def mnist_batcher_in_tanh_vector(
batch_size,
capacity=256,
min_after_dequeue=128,
):
(x, y), (_, _) = keras.datasets.mnist.load_data()
x = tf.constant(x)
x = tf.cast(x, tf.float32)
x = keras.layers.Flatten()(x) / 127.5 - 1.
y = tf.cast(y, tf.int64)
return tf.train.shuffle_batch(
[x, y],
batch_size=batch_size,
capacity=capacity,
min_after_dequeue=min_after_dequeue,
enqueue_many=True
)
评论列表
文章目录