IlyaOrson

# -*- coding: utf-8 -*-
import networkx as nx
import graph_tool as gt

def get_prop_type(value, key=None):
    """
    Performs typing and value conversion for the graph_tool PropertyMap class.
    If a key is provided, it also ensures the key is in a format that can be
    used with the PropertyMap. Returns a tuple, (type name, value, key)
    """

IlyaOrson

IlyaOrson

DiffEqFlux.jl (Julia) vs Jax on an Epidemic Model

The Jax developers optimized a differential equation benchmark in this issue which used DiffEqFlux.jl as a performance baseline. The Julia code from there was updated to include some standard performance tricks and is the benchmark code here. Thus both codes have been optimized by the library developers.

Results

Forward Pass

IlyaOrson

# may go to startup file to make it always available
# https://github.com/MasonProtter/ReplMaker.jl#creating-a-repl-mode-at-startup-time
using ReplMaker
function powershell_command(s)
    # adapted from https://github.com/JuliaLang/julia/blob/7a3fff1ea76b62b7681dbed5cc2dee43c64d9a51/base/client.jl#L45
    args = String.(split(s))
    if args[1] == "cd"
        new_oldpwd = pwd()
        if length(args) > 2
            throw(ArgumentError("cd method only takes one argument"))

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"""
Generate table assignments for 'n' customers,
according to a Chinese Restaurant Process with dispersion parameter 'α'
Returns an array of integer table assignments
"""
function crp(n, α)

    @assert n > 0
    table_assignments = zeros(Int, n)
    table_assignments[1] = 1 # first customer sits at table 1

IlyaOrson

border: no
height: 600
license: gpl-3.0

IlyaOrson

"""Provides methods around syncing and usage of AWS s3 buckets as local caches rather than individually
downloading every file"""

import os
import shutil
import boto3 as boto
import multiprocessing
import copy
import hashlib

IlyaOrson

#Set up data partition
sudo mkdir /data
sudo chmod 777 /data
sudo "echo /dev/xvdb   /data	ext4	rw,user,exec,comment=cloudconfig	0	2 >> /etc/fstab"
sudo mount /data

#Install build environment
sudo sed -i "s/enabled=0/enabled=1" /etc/yum.repos.d/epel.epo
sudo yum -y update
sudo yum -y upgrade

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""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward

IlyaOrson

#!/usr/bin/env python

class Vertex:
    def __init__(self, value):
        self.value = value
        self.edges = {}
    def degree(self):
        return len(self.edges)
    def __str__(self):
        return str(self.value)