feat: share multimodal hash helpers

[CUHKSZzxy]

Summary

• move multimodal content hashing into a shared VL helper
• update PyTorch prefix-cache paths to use the shared helper while preserving existing cache-key behavior
• populate dict-style multimodal content hashes before TurboMind conversion when prefix caching is enabled

Validation

• Focused VL hasher unit tests passed
• PyTorch block-trie prefix-cache unit tests passed
• Real PyTorch VL server repeated-image check showed cache reuse on a cacheable repeated multimodal prompt

Assistance

Assisted with Codex + GPT-5.5 xHigh Fast, reviewed manually

[Copilot]

Pull request overview

This PR centralizes multimodal content hashing into a shared lmdeploy.vl helper module, then updates PyTorch prefix-cache code paths (and tests) to use the shared implementation while keeping existing cache-key behavior stable.

Changes:

• Added lmdeploy/vl/hasher.py with deterministic hashing helpers for both dataclass-style and dict-style multimodal payloads.
• Rewired PyTorch prefix-cache hashing call sites to use the shared VL hasher (including unit test monkeypatch targets).
• Added focused unit tests covering hash stability, sensitivity to content/meta/mRoPE, and ignoring position-only keys for dict-style items.

Reviewed changes

Copilot reviewed 6 out of 6 changed files in this pull request and generated no comments.

Show a summary per file

File	Description
lmdeploy/vl/hasher.py	Introduces shared deterministic multimodal hashing + “ensure content_hash” helpers for two multimodal representations.
lmdeploy/pytorch/multimodal/data_type.py	Removes local hashing implementation and re-exports shared hashing helpers for compatibility.
lmdeploy/pytorch/messages.py	Updates prefix-cache meta hashing fallback to call the shared VL hasher.
lmdeploy/pytorch/engine/engine.py	Ensures multimodal content hashes are populated after preprocessing when prefix caching is enabled.
tests/test_lmdeploy/test_vl/test_hasher.py	Adds unit tests validating hash determinism and correct inclusion/exclusion rules.
tests/pytorch/paging/test_block_trie.py	Adjusts monkeypatching to target the shared hasher module instead of the previous PyTorch-local symbol.

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[grimoire]

Since we have alias make_multimodal_content_hash in pytorch/multimodal/data_type.py, the change in engine.py and messages.py might not be necessary.

[lvhan028]

It does not match what I had in mind for multimodal fingerprints.

What I expect

• Compute a stable content fingerprint early in the request path (before engine-specific preprocessing).
• Attach it to each multimodal item and pass it through to all backends
• Treat the fingerprint as general multimodal metadata, not something that only exists when enable_prefix_caching is on.

requirement mismatched