RF relative_positional_encoding, fix internal indices spatial dim

Specifically for cross attention, it could happen that
max(q_seq_len+k_seq_len-1) != shape.

returnn/frontend/attention.py

@@ -862,13 +862,23 @@ def _make_indices(
         query_spatial_dim_m1 = query_spatial_dim - 1
         q_pos_vec = rf.range_over_dim(query_spatial_dim_m1)  # [q_len-1]
 
+        # The masking in the output is quite custom (left+right masking), so our seq lens don't make sense,
+        # and might even cause to fail some tests (that e.g. max(q_seq_len+k_seq_len-1) == shape).
+        out_spatial_dim = Dim(
+            query_spatial_dim_m1.get_dim_value_tensor() + key_value_spatial_dim.get_dim_value_tensor() - 1,
+            name=f"2*{query_spatial_dim.description}-1"
+            if (query_spatial_dim == key_value_spatial_dim)
+            else f"{query_spatial_dim.description}+{key_value_spatial_dim.description}-1",
+        )
+
         # We want to have all distances as in rf.combine_bc(kv_pos_vec, "-", q_pos_vec) with shape [q_len,kv_len].
         # We want to store only non-duplicates.
         # The min value is with kv_pos=0, q_pos=q_len-1: -(q_len-1)
         # The max value is with kv_pos=kv_len-1, q_pos=0: k_len-1
-        indices, out_spatial_dim = rf.concat(
+        indices, _ = rf.concat(
             (q_pos_vec - query_spatial_dim_m1.get_dim_value_tensor(), query_spatial_dim_m1),
             (kv_pos_vec, key_value_spatial_dim),
+            out_dim=out_spatial_dim,
             handle_dynamic_dims=False,
         )
     if query_offset is not None: