import tensorflow as tf

from keras.models import Model

import tensorflow as tf


def make_parallel(model, gpu_count):
    def get_slice(data, idx, parts):
        shape = tf.shape(data)
        size = tf.concat(0, [shape[:1] // parts, shape[1:]])
        stride = tf.concat(0, [shape[:1] // parts, shape[1:] * 0])
        start = stride * idx
        return tf.slice(data, start, size)

    outputs_all = []
    for i in range(len(model.outputs)):
        outputs_all.append([])

    # Place a copy of the model on each GPU, each getting a slice of the batch
    for i in range(gpu_count):
        with tf.device('/gpu:%d' % i):
            with tf.name_scope('tower_%d' % i) as scope:

