harryscholes

def attr_printer(cls, indentation=0):
    for attr_name in getattr(cls, "__dict__"):
        attr = getattr(cls, attr_name)
        
        print("    " * indentation, attr_name, "=", attr)
        
        if hasattr(attr, "__dict__"):  # recursion
            indentation+=1
            attr_printer(attr, indentation)

harryscholes

import jsonpickle  # pip install jsonpickle
import json

def pprint_obj(obj, max_depth=None):
    """Pretty print all attributes of an object recursively.
    
    Arguments:
        obj (object): object whose attributes are to be printed
        max_depth (int, optional): maximum recursion depth
    """

harryscholes

pip install hide_code
jupyter nbextension install --py hide_code
jupyter nbextension enable --py hide_code
jupyter serverextension enable --py hide_code

harryscholes

import requests, secrets

url = "https://raw.githubusercontent.com/first20hours/google-10000-english/master/google-10000-english.txt"
words = requests.get(url).text.split("\n")


def generate_password(length=4,
                      min_word_length=4,
                      max_word_length=8,
                      as_string=False):

harryscholes

Keybase proof

I hereby claim:

• I am harryscholes on github.
• I am harryscholes (https://keybase.io/harryscholes) on keybase.
• I have a public key ASB46XcHPdiNgGh6EaQhhLHvrpQGAMwzN0FLjDAHulJ65wo

To claim this, I am signing this object:

harryscholes

Why?

Build Tensorflow from source to make use of all supported processor instructions.

Requirements

• git
• brew
• anaconda

harryscholes

# First time
docker run -p 5000:8888 --name tensorflow-udacity -it gcr.io/tensorflow/udacity-assignments:1.0.0

# Subsequently
docker start -ai tensorflow-udacity

harryscholes

###########
## Shell ##
###########

qrsh -verbose -l tmem=1G,gpu=1 -P gpu

echo $CUDA_VISIBLE_DEVICES

source /share/apps/examples/tensorflow-1.4.0.sh

harryscholes

from contextlib import contextmanager
import matplotlib.pyplot as plt


@contextmanager
def easyplot(filename, nrows=1, ncols=1, figsize=(6, 6), *,
             x="", y="", tight_layout=True, savefig=True, **kw):
  
    fig, ax = plt.subplots(nrows, ncols, figsize=figsize, **kw)

harryscholes

module OffsetArrays

export OffsetArray

importall Base

immutable OffsetArray{T,N,A<:AbstractArray} <: AbstractArray{T,N}
    array::A
    offset::NTuple{N,Int}
end