multi-gpu not works

[UpCoder]

Hi, I try to use this method to parallel my model. but it may do not work.
For example, I use 3 gpus. but actually it seem use one gpu.
The code is

def multi_gpu_wrapper(single_model, num_gpu):
    inputs = single_model.inputs
    towers = []
    concate_layer = tf.keras.layers.Concatenate(axis=0)
    for gpu_id in range(num_gpu):
        print 'cur gpu is ', gpu_id
        with tf.device('/gpu:' + str(gpu_id)):
            splited_layer = tf.keras.layers.Lambda(lambda x: slice_batch(x, num_gpu, gpu_id))
            cur_inputs = []
            for input in inputs:
                cur_inputs.append(
                    splited_layer(input)
                )
            towers.append(single_model(cur_inputs))
            print towers[-1]
    outputs = []
    num_output = len(towers[-1])
    with tf.device('/cpu:0'):
        for i in range(num_output):
            tmp_outputs = []
            for j in range(num_gpu):
                tmp_outputs.append(towers[j][i])
            outputs.append(concate_layer(tmp_outputs))
    multi_gpu_model = tf.keras.models.Model(inputs=inputs, outputs=outputs)
    return multi_gpu_model

The output of nvidia-smi is:

Do you know how to fix it?
Thank you!