feat(neuron): Stage A — vision tower load + preprocessor for Qwen3.6

Stage A of the vision implementation plan
(doc/vision-qwen3_6-spec.md). Builds the vision tower scaffolding
that today's silent-drop failure mode (issue #3) needs — the
Qwen3.6 ViT loads from `model.visual.*`, runs forward producing
post-merger LM-side image embeddings, and routes through the
device worker via a new `Job::EncodeImage`. No LM splice yet —
that's Stage B.

Refs #3 (umbrella). Deferred sub-stages tracked as #12 (TP-vision),
#13 (27B production deploy), #14 (dynamic resolution), #15
(numerical validation).

What landed:

- **A0 — investigation**: pulled config.json, preprocessor_config.json,
  chat_template.jinja, and safetensors index from beast's local
  Qwen3.6-27B cache. Documented in doc/vision-qwen3_6-spec.md with
  exact tensor shapes for every `model.visual.*` weight. Confirms
  27-block ViT with `hidden_size=1152`, `patch_size=16`,
  `spatial_merge_size=2`, `out_hidden_size=5120`. Vision tower lives
  in 2 of the 15 safetensors shards.

- **A1 — deps + scaffolding**: added `image = "0.25"` (default-
  features off, PNG/JPEG/WebP/BMP/GIF) and `base64 = "0.22"` to
  crates/neuron/Cargo.toml. Created `harness::preprocess` and
  `harness::arch::qwen3_5::vision` modules.

- **A2 — preprocess.rs**: `decode_data_uri` strips
  `data:image/...;base64,...` → image bytes → `image::DynamicImage`
  (rejecting `http(s)://` URLs to avoid SSRF/recursion); `preprocess`
  resizes to a fixed `PreprocessProfile::qwen3_6()` (448×448),
  normalises to `[-1, 1]` per the model's mean/std=0.5, emits
  row-major `(3, H, W)` f32. 9 unit tests covering data URI parse,
  decode failure paths, grayscale-to-RGB promotion, and the
  exact-value normalisation contract.

- **A3 — vision.rs**: `VisionTower` struct with `patch_embed: Conv2d`,
  learned `pos_embed: Embedding`, 27 `VisionBlock`s (pre-LN +
  multi-head self-attention with fused QKV + GELU-tanh MLP +
  residuals), and `VisionMerger` (LayerNorm → 2×2 spatial concat →
  linear_fc1 → GELU-tanh → linear_fc2 to LM hidden_size).
  Includes the Conv3d→Conv2d fold trick documented at the top of
  the file — the published patch_embed.proj.weight is 5D
  `(1152, 3, 2, 16, 16)` but candle 0.10 has no Conv3d; for static
  images we sum-collapse the temporal axis. Video would need real
  Conv3d. 5 unit tests including the exact `gelu_pytorch_tanh`
  reference values from PyTorch.

- **A4 — wire vision into Qwen3_5ForCausalLM**: extended `Config`
  with optional `vision_config: Option<VisionConfig>` and
  `image_token_id`; `Qwen3_5ForCausalLM::new` now loads the vision
  tower when present, exposes `has_vision()` and `vision()` so the
  HTTP layer can advertise capability and so the encode path can
  reach it.

- **A5 — device worker `Job::EncodeImage`**: new job variant carrying
  CPU-side `(C, H, W)` pixels. Dispatch handler reconstructs the
  tensor on the worker's device, calls `arch.encode_image(image)`,
  copies the result back to CPU as flat `Vec<f32>`. Keeps the
  "tensors don't escape the worker" invariant. Poisoned-worker
  drain path handles the new variant.

- **A6 — dispatch round-trip test**: `encode_image_routes_to_dispatch_
  and_errors_on_unknown_handle` proves the channel/dispatch wiring
  works end-to-end via the CPU device worker (errors on unknown
  ArchHandle, which is the expected behaviour without a loaded
  model — real-weights validation happens in Stage B when the LM
  splice path exists).

CI gate: cargo fmt --check, cargo clippy --workspace --all-targets
-- -D warnings, cargo test --workspace (all 28 test groups ok,
zero failures). New test counts: +9 in preprocess, +5 in vision,
+1 in device_worker.

Out of scope (deferred):
- LM-side splice of image embeddings at `<|image_pad|>` positions
  → Stage B.
- Streaming SSE for vision-bearing chat completions → Stage C.
- Reject `image_url` with HTTP 400 for non-vision models /
  advertise `capabilities` in /v1/models → Stage C.
- TP-vision (#12), 27B production deploy (#13), dynamic resolution
  (#14), numerical validation (#15).

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

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