miku

#!/usr/bin/env bash
# mostly from http://word.bitly.com/post/31921713978/static-analysis
function cfmt {
  if [[ $# -ne 1 ]]; then
    echo "Usage: cfmt <file>"
  else
    astyle \
      --style=1tbs \
      --lineend=linux \
      --convert-tabs \

miku

   model_G = nn.Sequential()
   model_G:add(nn.JoinTable(2, 2))
   model_G:add(cudnn.SpatialConvolutionUpsample(3+1, 64, 7, 7, 1, 1)):add(cudnn.ReLU(true))
   model_G:add(nn.SpatialBatchNormalization(64, nil, nil, false))
   model_G:add(cudnn.SpatialConvolutionUpsample(64, 368, 7, 7, 1, 4)):add(cudnn.ReLU(true))
   model_G:add(nn.SpatialBatchNormalization(368, nil, nil, false))
   model_G:add(nn.SpatialDropout(0.5))
   model_G:add(cudnn.SpatialConvolutionUpsample(368, 128, 7, 7, 1, 4)):add(cudnn.ReLU(true))
   model_G:add(nn.SpatialBatchNormalization(128, nil, nil, false))
   model_G:add(nn.FeatureLPPooling(2,2,2,true))

miku

Do the whole thing:

PYTHONPATH='.' luigi --module small Small --local-scheduler

miku

#!/usr/bin/env python
from sys import stdin, stdout
import csv

rdr = csv.reader(stdin, delimiter='\t')
wrt = csv.writer(stdout, delimiter='\t')

vals = []
rows = []
for row in rdr:

miku

  ## ngram following http://tidytextmining.com/ngrams.html
    library(dplyr)
    library(tidytext)
    library(tidyr)

    # load manually downloaded web of science data dump
    tt <- jsonlite::stream_in(file("data/wos_total.json"), verbose = FALSE) %>% 
      filter(!is.na(AB))

miku

Install

Either copy the aliases from the .gitconfig or run the commands in add-pr-alias.sh

Usage

Easily checkout local copies of pull requests from remotes:

• git pr 4 - creates local branch pr/4 from the github upstream(if it exists) or origin remote and checks it out
• git pr 4 someremote - creates local branch pr/4 from someremote remote and checks it out

miku

Latency Comparison Numbers
--------------------------
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

miku

package main

import (
	"io"
	"log"
	"mime/multipart"
	"net/http"
	"os"
	"path/filepath"
	"runtime"

miku

package main

import (
	"bufio"
	"fmt"
	"io"
	"io/ioutil"
	"log"
	"net/http"
	"sync"

miku

// Pipe creates a synchronous in-memory pipe.
// It can be used to connect code expecting an io.Reader
// with code expecting an io.Writer.
// Reads on one end are matched with writes on the other,
// copying data directly between the two; there is no internal buffering.
// It is safe to call Read and Write in parallel with each other or with
// Close. Close will complete once pending I/O is done. Parallel calls to
// Read, and parallel calls to Write, are also safe:
// the individual calls will be gated sequentially.