zmonoid

def insert_sort(A, reverse=False):
    for j in range(1, len(A)):
        key = A[j]
        i = j - 1


        # Insert A[j] to sorted sequence of A[:j]
        if reverse:

zmonoid

import threading
import queue
import time


class BackgroundGenerator(threading.Thread):
    def __init__(self, generator,max_prefetch = 100):
        threading.Thread.__init__(self)
        self.queue = queue.Queue(max_prefetch)

zmonoid

import asyncio

# Borrowed from http://curio.readthedocs.org/en/latest/tutorial.html.
async def countdown(number, n):
    while n > 0:
        print('T-minus', n, '({})'.format(number))
        yield from asyncio.sleep(1)
        n -= 1

loop = asyncio.get_event_loop()

zmonoid

import numpy as np
import matplotlib.pyplot as plt
import torch
class ValueMeter:
    def __init__(self):
        self.reset()

    def add(self, value):
        self.values.append(value)

zmonoid

#! /usr/bin/env python
# -*- coding: utf-8 -*-
# vim:fenc=utf-8
#
# Copyright © 2018 bzhou <bzhou@server2>
#
# Distributed under terms of the MIT license.

"""
mpirun -c 64 --hostfile hosts.txt python ~/cloud/es_walker.py

zmonoid

def find_prime_till(d):
    assert d > 10
    x = [True] * (d+1)
    x[0] = False
    x[1] = False
    last_prime = 2
    while True:
        k = last_prime*2
        while k < d+1:
            x[k] = False

zmonoid

import numpy as np

import torch
import torch.nn as nn
import torch.utils.data as data
from torch.autograd import Variable

class BinaryData(data.Dataset):

    def __init__(self):

zmonoid

"""
Create the tfrecord files for a dataset.

A lot of this code comes from the tensorflow inception example, so here is their license:

# Copyright 2016 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at

zmonoid

import tensorflow as tf
import numpy as np
from nets.nets_factory import get_network_fn
from preprocessing.preprocessing_factory import get_preprocessing
import glob

class Config:
    batch_size = 32
    num_epoch = 1
    name = 'resnet_v2_50'

zmonoid

"""
put the file under slim folder like: models/research/slim/classify_single_image.py
save checkpoint files under slim/checkpoints/*.ckpt
save class id to label text file like slim/imagenet1000_clsid_to_human.txt, download from https://gist.github.com/yrevar/942d3a0ac09ec9e5eb3a
put test images *.jpg under slim
run it!
"""