hughdbrown

import os
import os.path
from itertools import tee, izip
from subprocess import Popen, PIPE

BUFSIZE = 16 * 1024 * 1024

def pairwise(iterable):
    "s -> (s0,s1), (s1,s2), (s2, s3), ..."
    a, b = tee(iterable)

hughdbrown

r = r'^rgba\((?P<red>\d+), (?P<green>\d+), (?P<blue>\d+), \d\.\d+\)$'

def max_rgba(color):
    keys = ('red', 'green', 'blue')
    d = {
        k: int(v)
        for k, v in zip(
            keys,
            re.search(r, color).group(*keys)
        )

hughdbrown

#!/usr/bin/env python3
import logging

import requests

SIGNIN_URL = "http://10.0.0.2/sign-in"
AIM_URL = "https://10.0.0.2/aim"

PID = "59ba0a1a100d2b744e4303e7"

hughdbrown

>>> parameters3 = {
...     'g': [100],
...     'h': [200, 201],
...     'i': [300, 301, 302],
... }
>>>
>>> from itertools import product
>>> def _exhaustive_list(parameters):
...     keys, values = list(parameters.keys()), list(parameters.values())
...     return [

hughdbrown

#!/usr/bin/env python
from __future__ import print_function

import os
import os.path
import sys
from csv import DictReader

class DictDiffer(object):
    """

hughdbrown

#!/usr/bin/env python
from hashlib import sha1
import os
import os.path

from flask import (
    Flask,
    send_from_directory,
)

hughdbrown

# From:
# http://machinelearningmastery.com/5-step-life-cycle-long-short-term-memory-models-keras/

# Example of LSTM to learn a sequence
from pandas import DataFrame
from pandas import concat
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import LSTM
# create sequence

hughdbrown

% ls -l /usr/local/cuda/lib64/libcud*
-rw-r--r-- 1 root   root    556000 May 10 13:21 /usr/local/cuda/lib64/libcudadevrt.a
lrwxrwxrwx 1 root   root        16 May 10 13:21 /usr/local/cuda/lib64/libcudart.so -> libcudart.so.8.0
lrwxrwxrwx 1 root   root        19 May 10 13:21 /usr/local/cuda/lib64/libcudart.so.8.0 -> libcudart.so.8.0.61
-rwxr-xr-x 1 root   root    415432 May 10 13:21 /usr/local/cuda/lib64/libcudart.so.8.0.61
-rw-r--r-- 1 root   root    775162 May 10 13:21 /usr/local/cuda/lib64/libcudart_static.a
lrwxrwxrwx 1 ubuntu users       13 Nov  7  2016 /usr/local/cuda/lib64/libcudnn.so -> libcudnn.so.5
lrwxrwxrwx 1 ubuntu users       18 Nov  7  2016 /usr/local/cuda/lib64/libcudnn.so.5 -> libcudnn.so.5.1.10
-rwxr-xr-x 1 ubuntu users 84163560 May 31 16:28 /usr/local/cuda/lib64/libcudnn.so.5.1.10
-rw-r--r-- 1 ubuntu users 70364814 May 31 16:28 /usr/local/cuda/lib64/libcudnn_static.a

hughdbrown

{17-06-01 15:10}lambda-devbox:~ ubuntu% nvidia-debugdump -l
Found 4 NVIDIA devices
        Device ID:              0
        Device name:            Graphics Device   (*PrimaryCard)
        GPU internal ID:        0321017145676

        Device ID:              1
        Device name:            Graphics Device
        GPU internal ID:        0321017095492

hughdbrown

#!/bin/sh
brew install gcc@5
sudo -H pip install --upgrade --force xgboost