Files
tensorneat-mend/examples/xor3d.py
2023-07-02 22:15:26 +08:00

32 lines
842 B
Python

import jax
import numpy as np
from configs import Configer
from pipeline import Pipeline
xor_inputs = np.array([[0, 0, 0], [0, 0, 1], [0, 1, 0], [0, 1, 1], [1, 0, 0], [1, 0, 1], [1, 1, 0], [1, 1, 1]], dtype=np.float32)
xor_outputs = np.array([[0], [1], [1], [0], [1], [0], [0], [1]], dtype=np.float32)
def evaluate(forward_func):
"""
: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 = 8 - np.sum((outs - xor_outputs) ** 2, axis=(1, 2))
return fitnesses
def main():
config = Configer.load_config("xor3d.ini")
pipeline = Pipeline(config)
nodes, cons = pipeline.auto_run(evaluate)
# g = Genome(nodes, cons, config)
# print(g)
if __name__ == '__main__':
main()