---

name: structured-operators description: "Route pure-Python NeuroMANCER SLiM maps, structured recurrent layers, differentiable projection and iterative solvers, and dimension or parameterization failures." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Structured operators

Use this route when a task needs a NeuroMANCER structured linear map, a structured SLiM RNN, GradientProjection/IterativeSolver, a safe LOP building block, or a small operator smoke test. Start with the tensor/key contract and dimensions, then select a named map from neuromancer.slim.maps; do not guess a class or constructor keyword.

Route

1. Decide the map shape. A map consumes (..., insize) and returns (..., outsize); square parametrizations require insize == outsize, and trivial_nullspace additionally requires outsize >= insize and bias=False.
2. Select a registry key and instantiate it with only supported kwargs. Prefer the pure-Python map set in the bundled smoke script. Treat butterfly, its complex mode, and factor extension as an optional route, not as a CPU prerequisite.
3. Check effective_W(), reg_error(), output shape, and one backward pass. For an orthogonal map in this release, use bias=True because its forward implementation adds self.bias unconditionally.
4. For a sequence, use slim.RNNCell or slim.RNN: sequence tensors are (seq_len, batch, input_size), hidden maps are square on hidden_size, and the input map may be rectangular.
5. For a solver, keep symbolic constraint construction in the symbolic-problems route. Feed the solver a dictionary containing every constraint input key, preserve requires_grad=True for projected variables, and match input_keys to output_keys.
6. When embedding a map in modules.blocks.MLP, remember that linear_map is applied to every layer. A square map therefore requires every adjacent MLP width to be equal.

See the API and shape contracts, bounded workflows, and the failure matrix. Run scripts/maps_smoke.py --run for a deterministic CPU-only map and autograd check; --help documents the safe invocation.

Route out

• Ordinary MLPs, neural dynamics, and model architecture choices belong to dynamics-modeling.
• Variable/expression comparator syntax and symbolic problem graphs belong to symbolic-problems; this route only consumes their constraint objects.
• Dataset, benchmark, external-data, and download workflows are not part of this operator smoke.
• Native C++/CUDA butterfly factor multiplication and complex/butterfly benchmarking are explicitly optional and excluded from the minimum route.