fix: preserve explicit cuda selection in parallel workers

[RAMZI0TO99]

When device_ids is absent or empty, ParallelWorkerPool.start() omits its cuda setting from worker options. An explicit cuda=False CPU request can therefore be lost when the worker reconstructs its model with an automatic default.

This always forwards the pool's cuda setting, while retaining round-robin device assignment. Tests run real child processes and reporting workers without a GPU or model download. They cover Boolean and Device enum selections, absent/empty/explicit device IDs, ordering, other options, and the pool option's precedence over conflicting worker kwargs. GPU inference was not tested.

Validation on Windows 11, Python 3.13.5, NumPy 2.3.5, FastEmbed 0.8.1:

• 21 selected tests passed: python -m pytest -q tests/test_parallel_cuda_forwarding.py tests/test_parallel_processor.py.
• Local diff-scoped AST docstring coverage: 8/8 functions (100%, above the reported 80% threshold). CodeRabbit's own result is separate.
• Ruff 0.3.4 lint/format and staged whitespace checks passed.
• Repository mypy and pyright checks passed on Python 3.13.5.

The full model/OS/Python CI matrix was not run locally.

Split from #766 following the maintainer's request for one PR per problem. This branch is based directly on current main and contains only this problem's production change and regression module.

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ℹ️ Recent review info

⚙️ Run configuration

• Configuration used: Organization UI
• Review profile: CHILL
• Plan: Advanced
• Run ID: 4f979b84-1b1d-4041-ac36-001f27830e37

📥 Commits

Reviewing files that changed from the base of the PR and between 3d29818 and c81b6ca.

📒 Files selected for processing (1)

• fastembed/parallel_processor.py

💤 Files with no reviewable changes (1)

• fastembed/parallel_processor.py

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📝 Walkthrough

Walkthrough

ParallelWorkerPool.start now passes the configured cuda value to every worker. When device_ids are configured, the pool continues to assign each worker an ID by cycling through the list.

Priority: ⬇️ Low

Estimated code review effort: 1 (Trivial) | ~5 minutes

Change: Bug fix

Merge Risk: ⚪ Minimal · up to c81b6

This change makes parallel workers respect an explicit cuda selection, including CPU-only requests, while still assigning device IDs round-robin. No merge-blocking risk was identified.

Security Architecture Review

Security architecture risk: ⚪ Minimal · up to 3d298

The change consistently preserves the pool’s device selection without introducing a new privilege boundary or weakening existing provider checks. No material security risk was identified in the reviewed change.

Retained concerns
No architecture-level concerns identified.

Security review details

Security Blast Radius

• inferred — The changed behavior affects device selection in child workers created through the existing pool entrypoint. The reviewed path propagates an existing caller-supplied configuration value rather than adding an independently reachable privileged operation; deployment-specific device isolation was not established.

Trust Boundaries and Controls

• observed — Forwarded CUDA selection does not override explicit ONNX providers. The loader selects supplied providers first and rejects requested providers that are unavailable; these existing checks remain downstream of worker model reconstruction.

Resilience and Maintainability Implications

• observed — The diff leaves lifecycle handling unchanged. Child startup exceptions still signal an error and finalize queues before decrementing the active-worker counter; parent completion and interruption retain join or termination paths. Partial-startup and concurrent-use limitations are not newly addressed by this change.

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly and concisely describes the change: preserving the configured CUDA selection in parallel workers.
Description check	✅ Passed	The description explains the CUDA forwarding change and its regression tests, so it is directly related to the changeset.
Docstring Coverage	✅ Passed	Docstring coverage is 87.50% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 8 functions across 2 files.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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[joein]

thanks for addressing this!