fizzbuzz.py

"""
FizzBuzz is the following problem:

For each of numbers 1 to 100:
* if the number is divisible by 3, print "fizz"
* if the number is divisible by 3, print "buzz"
* if the number is divisible by 15, print "fizzbuzz"
* otherwise, print the number

The following program gives more or less correct results after 10000 epochs
"""

from typing import List
import numpy as np
from maznet.train import train
from maznet.nn import NeuralNet
from maznet.layers import Linear, Tanh
from maznet.optim import SGD


def fizz_buzz_encode(x: int) -> List[int]:
    if x % 15 == 0:
        return [0, 0, 0, 1]
    elif x % 5 == 0:
        return [0, 0, 1, 0]
    elif x % 3 == 0:
        return [0, 1, 0, 0]
    else:
        return [1, 0, 0, 0]


def binary_encode(x: int) -> List[int]:
    """
    10 digit binary encoding of x
    """
    return [x >> i & 1 for i in range(10)]


inputs = np.array([binary_encode(x) for x in range(101, 1024)])

targets = np.array([fizz_buzz_encode(x) for x in range(101, 1024)])

net = NeuralNet(
    [
        Linear(input_size=10, output_size=50),
        Tanh(),
        Linear(input_size=50, output_size=4),
    ]
)

train(net, inputs, targets, num_epochs=10000, optimizer=SGD(lr=0.001))

for x in range(1, 101):
    predicted = net.forward(binary_encode(x))
    predicted_idx = np.argmax(predicted)
    actual_idx = np.argmax(fizz_buzz_encode(x))
    labels = [str(x), "fizz", "buzz", "fizzbuzz"]
    print(x, labels[predicted_idx], labels[actual_idx])