Files
tensorneat-mend/examples/jit_xor.py
2023-06-27 18:47:47 +08:00

29 lines
731 B
Python

import numpy as np
from configs import Configer
from jit_pipeline import Pipeline
xor_inputs = np.array([[0, 0], [0, 1], [1, 0], [1, 1]], dtype=np.float32)
xor_outputs = np.array([[0], [1], [1], [0]], 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)
fitnesses = 4 - np.sum((outs - xor_outputs) ** 2, axis=(1, 2))
return np.array(fitnesses) # returns a list
def main():
config = Configer.load_config("xor.ini")
pipeline = Pipeline(config, seed=6)
nodes, cons = pipeline.auto_run(evaluate)
print(nodes, cons)
if __name__ == '__main__':
main()