saitodev

user  nginx;
worker_processes  1;

events {
    worker_connections  1024;
    use epoll;
}

http {
    include       mime.types;

saitodev

C:\cygwin\bin\bash.exe -c "/usr/bin/ssh-agent | /usr/bin/sed -e '/echo/d' | /usr/bin/cut -f 1 -d ';' | /usr/bin/tr '=' ' ' | while read line; do setx.exe $line; done;"

saitodev

shell /bin/bash
escape ^t^t
startup_message off
vbell off
defkanji utf-8
msgwait 1
defscrollback 10000
autodetach on

saitodev

GSSAPIAuthentication no
AddressFamily inet

Compression yes
CompressionLevel 9
ServerAliveInterval 100

ForwardX11 yes
ForwardX11Trusted yes
ForwardAgent yes

saitodev

export PS1="-- \[\033[0;31m\]\u@\h \[\033[1;34m\]\w \[\033[0m\]-- \n> "
 
alias ls='ls -hF --color=tty'
alias rm='rm -i'
alias cp='cp -i'
alias mv='mv -i'
alias less='less -r'                          # raw control characters
alias grep='grep --color'                     # show differences in colourx
alias ll='ls -l -A'                           # long list
alias la='ls -A'                              # all but . and ..

saitodev

#!/bin/bash
# -*- coding: utf-8 -*-

PLAYER_URL='http://radiko.jp/player/swf/player_4.1.0.00.swf'

wget $PLAYER_URL -O player.swf
swfextract -b 14 -o authkey.png player.swf
rm -f player.swf

saitodev

#!/bin/bash

container_id=$1
if [ -z $container_id ]; then
    echo "usage: sudo docker-nsenter <container_id> [args ...]"
    exit 1
fi
target=`docker inspect --format '{{.State.Pid}}' $container_id`
nsenter --mount --uts --ipc --net --pid --target $target ${@:2}

saitodev

#!/bin/bash -eu
# -*- coding: utf-8 -*-

HEADER_DIR=/tmp/tensorflow/include

if [ ! -e $HEADER_DIR ];
then
    mkdir -p $HEADER_DIR
fi

saitodev

from __future__ import print_function

from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data', one_hot=True)

import tensorflow as tf

def import_graph_def():
  with open('trained_graph.pb', 'rb') as f:
    graph_def = tf.GraphDef()

saitodev

from __future__ import print_function

from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data/', one_hot=True)

import tensorflow as tf
from tensorflow.python.framework.graph_util import convert_variables_to_constants

def train_and_save():
  x = tf.placeholder(tf.float32, [None, 784], name='x')