Files
tensorneat-mend/examples/xor.py

36 lines
937 B
Python

from typing import Callable, List
from functools import partial
import jax
import numpy as np
from utils import Configer
from algorithms.neat import Pipeline
from time_utils import using_cprofile
xor_inputs = np.array([[0, 0], [0, 1], [1, 0], [1, 1]])
xor_outputs = np.array([[0], [1], [1], [0]])
def evaluate(forward_func: Callable) -> List[float]:
"""
:param forward_func: (4: batch, 2: input size) -> (pop_size, 4: batch, 1: output size)
:return:
"""
outs = forward_func(xor_inputs)
outs = jax.device_get(outs)
fitnesses = 4 - np.sum((outs - xor_outputs) ** 2, axis=(1, 2))
return fitnesses.tolist() # returns a list
@using_cprofile
# @partial(using_cprofile, root_abs_path='/mnt/e/neat-jax/', replace_pattern="/mnt/e/neat-jax/")
def main():
config = Configer.load_config()
pipeline = Pipeline(config, seed=11323)
pipeline.auto_run(evaluate)
if __name__ == '__main__':
main()