feat(e2e-tests): stacked e2e after split metrics

[davidberenstein1957]

Summary

• Rebased the existing e2e branch on top of the fully split metric stack
• Keeps e2e/integration-focused changes isolated from per-metric PRs
• Removes overlap with metric-specific unit coverage now handled in dedicated PRs

Test plan

• Run uv run pytest tests/evaluation/test_vlm_e2e.py tests/evaluation/test_task.py

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Cursor Bugbot has reviewed your changes and found 4 potential issues.

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Package realesrgan moved from optional to core dependency

High Severity

realesrgan was moved from the [upscale] optional dependency group into core dependencies, and the [upscale] extra was deleted entirely. This forces every user to install realesrgan and its heavy transitive dependencies (basicsr, facexlib, gfpgan, etc.) even if they never use upscaling. This PR is about VLM e2e tests and has no reason to change this. Likely an accidental inclusion from a rebase or merge.

Additional Locations (1)

• pyproject.toml#L188-L198

 

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Version downgraded and Python 3.13 support dropped

High Severity

version was downgraded from "0.3.3" to "0.3.2" and requires-python was tightened from ">=3.10,<3.14" to ">=3.10,<3.13", dropping Python 3.13 support. The PR description says "pyproject.toml — Already updated in PR-2", suggesting these regressions were accidentally included during a rebase or merge conflict resolution.

Additional Locations (1)

• pyproject.toml#L102-L103

 

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evaluation extra silently drops lmharness and rapidata

Medium Severity

The [evaluation] optional extra was redefined from ["pruna[rapidata]", "pruna[lmharness]"] to ["outlines>1.2.0,<2.0.0", "litellm>=1.0.0"]. Users running pip install pruna[evaluation] will no longer get lm-eval or rapidata. The [rapidata] extra was also completely removed. This is a silent backward-incompatible change to the package's public install interface.

 

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DrawBench/GenAIBench collate change alters return type

Medium Severity

DrawBench and GenAIBench collate functions changed from prompt_collate (returns (prompts, None)) to prompt_with_auxiliaries_collate (returns (prompts, list[dict])). Any existing code consuming these datasets and expecting gt=None (e.g., model inference handlers, metric update calls that check for None ground truth) will now receive a list of dicts, potentially causing unexpected behavior.

Additional Locations (1)

• src/pruna/data/__init__.py#L117-L118

 

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