| MNIST |
Plain |
AVX+FMA+SSE |
Intel MKL-DNN |
| Train (s) |
83.375 |
64.026 |
77.266 |
| Evaluation (s) |
3.50 |
3.47 |
6.107 |
- Tensorflow 1.9.0
- Macbook Pro 13", 2016, 2.4 GHz Intel Core i7, 16 GB RAM, macOS Sierra
import tensorflow as tf
mnist = tf.keras.datasets.mnist
(x_train, y_train),(x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
model = tf.keras.models.Sequential([
tf.keras.layers.Flatten(),
tf.keras.layers.Dense(512, activation=tf.nn.relu),
tf.keras.layers.Dropout(0.2),
tf.keras.layers.Dense(10, activation=tf.nn.softmax)
])
model.compile(optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy'])
model.fit(x_train, y_train, epochs=5)
model.evaluate(x_train, y_train)
