23-06-23

readme 파일 수정 - env 파일 및 설명 추가 , 참고 자료 수정
iris_tf.py 모델의 성능 교차 검증을 위해 추가

iris_tf.py

@@ -0,0 +1,51 @@
+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 tensorflow import keras
+from tensorflow.keras import layers
+from tensorflow.keras.models import Sequential
+
+from sklearn.datasets import load_iris
+from sklearn.model_selection import train_test_split
+
+
+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)