The feature vector would be the output of the embedding layer and you could calculate the difference afterwards to get the index back:
emb = torch.nn.Embedding(10, 50)
x = torch.tensor([5])

out = emb(x)
out.shape
emb.weight.shape

rev = ((out - emb.weight).abs().sum(1) < 1e-6).nonzero()
print(rev)
# > tensor([[5]])