Add optional Modal calibration backend

[MaxGhenis]

Summary

• Recreates the useful part of Add Modal GPU calibration #279 on top of current main instead of resolving the stale/conflicting branch.
• Adds an opt-in Modal GPU backend for the constituency and local-authority calibration steps.
• Keeps pull-request builds on the existing CPU path; trusted push/manual builds enable Modal only when MODAL_TOKEN_ID and MODAL_TOKEN_SECRET are present.
• Mirrors current CPU calibration semantics for sparse local targets by sending a local_target_available mask and replacing NaNs with zero only in the tensor payload.

What this does

The dataset build still creates/imputes/uprates the FRS locally. At calibration time:

• default path: unchanged CPU calibrate_local_areas flow;
• MODAL_CALIBRATE=1: build the constituency, LA, and national loss matrices locally, serialize the arrays, spawn both GPU optimization jobs on Modal concurrently, retrieve weight checkpoints, write the calibration logs, and save the same .h5 weight files.

Verification

• uv lock --check
• uv run --python 3.13 --frozen --extra dev ruff check policyengine_uk_data/datasets/create_datasets.py policyengine_uk_data/utils/modal_calibrate.py policyengine_uk_data/tests/test_modal_calibration.py
• uv run --python 3.13 --frozen --extra dev python - <<'PY' ... import modal_calibrate ... PY
• uv run --python 3.13 --frozen pytest policyengine_uk_data/tests/test_modal_calibration.py policyengine_uk_data/tests/test_calibrate_save.py policyengine_uk_data/tests/test_calibration_progress.py -q
• Parsed .github/workflows/push.yaml and .github/workflows/pull_request.yaml with PyYAML.

Supersedes #279.