV ]
        . $SSH_ENV > /dev/null

windbg

#!/usr/bin/env python  
#coding=utf-8
#  
# Generate a list of dnsmasq rules with ipset for gfwlist
#  
# Copyright (C) 2014 http://www.shuyz.com   
# Ref https://code.google.com/p/autoproxy-gfwlist/wiki/Rules    
 
import urllib2 
import re

windbg

If you want to use the latest available version of Squid, you can Build a Squid anonymous proxy from source code

Setup a Squid anonymous proxy

Table of contents

• Disclaimer
• Squid installation script
• Manage users

windbg

''' Script for downloading all GLUE data.

Note: for legal reasons, we are unable to host MRPC.
You can either use the version hosted by the SentEval team, which is already tokenized, 
or you can download the original data from (https://download.microsoft.com/download/D/4/6/D46FF87A-F6B9-4252-AA8B-3604ED519838/MSRParaphraseCorpus.msi) and extract the data from it manually.
For Windows users, you can run the .msi file. For Mac and Linux users, consider an external library such as 'cabextract' (see below for an example).
You should then rename and place specific files in a folder (see below for an example).

mkdir MRPC
cabextract MSRParaphraseCorpus.msi -d MRPC

windbg

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

windbg

0.
基于tf2.0
1.
把已有的模型导出成pb格式
保存的时候的INFO:tensorflow:Unsupported signature for serialization貌似不用管
python code:

import os
os.environ['TF_KERAS'] = '1'
import numpy as np