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()