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main.py
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main.py
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#!/usr/bin/env python3
# vim: set ft=python fenc=utf-8 tw=72:
# MINML :: Minimal machine learning algorithms
# Copyright (c) 2019-2020, J. A. Corbal
#
# Permission is hereby granted, free of charge, to any person obtaining
# a copy of this software and associated documentation files (the
# “Software”), to deal in the Software without restriction, including
# without limitation the rights to use, copy, modify, merge, publish,
# distribute, sublicense, and/or sell copies of the Software, and to
# permit persons to whom the Software is furnished to do so, subject to
# the following conditions:
#
# The above copyright notice and this permission notice shall be
# included in all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
# IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
# CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
# TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
# SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
from minml import MinAnn
def round_list(float_list):
"""Rounds a list of floats and returns a list of integers."""
return [round(i) for i in float_list]
if __name__ == '__main__':
# Topology: 4 inputs; 4 outputs
# TODO(Optimize). Check best number of hidden layers (3 for now)
net = MinAnn([4, 3, 4])
# Example (random, as an example)
pattern = [
[[True, False, False, 0.35], [False, 1, -1, 0]],
[[True, False, False, 0.00], [False, 1, 1, 1]],
[[True, False, False, 1.00], [False, 1, 1, -1]],
[[False, False, False, 0.35], [True, 1, -1, 0]],
[[False, False, False, 0.00], [True, 1, 1, 1]],
[[False, False, False, 1.00], [True, 1, 1, -1]],
]
# Train the previous values (`pattern`) 8000 times
print("Training...")
net.train(pattern, 8000)
# Echo results
print(round_list(net.feed_forward([1, 0, 0, 0.9])))
print(round_list(net.feed_forward([0, 0, 0, 0.7])))
print(round_list(net.feed_forward([1, 0, 0, 0.5])))
print(round_list(net.feed_forward([0, 0, 0, 0.4])))
print(round_list(net.feed_forward([1, 0, 0, 0.3])))
print(round_list(net.feed_forward([0, 0, 0, 0.1])))
print(round_list(net.feed_forward([1, 0, 0, 0.0])))