jung-geun/PSO
1
0
Fork 0
mirror of https://github.com/jung-geun/PSO.git synced 2025-12-19 20:44:39 +09:00
Code Issues Packages Projects Releases Wiki Activity

23-06-28

Browse Source 
단순 업데이트
This commit is contained in:
jung-geun
2023-06-28 23:29:27 +09:00
parent 983913f2d2
commit 544a818940
7 changed files with 140884 additions and 67 deletions
Download Patch File Download Diff File Expand all files Collapse all files

30
pso/optimizer.py
View File

@@ -12,8 +12,6 @@ from tqdm import tqdm
# import cupy as cp
gpus = tf.config.experimental.list_physical_devices("GPU")
if gpus:
try:
@@ -37,6 +35,8 @@ class Optimizer:
momentun_swarm: float = 0,
):
"""
particle swarm optimization
Args:
model (keras.models): 모델 구조
loss (str): 손실함수
@@ -67,7 +67,8 @@ class Optimizer:
m = keras.models.model_from_json(model.to_json())
init_weights = m.get_weights()
w_, sh_, len_ = self._encode(init_weights)
w_ = np.random.uniform(-1.5, 1.5, len(w_))
w_ = np.random.rand(len(w_)) * 4 - 2
# w_ = np.random.uniform(-1.5, 1.5, len(w_))
m.set_weights(self._decode(w_, sh_, len_))
m.compile(loss=self.loss, optimizer="sgd", metrics=["accuracy"])
self.particles[i] = Particle(m, loss, negative=True if i < negative_swarm * self.n_particles else False, momentun=True if i > self.n_particles * (1 - self.momentun_swarm) else False)
@@ -309,17 +310,23 @@ class Optimizer:
if renewal == "acc":
if score[1] >= self.g_best_score[0]:
self.g_best_score[0] = score[1]
if score[0] <= self.g_best_score[1]:
self.g_best_score[1] = score[0]
self.g_best = self.particles[i].get_best_weights()
if score[1] > self.g_best_score[0]:
self.g_best_score[0] = score[1]
self.g_best = self.particles[i].get_best_weights()
else:
if score[0] < self.g_best_score[1]:
self.g_best_score[1] = score[0]
self.g_best = self.particles[i].get_best_weights()
epochs_pbar.set_description(f"best {self.g_best_score[0]:.4f} | {self.g_best_score[1]:.4f}")
elif renewal == "loss":
if score[0] <= self.g_best_score[1]:
self.g_best_score[1] = score[0]
if score[1] >= self.g_best_score[0]:
self.g_best_score[0] = score[1]
self.g_best = self.particles[i].get_best_weights()
if score[0] < self.g_best_score[1]:
self.g_best_score[1] = score[0]
self.g_best = self.particles[i].get_best_weights()
else:
if score[1] > self.g_best_score[0]:
self.g_best_score[0] = score[1]
self.g_best = self.particles[i].get_best_weights()
epochs_pbar.set_description(f"best {self.g_best_score[0]:.4f} | {self.g_best_score[1]:.4f}")
if score[0] == None:
@@ -420,6 +427,7 @@ class Optimizer:
"empirical_balance": self.empirical_balance,
"Dispersion": self.Dispersion,
"negative_swarm": self.negative_swarm,
"momentun_swarm": self.momentun_swarm,
"renewal": self.renewal,
}

2
pso/particle.py
View File

@@ -114,6 +114,8 @@ class Particle:
self.best_score = score[1]
self.best_weights = self.model.get_weights()
elif renewal == "loss":
if score[0] == 'nan':
score[0] = np.inf
if score[0] < self.best_score:
self.best_score = score[0]
self.best_weights = self.model.get_weights()