Handle error in case outputs subscripts of xeinsum are not unique

[lgeiger]

np.einsum("ij->jij", np.zeros((2, 2)))

throws an error since the output subscript j is specified multiple times:

ValueError: einstein sum subscripts string includes output subscript 'j' multiple times

However

jnp.einsum_path("ij->jij", jnp.zeros((2, 2)))

runs into an internal assertion error which is not very user friendly.

   3629   raise NotImplementedError  # if this is actually reachable, open an issue!
   3631 # the resulting 'operand' with axis labels 'names' should be a permutation
   3632 # of the desired result
-> 3633 assert len(names) == len(result_names) == len(set(names))
   3634 assert set(names) == set(result_names)
   3635 if names != result_names:

AssertionError:

Since jax relies on opt_einsum for its error handling I made an upstream PR to fix that in dgasmith/opt_einsum#222 (also see numpy/numpy#25230 which does the same for np.einsum_path)

This PR fixes the _use_xeinsum=True code path which currently would completely ignore the error and still output an array:

jnp.einsum_path("ij->jij", jnp.zeros((2, 2)), _use_xeinsum=True)
# Array([[0., 0.],
#        [0., 0.]], dtype=float32)

[lgeiger]

An alternative would be to do something like this if we want a more verbose error message and don't mind iterating over the array

    for out_sub in out_subs:
        if out_subs.count(out_sub) != 1:
            raise ValueError("Output subscript %s appeared more than once in the output." % out_sub))