def build_inputs(parameters, sess, inputs, outputs):
    (input_shape, filter_shape) = get_tensor_shapes(parameters)
    if (not parameters['fully_quantize']):
        values = [create_tensor_data(np.float32, input_shape), create_tensor_data(np.float32, filter_shape)]
    else:
        values = [create_tensor_data(np.float32, input_shape, min_value=(- 1), max_value=1)]
    return (values, sess.run(outputs, feed_dict=dict(zip(inputs, values))))
def build_inputs(parameters, sess, inputs, outputs):
    (input_shape, filter_shape) = get_tensor_shapes(parameters)
    if (not parameters['fully_quantize']):
        values = [create_tensor_data(np.float32, input_shape), create_tensor_data(np.float32, filter_shape)]
    else:
        values = [create_tensor_data(np.float32, input_shape, min_value=(- 1), max_value=1)]
    return (values, sess.run(outputs, feed_dict=dict(zip(inputs, values))))