How to check if a least squares problem (objective="none") is constrained or unconstrained

[FYuChen]

In the "Example Usage" section of the PyCUTE v1.7.2 documentation, it mentions "In CUTEst nonlinear least-squares problems are encoded as nonlinear equations which have no objective function defined (as denoted by ‘none’ in their classification). Instead, their residual(s) r(x) and Jacobian J(x) are accessed using CUTEstProblem.cons()." Does this mean that all least-squares problems are unconstrained?
I know that I can check whether a problem has bound constraints by examining its bl and bu attributes. However, I'm not sure how to check if a problem has general nonlinear equality or inequality constraints. In other words, how can I tell if the least-squares problem is of the form min_x ||r(x)||^2 or min_x ||r(x)||^2 s.t. g(x)=0,h(x)<=0? Thanks for any help!

[jfowkes]

Yes that is correct, all general nonlinear least-squares problems are unconstrained as there is no mechanism within CUTEst to incorporate additional constraints (since the least-squares objective is defined in problem.cons()).

However, there are some CUTEst problems that have sum of squares objectives and these can have additional constraints, but this is a very special nonlinear least-squares problem. You can search for these using the search functions within PyCUTEst.

[FYuChen]

Got it! Thanks for your reply.