v0.4.3: Bug-fix roundup — chunked top-k, empty batches, varlen autotune

Fixed

• Chunked top-k no longer crashes when top_k exceeds the merge width.
  retrieve(Q, D, top_k=10, chunk=4) (and the CUDA maxsim_topk it wraps)
  raised "selected index k out of range": each chunk contributes at most
  chunk columns, but the running merge always asked torch.topk for k.
  The merge now clamps k to the merged width; the final output still
  honors the documented min(top_k, Nd) contract on both paths.
• MaxSimScorer.forward() respects a caller's torch.no_grad(). The
  non-inference branch of _score forced torch.enable_grad(), so
  MaxSimScorer()(Q, D) inside torch.no_grad() returned a tensor with
  requires_grad=True. It now uses a null context and leaves the caller's
  grad mode untouched.
• maxsim_residual_varlen handles an empty corpus (Nd == 0). The
  launcher used grid Nq * max(Nd, 1) while the kernel computed
  pid // Nd with a constexpr Nd=0. The empty [Nq, 0] result is now
  returned before any launch.
• pack_padded handles an empty batch (B == 0). It crashed on
  qlen.max() of a zero-element tensor; it now returns the trivially-empty
  PackedBatch up front, so maxsim_padded agrees with the CPU reference
  ([0, C]).
• PyLate legacy mask= is forwarded on the fallback path. The patched
  colbert_scores / colbert_kd_scores / colbert_scores_pairwise mapped
  a legacy mask= into the fused path but called the original function
  with a still-None documents_mask when deferring to PyLate (CPU,
  sub-Ampere, LIK_DISABLE=1), silently dropping the doc mask.
• maxsim_backward_lowmem raises a clean RuntimeError without
  Triton/CUDA instead of failing inside the launch — same guard as
  maxsim_backward_unified, so backward/__init__'s import-anywhere
  promise holds.
• prune_forward falls back to the smallest-footprint configs. When
  every autotune config overflowed the shared-memory budget, the fallback
  returned the first two list entries — configs just pruned for exceeding
  the budget. It now returns the two with the smallest estimated SMEM
  footprint.
• The KD path (maxsim with 4-D D) validates device agreement for
  Q / D / masks like the 3-D path, instead of surfacing an internal
  kernel error on mixed devices.
• FP8 fallback really works without Triton. maxsim_inference_fp8's
  documented "transparent fallback" imported the Triton-backed maxsim
  unconditionally; it now dispatches like retrieve (Triton on CUDA,
  compiled reference on MPS, eager reference elsewhere), so the dequantized
  bf16 fallback runs on CPU-only installs.

Changed

• maxsim_varlen autotune sweeps are amortized across batch shapes.
  max_lq / max_ld were constexpr autotune keys with no bucketing, so —
  contrary to the previous docs — every distinct (max_lq, max_ld) pair
  re-triggered the full autotune sweep and recompiled the kernel. They
  are now exact runtime loop bounds (like the dense kernel's Ld), and
  the autotune cache is keyed on power-of-two-bucketed copies (floor 16)
  passed as key-only arguments: one sweep per bucket, zero masked
  iterations added, argmax buffer still sized on the exact max_lq.
  Results are unchanged. The PLAID kernels (maxsim_residual /
  maxsim_residual_varlen) deliberately keep their exact max_Ld key: it
  is a property of the compressed index, stable across calls, so the sweep
  amortizes to one — bucketing the loop bound there measured 30-50%
  steady-state throughput loss on Ld=300 corpora for no benefit, which
  is also why the varlen bounds stay exact.
• max_seqlen_* arguments are documented as hard loop bounds, not
  hints, in maxsim_varlen, score_pairs_packed, and
  maxsim_residual_varlen: a too-small value silently truncated tokens and
  returned wrong scores. Caller-supplied values are now checked against the
  cu_seqlens maxima with an on-device torch._assert_async (no D2H sync,
  same trade-off as pack_padded's length checks).
• maxsim_residual squeezes a 2-D Q back to [Nd] instead of
  returning [1, Nd], matching maxsim_residual_varlen and the maxsim
  wrapper's convention. Behavior change for callers that relied on the
  un-squeezed shape.
• Removed the dead B constexpr from _plaid_approx_score_kernel (it
  forced a recompile per batch size), the unused Lq / Ld placeholder
  params from the varlen forward kernel, and the dead Nq constexpr from
  _varlen_bwd_dQ_kernel. The varlen backward kernels also take max_lq
  as a runtime arg instead of a constexpr (mirroring the score_pairs
  backward kernels), so a new query-length maximum no longer recompiles
  them.
• Docstring corrections: maxsim_inference_fp8 no longer mentions argmax
  ties (the inference kernel never computes an argmax), and the lowmem
  backward docs say grads are written in the input dtype (fp16 / bf16 /
  fp32), not "bf16 grads".

Removed

• The interactive kernel picker page (docs/choose-a-kernel.html). It predates
  the API consolidation: with maxsim dispatching on layout and the patchers /
  native PyLate & colpali-engine backends covering the framework paths, a
  decision tree over many entry points no longer reflects the library. The
  README "Choose a kernel" section and links are gone with it.