kastnerkyle

kastnerkyle

kastnerkyle

from __future__ import division
from random import random
import numpy as np
import pandas as pd

'''
    Use regret-matching algorithm to play Scissors-Rock-Paper.
'''

class RPS:

kastnerkyle

from __future__ import division
from random import random
import numpy as np
import pandas as pd

'''
    Use regret-matching algorithm to play Scissors-Rock-Paper.
'''

class RPS:

kastnerkyle

kastnerkyle

# git clone from https://github.com/tkarras/progressive_growing_of_gans
# download the snapshot from their Google drive
# use the following code in the same directory to generate random faces
import os
import sys
import time
import glob
import shutil
import operator
import theano

kastnerkyle

kastnerkyle

kastnerkyle

import torch
from torch import nn
from torch.autograd import Variable

class AdaptiveSoftmax(nn.Module):
    def __init__(self, input_size, cutoff):
        super().__init__()
        
        self.input_size = input_size
        self.cutoff = cutoff

kastnerkyle

'''
Non-parametric computation of entropy and mutual-information

Adapted by G Varoquaux for code created by R Brette, itself
from several papers (see in the code).

These computations rely on nearest-neighbor statistics
'''
import numpy as np