코드 변경 내용을 요약한 커밋 메시지입니다.

test/mnist.py

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+# %%
+import os
+import sys
+
+from pso import optimizer
+
+import tensorflow as tf
+from keras.datasets import mnist
+from keras.layers import Conv2D, Dense, Dropout, Flatten, MaxPooling2D
+from keras.models import Sequential
+
+
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
+
+
+def get_data():
+    (x_train, y_train), (x_test, y_test) = mnist.load_data()
+
+    x_train, x_test = x_train / 255.0, x_test / 255.0
+    x_train = x_train.reshape((60000, 28, 28, 1))
+    x_test = x_test.reshape((10000, 28, 28, 1))
+
+    y_train, y_test = tf.one_hot(y_train, 10), tf.one_hot(y_test, 10)
+
+    x_train, x_test = tf.convert_to_tensor(x_train), tf.convert_to_tensor(x_test)
+    y_train, y_test = tf.convert_to_tensor(y_train), tf.convert_to_tensor(y_test)
+
+    print(f"x_train : {x_train[0].shape} | y_train : {y_train[0].shape}")
+    print(f"x_test : {x_test[0].shape} | y_test : {y_test[0].shape}")
+
+    return x_train, y_train, x_test, y_test
+
+
+def make_model():
+    model = Sequential()
+    model.add(
+        Conv2D(32, kernel_size=(5, 5), activation="relu", input_shape=(28, 28, 1))
+    )
+    model.add(MaxPooling2D(pool_size=(2, 2)))
+    model.add(Dropout(0.5))
+    model.add(Conv2D(64, kernel_size=(3, 3), activation="relu"))
+    model.add(MaxPooling2D(pool_size=(2, 2)))
+    model.add(Flatten())
+    model.add(Dropout(0.5))
+    model.add(Dense(256, activation="relu"))
+    model.add(Dense(128, activation="relu"))
+    model.add(Dense(10, activation="softmax"))
+
+    return model
+
+
+# %%
+model = make_model()
+x_train, y_train, x_test, y_test = get_data()
+
+
+pso_mnist = optimizer(
+    model,
+    loss="categorical_crossentropy",
+    n_particles=200,
+    c0=0.7,
+    c1=0.4,
+    w_min=0.1,
+    w_max=0.9,
+    negative_swarm=0.0,
+    mutation_swarm=0.05,
+    convergence_reset=True,
+    convergence_reset_patience=10,
+    convergence_reset_monitor="loss",
+    convergence_reset_min_delta=0.005,
+)
+
+best_score = pso_mnist.fit(
+    x_train,
+    y_train,
+    epochs=1000,
+    save_info=True,
+    log=2,
+    log_name="mnist",
+    renewal="loss",
+    check_point=25,
+    batch_size=5000,
+    validate_data=(x_test, y_test),
+)
+
+print("Done!")
+
+sys.exit(0)