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create function_factory.py, use to manage functions

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wls2002
2023-05-09 01:49:43 +08:00
parent ee6bb01eff
commit f63a0c447b
7 changed files with 231 additions and 18 deletions
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15
algorithms/neat/pipeline.py
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@@ -2,13 +2,13 @@ from typing import List, Union, Tuple, Callable
import time
import jax
import jax.numpy as jnp
import numpy as np
from .species import SpeciesController
from .genome import expand, expand_single
from .genome import create_initialize_function, create_mutate_function, create_forward_function, \
create_distance_function, create_crossover_function
from .function_factory import FunctionFactory
class Pipeline:
@@ -17,17 +17,18 @@ 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.function_factory = FunctionFactory(config)
self.N = config.basic.init_maximum_nodes
self.expand_coe = config.basic.expands_coe
self.pop_size = config.neat.population.pop_size
self.species_controller = SpeciesController(config)
self.initialize_func = create_initialize_function(config)
self.initialize_func = self.function_factory.create_initialize()
self.pop_nodes, self.pop_connections, self.input_idx, self.output_idx = self.initialize_func()
self.compile_functions(debug=True)
@@ -36,6 +37,7 @@ class Pipeline:
self.species_controller.init_speciate(self.pop_nodes, self.pop_connections)
self.best_fitness = float('-inf')
self.generation_timestamp = time.time()
def ask(self, batch: bool):
"""
@@ -140,10 +142,9 @@ class Pipeline:
self.compile_functions(debug=True)
def compile_functions(self, debug=False):
self.mutate_func = create_mutate_function(self.N, self.config, batch=True, debug=debug)
self.crossover_func = create_crossover_function(self.N, self.config, batch=True, debug=debug)
self.o2o_distance = create_distance_function(self.N, self.config, type='o2o', debug=debug)
self.o2m_distance = create_distance_function(self.N, self.config, type='o2m', debug=debug)
self.mutate_func = self.function_factory.create_mutate(self.N)
self.crossover_func = self.function_factory.create_crossover(self.N)
self.o2o_distance, self.o2m_distance = self.function_factory.create_distance(self.N)
def default_analysis(self, fitnesses):
max_f, min_f, mean_f, std_f = max(fitnesses), min(fitnesses), np.mean(fitnesses), np.std(fitnesses)