코드 변경 내용을 요약한 커밋 메시지입니다.

test/iris_tf.py

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+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)