>>> x = torch.LongTensor(2, 5).random_(0, 10)
>>> x
tensor([[5, 3, 9, 3, 8],
        [8, 1, 8, 6, 9]])
>>> embedded = embedding(x)
>>> embedded
tensor([[[ 1.0062,  0.8589, -1.6106],
         [-0.3584, -0.4176,  0.1584],
         [-0.0904,  0.4995, -0.6367],
         [-0.3584, -0.4176,  0.1584],
         [ 0.3695,  0.8041, -0.6507]],

        [[ 0.3695,  0.8041, -0.6507],
         [ 0.2623, -0.6216,  1.8112],
         [ 0.3695,  0.8041, -0.6507],
         [-0.4756,  1.3294,  0.3395],
         [-0.0904,  0.4995, -0.6367]]], grad_fn=<EmbeddingBackward>)