How to expand dimensions in Tensorflow

Question

I have this tensor A:

<tf.Tensor: shape=(2, 18), dtype=float32, numpy=
array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1.,
        1., 1.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
        0., 0.]], dtype=float32)>

I want to create a mask to add to another tensor with shape (2, 18, 1000). That is, I want to expand each number to 1000 of them, so for example, in tensor A, change each 0 to a dimension of 1000 zeros, and in each 1, change each of them to a dimension of 1000 ones. How could I do it?

Edit

Basically, what I want to do is transform tensor A from shape (2, 18) to shape (2, 18, 1000) with those 1000 values being 0 or 1