MattChanTK

'''
--------------------------------------------------
Retrieve and process the training and testing data
--------------------------------------------------
'''
# Ensure we always get the same amount of randomness
np.random.seed(0)

# Define the data dimensions
image_shape = (1, 28, 28)

MattChanTK

'''
-----------------------------------------------------
Functions to load or download MNIST images and unpack
into training and testing sets.
-----------------------------------------------------
'''
# loading data from local path if possible. Otherwise download from online sources
def load_or_download_mnist_files(filename, num_samples, local_data_dir):

    if (local_data_dir):

MattChanTK

import gzip
import os
import struct
import numpy as np

try:
    from urllib.request import urlretrieve
except ImportError:
    from urllib import urlretrieve

MattChanTK

import gym
import numpy as np
import random
import math
from time import sleep


## Initialize the "Cart-Pole" environment
env = gym.make('CartPole-v0')

MattChanTK

import gym
import numpy as np
import random
import math
from time import sleep

## Initialize the "Cart-Pole" environment
env = gym.make('CartPole-v0')

## Defining the environment related constants

MattChanTK

import gym
import numpy as np
import random
import math
from time import sleep

## Initialize the "Cart-Pole" environment
env = gym.make('CartPole-v0')

## Defining the environment related constants