23-06-24

패키지 호출 단순 수정

mnist.py

@@ -1,30 +1,28 @@
 # %%
 import os
+
 os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
 
 import tensorflow as tf
+
 tf.random.set_seed(777)  # for reproducibility
 
 import numpy as np
+
 np.random.seed(777)
 
-from tensorflow import keras
-from keras.datasets import mnist
-from keras.models import Sequential
-from keras.layers import Dense, Dropout, Flatten
-from keras.layers import Conv2D, MaxPooling2D
-from keras import backend as K
+import gc
+from datetime import date
 
+from keras import backend as K
+from keras.datasets import mnist
+from keras.layers import Conv2D, Dense, Dropout, Flatten, MaxPooling2D
+from keras.models import Sequential
 # from pso_tf import PSO
 from pso import Optimizer
-# from optimizer import Optimizer
-
-
-from datetime import date
+from tensorflow import keras
 from tqdm import tqdm
 
-import gc
-
 # print(tf.__version__)
 # print(tf.config.list_physical_devices())
 # print(f"Num GPUs Available: {len(tf.config.list_physical_devices('GPU'))}")
@@ -74,12 +72,13 @@ if __name__ == "__main__":
         pso_mnist = Optimizer(
             model,
             loss=loss[0], 
-            n_particles=50,
+            n_particles=75,
             c0=0.35, 
             c1=0.8, 
             w_min=0.7,
             w_max=1.15,
-            negative_swarm=0.25
+            negative_swarm=0.25,
+            momentun_swarm=0.25,
             )
 
         best_score = pso_mnist.fit(
@@ -88,7 +87,7 @@ if __name__ == "__main__":
             epochs=200,
             save=True,
             save_path="./result/mnist", 
-            renewal="acc", 
+            renewal="loss", 
             empirical_balance=False,
             Dispersion=False, 
             check_point=25