Adds VectorNonlinearOracle support

.github/workflows/ci.yml

@@ -17,9 +17,6 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          - version: '1.6'
-            os: ubuntu-latest
-            arch: x64
           - version: '1'
             os: ubuntu-latest
             arch: x64

.gitignore

@@ -8,3 +8,4 @@ Manifest.toml
 examples/.ipynb_checkpoints
 .DS_Store
 /Manifest.toml
+coverage/lcov.info

Project.toml

@@ -1,7 +1,7 @@
 name = "DiffOpt"
 uuid = "930fe3bc-9c6b-11ea-2d94-6184641e85e7"
 authors = ["Akshay Sharma", "Mathieu Besançon", "Joaquim Dias Garcia", "Benoît Legat", "Oscar Dowson", "Andrew Rosemberg"]
-version = "0.5.5"
+version = "0.5.6"
 
 [deps]
 BlockDiagonals = "0a1fb500-61f7-11e9-3c65-f5ef3456f9f0"
@@ -24,4 +24,4 @@ LazyArrays = "1, 2"
 MathOptInterface = "1.18"
 MathOptSetDistances = "0.2.9"
 ParametricOptInterface = "0.14.1"
-julia = "1.6"
+julia = "1.10"

docs/src/manual.md

@@ -76,6 +76,89 @@ and the following objective types:
 | `ScalarQuadraticFunction`  | 
 | `ScalarNonlinearFunction`  |
 
+### `VectorNonlinearOracle` bridge (`NonlinearProgram`)
+
+`DiffOpt.NonLinearProgram` supports `MOI.VectorOfVariables` in
+`MOI.VectorNonlinearOracle` through an internal bridge that rewrites the vector
+oracle into scalar nonlinear constraints.
+
+At a high level, for a vector oracle $f:\mathbb{R}^n \to \mathbb{R}^m$ with
+bounds $l \le f(x) \le u$:
+
+- one scalar nonlinear operator is registered per output row $f_i(x)$
+- each row is converted into one or two scalar constraints based on bounds:
+  - finite and equal $l[i] == u[i]$: `EqualTo(l[i])`
+  - finite lower only: `GreaterThan(l[i])`
+  - finite upper only: `LessThan(u[i])`
+  - both finite and different: one `GreaterThan` and one `LessThan`
+  - infinite bounds are skipped
+
+Callback signature requirements follow MOI:
+
+- univariate (`input_dimension == 1`):
+  - `f(x)::Real`
+  - `∇f(x)::Real`
+  - `∇²f(x)::Real`
+- multivariate (`input_dimension > 1`):
+  - `f(x...)::Real`
+  - `∇f(g, x...)` fills `g`
+  - `∇²f(H, x...)` fills the lower-triangular part of `H`
+
+Warm-start mapping for bridged constraints:
+
+- `ConstraintPrimalStart` expects an input vector `x` (not `f(x)`), evaluates
+  the oracle at `x`, and writes starts for each generated scalar constraint.
+- `ConstraintDualStart` accepts either:
+  - length = output dimension `m`: treated as direct row duals
+  - length = input dimension `n`: interpreted as `J' * λ` and converted to row
+    duals `λ` via a least-squares solve
+
+Current limitation:
+
+- for dual starts on rows with both finite bounds (`l[i] < u[i]`), only the
+  lower-bound side is propagated explicitly (the upper-side split is not
+  modeled in this bridge-level helper).
+
+Minimal JuMP example:
+
+```julia
+using JuMP, DiffOpt, Ipopt
+import MathOptInterface as MOI
+
+model = DiffOpt.nonlinear_diff_model(Ipopt.Optimizer)
+@variable(model, x[1:2])
+@objective(model, Min, x[1]^2 + x[2]^2)
+
+function eval_f(ret, z)
+    ret[1] = z[1]^2 + z[2]^2
+    return
+end
+function eval_jacobian(ret, z)
+    ret[1] = 2z[1]
+    ret[2] = 2z[2]
+    return
+end
+function eval_hessian_lagrangian(ret, z, μ)
+    ret[1] = 2μ[1]  # (1,1)
+    ret[2] = 2μ[1]  # (2,2)
+    return
+end
+
+set = MOI.VectorNonlinearOracle(;
+    dimension = 2,
+    l = [-Inf],
+    u = [1.0],
+    eval_f,
+    jacobian_structure = [(1, 1), (1, 2)],
+    eval_jacobian,
+    hessian_lagrangian_structure = [(1, 1), (2, 2)],
+    eval_hessian_lagrangian,
+)
+
+@constraint(model, [x[1], x[2]] in set)
+optimize!(model)
+```
+
 ## Creating a differentiable MOI optimizer
 
 You can create a differentiable optimizer over an existing MOI solver by using the `diff_optimizer` utility. 

src/ConicProgram/ConicProgram.jl

@@ -140,6 +140,17 @@ function MOI.supports_constraint(
     return MOI.supports_constraint(model.model, F, S)
 end
 
+function MOI.supports_constraint(
+    ::Model,
+    ::Type{MOI.VectorAffineFunction{Float64}},
+    ::Type{MOI.VectorNonlinearOracle{Float64}},
+)
+    # VNO constraints require the nonlinear bridge path. If we accept them here,
+    # the conic projection code later tries to reconstruct the set by dimension
+    # only, which is invalid for VectorNonlinearOracle.
+    return false
+end
+
 function MOI.supports_constraint(
     ::Model,
     ::Type{MOI.VectorAffineFunction{T}},

src/NonLinearProgram/NonLinearProgram.jl

@@ -353,6 +353,7 @@ function MOI.empty!(model::Model)
 end
 
 include("nlp_utilities.jl")
+include("vno_bridge.jl")
 
 """
     _inertia_correction(