mirror of
https://github.com/jung-geun/PSO.git
synced 2025-12-20 04:50:45 +09:00
56 lines
1.5 KiB
Python
56 lines
1.5 KiB
Python
import os
|
|
|
|
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
|
|
|
|
import tensorflow as tf
|
|
|
|
gpus = tf.config.experimental.list_physical_devices("GPU")
|
|
if gpus:
|
|
try:
|
|
# tf.config.experimental.set_visible_devices(gpus[0], "GPU")
|
|
tf.config.experimental.set_memory_growth(gpus[0], True)
|
|
except RuntimeError as e:
|
|
print(e)
|
|
|
|
from sklearn.datasets import load_iris
|
|
from sklearn.model_selection import train_test_split
|
|
from tensorflow import keras
|
|
from tensorflow.keras import layers
|
|
from tensorflow.keras.models import Sequential
|
|
|
|
|
|
def make_model():
|
|
model = Sequential()
|
|
model.add(layers.Dense(10, activation="relu", input_shape=(4,)))
|
|
model.add(layers.Dense(10, activation="relu"))
|
|
model.add(layers.Dense(3, activation="softmax"))
|
|
|
|
return model
|
|
|
|
|
|
def load_data():
|
|
iris = load_iris()
|
|
x = iris.data
|
|
y = iris.target
|
|
|
|
y = keras.utils.to_categorical(y, 3)
|
|
|
|
x_train, x_test, y_train, y_test = train_test_split(
|
|
x, y, test_size=0.2, shuffle=True, stratify=y
|
|
)
|
|
|
|
return x_train, x_test, y_train, y_test
|
|
|
|
|
|
if __name__ == "__main__":
|
|
model = make_model()
|
|
x_train, x_test, y_train, y_test = load_data()
|
|
print(x_train.shape, y_train.shape)
|
|
|
|
loss = ["categorical_crossentropy", "accuracy", "mse"]
|
|
metrics = ["accuracy"]
|
|
|
|
model.compile(optimizer="sgd", loss=loss[0], metrics=metrics[0])
|
|
model.fit(x_train, y_train, epochs=200, batch_size=32, validation_split=0.2)
|
|
model.evaluate(x_test, y_test, batch_size=32)
|