feat(m2): TS Encoder — Patchify + 2-layer Transformer (T2.1)

- src/tsmm/model/ts_encoder.py: Patchify (channel-independent unfold) +
  TSEncoder (shared per-channel patch linear, mean-pool over channels,
  learnable positional embedding, 2-layer pre-norm Transformer, LayerNorm).
- configs/ts_encoder.yaml: encoder/projector hyperparameters.
- tests/test_ts_encoder.py: 10 tests (shape, n_patches formula, window
  values, determinism, gradient flow, param sanity).
- 61 tests passing; GPU fwd/bwd verified on RTX 3060 (39 MB peak).

Spec clarifications (small tier, comet-build Step 4):
- n_patches = (T-P)//S+1 ⇒ 127 for T=512 (design said 128; arithmetic slip).
- 'Channel-independent' = shared per-channel patch embed + mean-pool →
  C-free output [B,n_patches,d]; channel identity carried by [属性] tokens.
- Actual params ≈2.1M (design's '≈4M' was a rough estimate).

configs/ts_encoder.yaml

@@ -0,0 +1,20 @@
+# TS Encoder + Projector hyperparameters (T2.1 / T2.2)
+# Design ref: docs/superpowers/specs/2026-06-29-ts-as-modality-design.md §2.2
+
+# Patchify (channel-independent)
+patch_len: 8        # P
+stride: 4           # S (overlap); n_patches = (T - P) // S + 1
+
+# TS Encoder (2-layer Transformer)
+d: 256              # hidden dim
+layers: 2
+heads: 4
+ffn_mult: 4         # dim_feedforward = d * ffn_mult
+dropout: 0.1
+
+# Projector (T2.2) — maps TS token d → LLM hidden
+llm_hidden: 896     # Qwen2.5-0.5B hidden size
+
+# Context
+T: 512              # default window length → 127 TS tokens
+max_patches: 2048   # positional-embedding budget