start new:
tmux
start new with session name:
tmux new -s myname
// by alex evans, 2011. released into the public domain. | |
// based on a first ever reading of the png spec, it occurs to me that a minimal png encoder should be quite simple. | |
// this is a first stab - may be buggy! the only external dependency is zlib and some basic typedefs (u32, u8) | |
// | |
// VERSION 0.02! now using zlib's crc rather than my own, and avoiding a memcpy and memory scribbler in the old one | |
// by passing the zero byte at the start of the scanline to zlib first, then the original scanline in place. WIN! | |
// | |
// more context at http://altdevblogaday.org/2011/04/06/a-smaller-jpg-encoder/. | |
// | |
// follow me on twitter @mmalex http://twitter.com/mmalex |
$ git branch -r --merged | | |
grep origin | | |
grep -v '>' | | |
grep -v master | | |
xargs -L1 | | |
awk '{split($0,a,"/"); print a[2]}' | | |
xargs git push origin --delete |
Latency Comparison Numbers (~2012) | |
---------------------------------- | |
L1 cache reference 0.5 ns | |
Branch mispredict 5 ns | |
L2 cache reference 7 ns 14x L1 cache | |
Mutex lock/unlock 25 ns | |
Main memory reference 100 ns 20x L2 cache, 200x L1 cache | |
Compress 1K bytes with Zippy 3,000 ns 3 us | |
Send 1K bytes over 1 Gbps network 10,000 ns 10 us | |
Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD |
#!/bin/python | |
import os | |
from flask import Flask, Response, request, abort, render_template_string, send_from_directory | |
import Image | |
import StringIO | |
app = Flask(__name__) | |
WIDTH = 1000 |
#!/usr/bin/env python3 | |
# -*- coding: utf-8 -*- | |
""" | |
Memory-aware LRU Cache function decorator | |
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | |
A modification of the builtin ``functools.lru_cache`` decorator that takes an | |
additional keyword argument, ``use_memory_up_to``. The cache is considered full | |
if there are fewer than ``use_memory_up_to`` bytes of memory available. |
package org.paulbetts.shroom.core; | |
import android.os.AsyncTask; | |
import com.squareup.okhttp.*; | |
import java.io.IOException; | |
import java.io.InputStream; | |
import java.io.UnsupportedEncodingException; | |
import java.util.Arrays; |
##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman
""" | |
A simple FiveThirtyEight palette for Seaborn plots. | |
""" | |
import seaborn as sns | |
import matplotlib.pyplot as plt | |
five_thirty_eight = [ | |
"#30a2da", | |
"#fc4f30", |