huge accelerate: delete recycle new keys

This commit is contained in:
wls2002
2023-05-08 00:02:51 +08:00
parent 64f8eaccaf
commit cf47c5bb38
2 changed files with 13 additions and 29 deletions

View File

@@ -30,11 +30,8 @@ class Pipeline:
self.crossover_func = create_crossover_function(batch=True) self.crossover_func = create_crossover_function(batch=True)
self.generation = 0 self.generation = 0
self.species_controller.speciate(self.pop_nodes, self.pop_connections, self.generation) self.species_controller.speciate(self.pop_nodes, self.pop_connections, self.generation)
self.new_node_keys_pool: List[int] = [max(self.output_idx) + 1]
self.generation_timestamp = time.time() self.generation_timestamp = time.time()
self.best_fitness = float('-inf') self.best_fitness = float('-inf')
@@ -107,24 +104,23 @@ class Pipeline:
# mutate # mutate
mutate_rand_keys = jax.random.split(k2, self.pop_size) mutate_rand_keys = jax.random.split(k2, self.pop_size)
new_node_keys = np.array(self.fetch_new_node_keys()) new_node_keys = np.arange(self.generation * self.pop_size, self.generation * self.pop_size + self.pop_size)
m_npn, m_npc = self.mutate_func(mutate_rand_keys, npn, npc, new_node_keys) # mutate_new_pop_nodes m_npn, m_npc = self.mutate_func(mutate_rand_keys, npn, npc, new_node_keys) # mutate_new_pop_nodes
m_npn, m_npc = jax.device_get(m_npn), jax.device_get(m_npc)
# elitism don't mutate # elitism don't mutate
# (pop_size, ) to (pop_size, 1, 1) # (pop_size, ) to (pop_size, 1, 1)
self.pop_nodes = np.where(elitism_mask[:, None, None], npn, m_npn)
# (pop_size, ) to (pop_size, 1, 1, 1) def aux_function1():
self.pop_connections = np.where(elitism_mask[:, None, None, None], npc, m_npc) nonlocal m_npn, m_npc
m_npn, m_npc = jax.device_get(m_npn), jax.device_get(m_npc)
self.pop_nodes = np.where(elitism_mask[:, None, None], npn, m_npn)
# (pop_size, ) to (pop_size, 1, 1, 1)
self.pop_connections = np.where(elitism_mask[:, None, None, None], npc, m_npc)
# print(pop_analysis(self.pop_nodes, self.pop_connections, self.input_idx, self.output_idx)) # print(pop_analysis(self.pop_nodes, self.pop_connections, self.input_idx, self.output_idx))
# recycle unused node keys aux_function1()
unused = []
for i, nodes in enumerate(self.pop_nodes):
node_keys, key = nodes[:, 0], new_node_keys[i]
if not np.isin(key, node_keys): # the new node key is not used
unused.append(key)
self.new_node_keys_pool = unused + self.new_node_keys_pool
def expand(self): def expand(self):
""" """
@@ -145,18 +141,6 @@ class Pipeline:
for s in self.species_controller.species.values(): for s in self.species_controller.species.values():
s.representative = expand_single(*s.representative, self.N) s.representative = expand_single(*s.representative, self.N)
def fetch_new_node_keys(self):
# if remain unused keys are not enough, create new keys
if len(self.new_node_keys_pool) < self.pop_size:
max_unused_key = max(self.new_node_keys_pool) if self.new_node_keys_pool else -1
new_keys = list(range(max_unused_key + 1, max_unused_key + 1 + 10 * self.pop_size))
self.new_node_keys_pool.extend(new_keys)
# fetch keys from pool
res = self.new_node_keys_pool[:self.pop_size]
self.new_node_keys_pool = self.new_node_keys_pool[self.pop_size:]
return res
def default_analysis(self, fitnesses): def default_analysis(self, fitnesses):
max_f, min_f, mean_f, std_f = max(fitnesses), min(fitnesses), np.mean(fitnesses), np.std(fitnesses) max_f, min_f, mean_f, std_f = max(fitnesses), min(fitnesses), np.mean(fitnesses), np.std(fitnesses)
species_sizes = [len(s.members) for s in self.species_controller.species.values()] species_sizes = [len(s.members) for s in self.species_controller.species.values()]

View File

@@ -23,8 +23,8 @@ def evaluate(forward_func: Callable) -> List[float]:
return fitnesses.tolist() # returns a list return fitnesses.tolist() # returns a list
# @using_cprofile @using_cprofile
@partial(using_cprofile, root_abs_path='/mnt/e/neat-jax/', replace_pattern="/mnt/e/neat-jax/") # @partial(using_cprofile, root_abs_path='/mnt/e/neat-jax/', replace_pattern="/mnt/e/neat-jax/")
def main(): def main():
config = Configer.load_config() config = Configer.load_config()
pipeline = Pipeline(config, seed=11323) pipeline = Pipeline(config, seed=11323)