train_mnist_model.py 文件源码

def load_tf_session():
    # Set TF random seed to improve reproducibility
    tf.set_random_seed(1234)

    # Image dimensions ordering should follow the Theano convention
    if keras.backend.image_dim_ordering() != 'th':
        keras.backend.set_image_dim_ordering('th')
        print("INFO: '~/.keras/keras.json' sets 'image_dim_ordering' to 'tf', temporarily setting to 'th'")

    # Create TF session and set as Keras backend session
    sess = tf.Session()
    keras.backend.set_session(sess)
    print("Created TensorFlow session and set Keras backend.")
    return sess


# Get MNIST test data