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optimize function reproduce for time usage

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This commit is contained in:
wls2002
2023-05-08 16:28:13 +08:00
parent dde338696f
commit 8653f49826
2 changed files with 5 additions and 8 deletions
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5
algorithms/neat/pipeline.py
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@@ -2,7 +2,6 @@ from typing import List, Union, Tuple, Callable
import time
import jax
import jax.numpy as jnp
import numpy as np
from .species import SpeciesController
@@ -19,6 +18,7 @@ class Pipeline:
def __init__(self, config, seed=42):
self.generation_timestamp = time.time()
self.randkey = jax.random.PRNGKey(seed)
np.random.seed(seed)
self.config = config
self.N = config.basic.init_maximum_nodes
@@ -34,9 +34,6 @@ class Pipeline:
self.generation = 0
self.species_controller.init_speciate(self.pop_nodes, self.pop_connections)
# self.species_controller.speciate(self.pop_nodes, self.pop_connections,
# self.generation, self.o2o_distance, self.o2m_distance)
self.best_fitness = float('-inf')
def ask(self, batch: bool):

8
algorithms/neat/species.py
View File

@@ -239,7 +239,9 @@ class SpeciesController:
self.species = {}
# int -> idx in the pop_nodes, pop_connections of elitism
# (int, int) -> the father and mother idx to be crossover
crossover_pair: List[Union[int, Tuple[int, int]]] = []
for spawn, s in zip(spawn_amounts, remaining_species):
assert spawn >= self.genome_elitism
@@ -264,10 +266,8 @@ class SpeciesController:
# only use good genomes to crossover
sorted_members = sorted_members[:repro_cutoff]
# Randomly choose parents and produce the number of offspring allotted to the species.
for _ in range(spawn):
# allow to replace, for the case that the species only has one genome
c1, c2 = np.random.choice(len(sorted_members), size=2, replace=True)
list_idx1, list_idx2 = np.random.choice(len(sorted_members), size=(2, spawn), replace=True)
for c1, c2 in zip(list_idx1, list_idx2):
idx1, fitness1 = sorted_members[c1], sorted_fitnesses[c1]
idx2, fitness2 = sorted_members[c2], sorted_fitnesses[c2]
if fitness1 >= fitness2: