Files
tensorneat-mend/examples/xor.py
2023-05-10 19:30:12 +08:00

37 lines
1.0 KiB
Python

from functools import partial
from utils import Configer
from algorithms.neat import Pipeline
from time_utils import using_cprofile
from problems import Sin, Xor
# xor_inputs = np.array([[0, 0], [0, 1], [1, 0], [1, 1]], dtype=np.float32)
# 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()
# problem = Xor()
problem = Sin()
problem.refactor_config(config)
pipeline = Pipeline(config, seed=11454)
pipeline.auto_run(problem.evaluate)
if __name__ == '__main__':
main()