justanotherminh

import numpy as np
from tensorflow.examples.tutorials.mnist import input_data

mnist = input_data.read_data_sets('MNIST_data', one_hot=True)


def softmax(logits):
    e = np.exp(logits)
    return e / np.expand_dims(e.sum(axis=1), axis=1)

justanotherminh

import time

inv = 0


def mergesort(arr):
    global inv
    if len(arr) <= 1:
        return arr
    else:

justanotherminh

counts = 0


def quicksort(arr):
    global counts
    if len(arr) >= 1:
        counts += len(arr)-1
    if len(arr) <= 1:
        return arr
    else:

justanotherminh

import time
import random
import copy


# j4f
def runtime(func, args):
    now = time.time()
    func(args)
    return time.time() - now

justanotherminh

import time
from collections import deque
import sys
sys.setrecursionlimit(10000)


class Node(object):
    def __init__(self, name):
        self.name = name
        self.explored = False

justanotherminh

import numpy as np
import matplotlib.pyplot as plt
from tensorflow.examples.tutorials.mnist import input_data


def sample_vector(v, w, b, bernoulli=True):
    h = 1 / (1 + np.exp(-(v.dot(w) + b)))
    if bernoulli:
        h = np.random.binomial(1, h)
    return h

justanotherminh

# Sometimes it works, sometimes it doesn't
import numpy as np
import gym


class Net(object):
    def __init__(self, input, output):
        # W = 0.01 * np.random.randn(input, output)
        # b = np.zeros([1, output])  # Random initialization
        W = np.array([[-0.60944746, 0.45539405],

justanotherminh

import numpy as np


def sigmoid(v):
    return 1 / (1 + np.exp(-v))


def one_hot(x):
    N = x.size
    D = x.max() + 1

justanotherminh

    {
        "package": {
            "version": "3.1",
            "division": [
                {
                    "alias": "tx2_64bit",
                    "selected": "1",
                    "name": "Jetson TX2"
                },
                { 

justanotherminh

from fractions import Fraction
import numpy as np


def print_matrix(matrix):
    def tostr(i):
        return str(i) if i.denominator == 1 else '{}\\{}'.format(i.numerator, i.denominator)
    print '\n'.join(['\t'.join([tostr(col) for col in row]) for row in matrix])