mirror of
https://github.com/jung-geun/PSO.git
synced 2025-12-19 20:44:39 +09:00
82 lines
1.8 KiB
Python
82 lines
1.8 KiB
Python
import os
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import sys
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import pandas as pd
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import tensorflow as tf
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from sklearn.datasets import load_digits
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from sklearn.model_selection import train_test_split
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from tensorflow import keras
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from tensorflow.keras import layers
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from tensorflow.keras.layers import Dense
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from tensorflow.keras.models import Sequential
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from tensorflow.keras.utils import to_categorical
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gpus = tf.config.experimental.list_physical_devices("GPU")
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if gpus:
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try:
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tf.config.experimental.set_memory_growth(gpus[0], True)
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except RuntimeError as r:
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print(r)
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os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
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def make_model():
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model = Sequential()
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model.add(Dense(12, input_dim=64, activation="relu"))
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model.add(Dense(12, activation="relu"))
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model.add(Dense(10, activation="softmax"))
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return model
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def get_data():
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digits = load_digits()
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X = digits.data
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y = digits.target
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x = X.astype("float32")
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y_class = to_categorical(y)
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x_train, x_test, y_train, y_test = train_test_split(
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x, y_class, test_size=0.2, random_state=42, shuffle=True
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)
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return x_train, x_test, y_train, y_test
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if __name__ == "__main__":
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model = make_model()
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x_train, x_test, y_train, y_test = get_data()
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callbacks = [
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tf.keras.callbacks.EarlyStopping(
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monitor="val_loss", patience=10, restore_best_weights=True
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)
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]
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print(x_train.shape, y_train.shape)
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model.compile(
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optimizer="adam",
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loss="categorical_crossentropy",
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metrics=["accuracy", "mse"],
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)
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print(model.summary())
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history = model.fit(
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x_train,
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y_train,
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epochs=500,
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batch_size=32,
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verbose=1,
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validation_data=(x_test, y_test),
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callbacks=callbacks,
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)
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print("Done!")
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sys.exit(0)
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