from tensorflow.python.ops import random_ops

      raise ValueError("keep_prob must be a scalar tensor or a float in the "
                       "range (0, 1], got %g" % keep_prob)
    keep_prob = ops.convert_to_tensor(
        keep_prob, dtype=x.dtype, name="keep_prob")
    keep_prob.get_shape().assert_is_compatible_with(tensor_shape.scalar())

    noise_shape = noise_shape or array_ops.shape(x)
    # uniform [keep_prob, 1.0 + keep_prob)
    random_tensor = keep_prob
    random_tensor += random_ops.random_uniform(
        noise_shape, seed=seed, dtype=x.dtype)
    # 0. if [keep_prob, 1.0) and 1. if [1.0, 1.0 + keep_prob)
    binary_tensor = math_ops.floor(random_tensor)
    ret = x * math_ops.inv(keep_prob) * binary_tensor
    ret.set_shape(x.get_shape())
    return ret


