53 lines
1.6 KiB
Python
53 lines
1.6 KiB
Python
|
|
import numpy as np
|
|
import jax
|
|
from utils import Configer
|
|
from algorithms.neat import Pipeline
|
|
from time_utils import using_cprofile
|
|
from algorithms.neat.function_factory import FunctionFactory
|
|
from problems import EnhanceLogic
|
|
import time
|
|
|
|
|
|
def evaluate(problem, func):
|
|
outs = func(problem.inputs)
|
|
outs = jax.device_get(outs)
|
|
fitnesses = -np.mean((problem.outputs - outs) ** 2, axis=(1, 2))
|
|
return fitnesses
|
|
|
|
|
|
def main():
|
|
config = Configer.load_config()
|
|
problem = EnhanceLogic("xor", n=3)
|
|
problem.refactor_config(config)
|
|
|
|
evaluate_func = lambda func: evaluate(problem, func)
|
|
|
|
for p in [100, 200, 500, 1000, 2000, 5000, 10000, 20000]:
|
|
config.neat.population.pop_size = p
|
|
tic = time.time()
|
|
function_factory = FunctionFactory(config)
|
|
print(f"running: {p}")
|
|
|
|
pipeline = Pipeline(config, function_factory, seed=2)
|
|
pipeline.auto_run(evaluate_func)
|
|
|
|
total_time = time.time() - tic
|
|
evaluate_time = pipeline.evaluate_time
|
|
total_it = pipeline.generation
|
|
print(f"total time: {total_time:.2f}s, evaluate time: {evaluate_time:.2f}s, total_it: {total_it}")
|
|
|
|
with open("2060_log2", "ab") as f:
|
|
f.write \
|
|
(f"{p}, total time: {total_time:.2f}s, compile time: {function_factory.compile_time:.2f}s, total_it: {total_it}\n".encode
|
|
("utf-8"))
|
|
f.write(f"{str(pipeline.generation_time_list)}\n".encode("utf-8"))
|
|
|
|
compile_time = function_factory.compile_time
|
|
|
|
print("total_compile_time:", compile_time)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
main()
|