xarg

#!/bin/bash
#
#  tc uses the following units when passed as a parameter.
#  kbps: Kilobytes per second
#  mbps: Megabytes per second
#  kbit: Kilobits per second
#  mbit: Megabits per second
#  bps: Bytes per second
#       Amounts of data can be specified in:
#       kb or k: Kilobytes

mailletf

# Mostly taken from: http://nbviewer.ipython.org/github/bmcfee/librosa/blob/master/examples/LibROSA%20demo.ipynb

import librosa
import matplotlib.pyplot as plt

# Load sound file
y, sr = librosa.load("filename.mp3")

# Let's make and display a mel-scaled power (energy-squared) spectrogram
S = librosa.feature.melspectrogram(y, sr=sr, n_mels=128)

jarutis

## install Catalyst proprietary
sudo ntfsfix /dev/sda2
sudo cp /etc/X11/xorg.conf /etc/X11/xorg.conf.BAK
sudo apt-get remove --purge fglrx*
sudo apt-get install linux-headers-generic
sudo apt-get install fglrx xvba-va-driver libva-glx1 libva-egl1 vainfo 
sudo amdconfig --initial

## install build essentials
sudo apt-get install cmake

kevinkindom

Python Socket 编程详细介绍

Python 提供了两个基本的 socket 模块：

• Socket 它提供了标准的BSD Socket API。
• SocketServer 它提供了服务器重心，可以简化网络服务器的开发。

下面讲解下 Socket模块功能。

Socket 类型

Uchean

Get ClamAV running on Mac OS X (using Homebrew)

The easiest way to get the ClamAV package is using Homebrew

$ brew install clamav

Before trying to start the clamd process, you'll need a copy of the ClamAV databases.

Create a freshclam.conf file and configure as so

ernestum

import numpy as np
from scipy.ndimage.interpolation import map_coordinates
from scipy.ndimage.filters import gaussian_filter

def elastic_transform(image, alpha, sigma, random_state=None):
    """Elastic deformation of images as described in [Simard2003]_.
    .. [Simard2003] Simard, Steinkraus and Platt, "Best Practices for
       Convolutional Neural Networks applied to Visual Document Analysis", in
       Proc. of the International Conference on Document Analysis and
       Recognition, 2003.

ryerh

注意：本文内容适用于 Tmux 2.3 及以上的版本，但是绝大部分的特性低版本也都适用，鼠标支持、VI 模式、插件管理在低版本可能会与本文不兼容。

Tmux 快捷键 & 速查表 & 简明教程

启动新会话：

tmux [new -s 会话名 -n 窗口名]

恢复会话：

udibr

# variation to https://github.com/ryankiros/skip-thoughts/blob/master/decoding/search.py

def keras_rnn_predict(samples, empty=empty, rnn_model=model, maxlen=maxlen):
    """for every sample, calculate probability for every possible label
    you need to supply your RNN model and maxlen - the length of sequences it can handle
    """
    data = sequence.pad_sequences(samples, maxlen=maxlen, value=empty)
    return rnn_model.predict(data, verbose=0)

def beamsearch(predict=keras_rnn_predict,

amchercashin

/usr/local/cuda/lib64

jacky860226

#define F(x) (x)/3+((x)%3==1?0:tb)
#define G(x) (x)<tb?(x)*3+1:((x)-tb)*3+2
int wa[3*maxn+5],wb[3*maxn+5],wv[3*maxn+5],c[maxn+5];
inline bool c0(int *s,int a,int b){
	return s[a]==s[b]&&s[a+1]==s[b+1]&&s[a+2]==s[b+2];
}
inline bool c12(int k,int *s,int a,int b){
	if(k==2)return s[a]<s[b]||s[a]==s[b]&&c12(1,s,a+1,b+1);
	else return s[a]<s[b]||s[a]==s[b]&&wv[a+1]<wv[b+1];
}