Expose distributed (multi-GPU) PDLP settings in the Python API

[ramakrishnap-nv]

Exposes distributed (multi-GPU) PDLP settings on the Python side — a typed DistributedPdlpPartitioner enum (core + thin client), the missing use_distributed_pdlp/distributed_pdlp_partitioner fields on the REST server's solver_config model, and docs. Java is out of scope here.

Note: solving via DataModel/Solve() (and the REST server) builds the problem directly on the GPU, so these settings only take effect once #1958 (GPU-resident dispatch fix) lands — documented in the docstrings until then.

Fixes #1931

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📝 Walkthrough

Walkthrough

Adds distributed PDLP multi-GPU configuration, partitioner enums, public API exports, documentation, and solver-settings tests for Python and self-hosted clients.

Changes

Distributed PDLP API

Layer / File(s)	Summary
Configuration and partitioner enums python/cuopt_server/.../data_definition.py, python/cuopt/.../solver_settings/*, python/cuopt_self_hosted/.../*	Adds distributed PDLP configuration fields and DistributedPdlpPartitioner enums with Auto, KaMinPar, and RoundRobin values.
API documentation docs/cuopt/source/...	Documents distributed PDLP requirements, GPU selection, partitioner constants, and the self-hosted client enum.
Solver settings validation python/cuopt/cuopt/tests/linear_programming/test_lp_solver.py	Tests distributed PDLP setting assignment, retrieval, enum values, and string conversion.

Priority: ➖ Normal

Estimated code review effort: 3 (Moderate) | ~20 minutes

Change: Feature

Suggested reviewers: iroy30

Merge Risk: 🟡 Moderate · up to a2ec0

Validate distributed-PDLP REST inputs and correct the Python usage and GPU-boundary documentation before merging.

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 50.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 6 functions across 6 files. (5 skipped: 5…	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Linked Issues check	✅ Passed	The PR satisfies the Python objectives for issue #1931. It adds the typed DistributedPdlpPartitioner enum, package exports, REST solver_config fields for use_distributed_pdlp and `distributed_pd…
Out of Scope Changes check	✅ Passed	The changed files support issue #1931. The enum exports, REST model fields, tests, and documentation expose or verify distributed PDLP configuration. The copyright-year update is limited to a changed …
Description check	✅ Passed	The description clearly covers the Python API enums, REST solver configuration fields, documentation, scope, dependency on issue #1958, and the linked issue. It is directly related to the changeset.
Title check	✅ Passed	The title clearly and concisely summarizes the main change: exposing distributed multi-GPU PDLP settings through the Python API.

Full details: Docstring Coverage

Explanation

Docstring coverage is 50.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 6 functions across 6 files. (5 skipped: 5 unsupported.)

✨ Finishing Touches 💡 1

🛠️ Fix failing CI checks 💡

• Commit to this branch
• Create a new PR

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Actionable comments posted: 3

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Inline comments:
In `@docs/cuopt/source/convex-features.rst`:
- Line 331: Update the Distributed PDLP documentation to clarify that
num_gpus=-1 may resolve to only one visible GPU, and that multi-GPU sharding
occurs only when more than one GPU is selected. Apply this qualification
consistently to both relevant descriptions while preserving the existing PDLP,
partitioner, and use_distributed_pdlp details.

In `@docs/cuopt/source/convex-settings.rst`:
- Around line 153-155: Update the distributed PDLP parameter documentation to
cover the core Python API alongside the existing C and thin-client guidance. Add
a Python example or link showing SolverSettings.set_parameter configured with
SolverMethod.PDLP, num_gpus, use_distributed_pdlp, and
DistributedPdlpPartitioner, using the existing symbols
DistributedPdlpPartitioner, SolverMethod, and SolverSettings.

In
`@python/cuopt_server/cuopt_server/utils/linear_programming/data_definition.py`:
- Line 487: The SolverConfig definition currently permits invalid
distributed-PDLP settings. Constrain distributed_pdlp_partitioner to the
documented categorical values, and add a model-level validator enforcing the
dependency between use_distributed_pdlp, method, and num_gpus; reject invalid
combinations during request validation while preserving valid configurations.

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📥 Commits

Reviewing files that changed from the base of the PR and between c80859c and a2ec08a.

📒 Files selected for processing (11)

• docs/cuopt/source/convex-features.rst
• docs/cuopt/source/convex-settings.rst
• docs/cuopt/source/cuopt-c/convex/convex-c-api.rst
• docs/cuopt/source/cuopt-server/client-api/sh-cli-api.rst
• python/cuopt/cuopt/linear_programming/__init__.py
• python/cuopt/cuopt/linear_programming/solver_settings/__init__.py
• python/cuopt/cuopt/linear_programming/solver_settings/solver_settings.pyx
• python/cuopt/cuopt/tests/linear_programming/test_lp_solver.py
• python/cuopt_self_hosted/cuopt_sh_client/__init__.py
• python/cuopt_self_hosted/cuopt_sh_client/thin_client_solver_settings.py
• python/cuopt_server/cuopt_server/utils/linear_programming/data_definition.py

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[ramakrishnap-nv]

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[chris-maes]

Are we sure we want to define this as an enum. Enums require extra code. By keeping this as an int no further code changes are required.