23-07-21

pypi 0.1.4 업데이트
keras 의 메모리 누수를 어느정도 해결했으나 아직 완벽히 해결이 되지 않음
입력 데이터를 tensor 형태로 변환해주어 넣는 방식으로 전환

pso/__init__.py

@@ -1,7 +1,7 @@
 from .optimizer import Optimizer
 from .particle import Particle
 
-__version__ = "0.1.3"
+__version__ = "0.1.4"
 
 __all__ = [
     "Optimizer",

pso/optimizer.py

@@ -38,6 +38,7 @@ class Optimizer:
         mutation_swarm: float = 0,
         np_seed: int = None,
         tf_seed: int = None,
+        random_state: tuple = None,
         particle_min: float = -5,
         particle_max: float = 5,
     ):
@@ -66,6 +67,9 @@ class Optimizer:
 
         self.random_state = np.random.get_state()
 
+        if random_state is not None:
+            np.random.set_state(random_state)
+
         self.model = model  # 모델 구조
         self.loss = loss  # 손실함수
         self.n_particles = n_particles  # 파티클 개수
@@ -113,6 +117,8 @@ class Optimizer:
         print(f"mutation swarm : {mutation_swarm * 100}%")
 
         gc.collect()
+        tf.keras.backend.reset_uids()
+        tf.keras.backend.clear_session()
 
     def __del__(self):
         del self.model
@@ -129,6 +135,8 @@ class Optimizer:
         del self.g_best_
         del self.avg_score
         gc.collect()
+        tf.keras.backend.reset_uids()
+        tf.keras.backend.clear_session()
 
     def _encode(self, weights):
         """
@@ -304,7 +312,8 @@ class Optimizer:
                     tf.summary.scalar("accuracy", local_score[1], step=0)
             del local_score
             gc.collect()
-
+            tf.keras.backend.reset_uids()
+            tf.keras.backend.clear_session()
         print(
             f"initial g_best_score : {self.g_best_score[0] if self.renewal == 'acc' else self.g_best_score[1]}"
         )
@@ -454,7 +463,9 @@ class Optimizer:
                                 f.write(", ")
                             else:
                                 f.write("\n")
-
+                    # gc.collect()
+                    # tf.keras.backend.reset_uids()
+                    # tf.keras.backend.clear_session()
                 part_pbar.refresh()
 
                 if check_point is not None:
@@ -463,6 +474,8 @@ class Optimizer:
                         self._check_point_save(f"./{save_path}/{self.day}/ckpt-{epoch}")
 
                 gc.collect()
+                tf.keras.backend.reset_uids()
+                tf.keras.backend.clear_session()
 
         except KeyboardInterrupt:
             print("Ctrl + C : Stop Training")

pso/particle.py

@@ -1,6 +1,7 @@
 import gc
 
 import numpy as np
+import tensorflow as tf
 from tensorflow import keras
 
 
@@ -37,7 +38,6 @@ class Particle:
 
         del i_w_, s_, l_
         del init_weights
-        gc.collect()
 
     def __del__(self):
         del self.model
@@ -46,7 +46,6 @@ class Particle:
         del self.negative
         del self.best_score
         del self.best_weights
-        gc.collect()
 
     def _encode(self, weights: list):
         """
@@ -109,7 +108,7 @@ class Particle:
             (float): 점수
         """
         self.model.compile(loss=self.loss, optimizer="sgd", metrics=["accuracy"])
-        score = self.model.evaluate(x, y, verbose=0)
+        score = self.model.evaluate(x, y, verbose=0, use_multiprocessing=True)
         if renewal == "acc":
             if score[1] > self.best_score:
                 self.best_score = score[1]
@@ -221,26 +220,6 @@ class Particle:
         del encode_w, w_sh, w_len
         del encode_v, v_sh, v_len
 
-    def f(self, x, y, weights):
-        """
-        EBPSO의 목적함수(예상)
-
-        Args:
-            x (list): 입력 데이터
-            y (list): 출력 데이터
-            weights (list): 가중치
-
-        Returns:
-            float: 목적함수 값
-        """
-        self.model.set_weights(weights)
-        score = self.model.evaluate(x, y, verbose=0)[1]
-
-        if score > 0:
-            return 1 / (1 + score)
-        else:
-            return 1 + np.abs(score)
-
     def step(self, x, y, local_rate, global_rate, w, g_best, renewal: str = "acc"):
         """
         파티클의 한 스텝을 진행합니다.