import tensorflow as tf
print(tf.__version__)
2.4.0
!pip install -q tensorflow-gpu==2.0.0-rc1
import tensorflow as tf# 데이터 가져오기
mnist = tf.keras.datasets.mnist
(x_train, y_train), (x_test, y_test) = mnist.load_data()
# 데이터 정규화
x_train, x_test = x_train / 255.0, x_test / 255.0
Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz 11493376/11490434 [==============================] - 0s 0us/step
print("학습용 데이터 : x: {}, y:{}".format(x_train.shape, y_train.shape) )
print("테스트 데이터 : x: {}, y:{}".format(x_test.shape, y_test.shape) )
학습용 데이터 : x: (60000, 28, 28), y:(60000,) 테스트 데이터 : x: (10000, 28, 28), y:(10000,)
model = tf.keras.models.Sequential([
tf.keras.layers.Flatten(input_shape=(28, 28)), # 2D -> 1D
tf.keras.layers.Dense(128, activation='relu'), # 활성화 함수 - relu
tf.keras.layers.Dropout(0.2), # Dropout적용
tf.keras.layers.Dense(10, activation='softmax') # 활성화 함수 - softmax
])
model.compile(optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy'])
model
<tensorflow.python.keras.engine.sequential.Sequential at 0x7fb25a98a9b0>
%%time
model.fit(x_train, y_train, epochs=15)
model.evaluate(x_test, y_test, verbose=2)
Epoch 1/15 1875/1875 [==============================] - 5s 2ms/step - loss: 0.4789 - accuracy: 0.8591 Epoch 2/15 1875/1875 [==============================] - 3s 2ms/step - loss: 0.1522 - accuracy: 0.9545 Epoch 3/15 1875/1875 [==============================] - 3s 2ms/step - loss: 0.1068 - accuracy: 0.9674 Epoch 4/15 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0848 - accuracy: 0.9735 Epoch 5/15 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0740 - accuracy: 0.9768 Epoch 6/15 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0631 - accuracy: 0.9795 Epoch 7/15 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0569 - accuracy: 0.9810 Epoch 8/15 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0515 - accuracy: 0.9833 Epoch 9/15 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0458 - accuracy: 0.9847 Epoch 10/15 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0452 - accuracy: 0.9854 Epoch 11/15 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0387 - accuracy: 0.9882 Epoch 12/15 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0378 - accuracy: 0.9875 Epoch 13/15 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0345 - accuracy: 0.9881 Epoch 14/15 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0327 - accuracy: 0.9890 Epoch 15/15 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0316 - accuracy: 0.9892 313/313 - 0s - loss: 0.0689 - accuracy: 0.9800 CPU times: user 52.4 s, sys: 5.36 s, total: 57.8 s Wall time: 49.5 s