…caches, F16 weights, profile CSV

QVAC-18607 follow-up tetherto#2.  Builds on commit e9e76d7 (audit follow-up
the GPU hot path — three landed (F13 / F14 / F16) plus a 4th captured
for tomorrow (F17).  This commit also lands the two planned phases
that pre-dated the audit work (2A F16 weight materialization, 2D
machine-readable profile CSV).

Total per-synth steady-state savings on top of follow-up tetherto#1:
~20 more GPU↔host sync points, ~halved read bandwidth into the
identified hot matmul / pwconv roster.

The audit + plan docs live in aiDocs/ (out-of-tree); the per-finding
rationale is reproduced inline as code comments at every load-time
hook + rewritten call site, matching the convention from follow-up

Audit findings landed (tetherto#2):

  F13  Text-encoder layer-norm weight host-side cache.
       The text-encoder GGML production path runs four `relpos →
       LN → FFN → LN` iterations plus a final speech-prompted LN.
       Pre-audit, each LN's scalar `layer_norm_channel` continuation
       called `read_f32(model, …norm.weight)` + `…norm.bias` per
       synth — 18 GPU→host downloads per synth on a non-CPU
       backend.  Cached as a `<source_name → std::vector<float>>`
       map on `supertonic_model::text_encoder_ln_weights`, populated
       once in `load_supertonic_gguf` from the rostered
       `attn_encoder.norm_layers_{1,2}.{0..3}.norm.{weight,bias}`
       pairs plus the final `speech_prompted_text_encoder.norm.norm.*`.
       Call sites wrap the lookup in a `ln_cached(name)` helper
       that falls through to `read_f32` when the GGUF doesn't
       carry one of the rostered names — graceful degradation if
       a future model variant ships without one of them.

  F14  Speech-prompted attention QKV graph cached across calls.
       `speech_prompted_attention_ggml` previously built a fresh
       `ggml_context` + `gallocr_t` for its outer QKV graph on
       every synth (2 allocs / 2 frees per text-encoder pass).
       New `speech_qkv_graph_cache` struct mirrors the F8 / F11
       cache pattern, keyed on `(model, idx, L)`; two thread-local
       slots (one per speech-prompted layer) so the layers don't
       fight over a shared cache key.  Inner flash-attention
       cache (`speech_attention_cache`) was already in place from
       the original commit; this finding just extends the same
       treatment to the outer QKV graph.

  F16  Speech-prompted attention `tanh_k` host-side cache.
       Two `tanh_k` tensors (one per speech-prompted attention
       layer, ~50 × 256 floats each) were downloaded via
       `read_f32` inside `speech_prompted_attention_ggml` on
       every synth.  Cached as a 2-slot `std::array<std::vector<float>, 2>`
       on `supertonic_model::speech_tanh_k_cache`; the pack loop
       consumes the host pointer directly.  Saves 2 sync points
       + ~100 KiB redundant traffic per synth.  Fallback to the
       per-call `read_f32` preserved for the missing-source case.

  F17  Duration scalar-continuation `read_f32` cache.
       NOT IN THIS COMMIT.  Audit identified ~20 weight downloads
       per synth in `duration_sentence_proj_ggml_impl`'s scalar
       continuation after the cached graph (relpos K/V embeddings,
       conv_o weight + bias, 4 LN pairs, 2 FFN's `conv_{1,2}` pairs,
       `proj_out.net.weight`).  Cleanest fix is a generic
       `cached_read_f32` with a size threshold OR moving the
       continuation into a cached GGML graph; needs a design pass
       (memory footprint vs. cache hit rate) before shipping.
       Captured in aiDocs for tomorrow.

Phase 2A — F16 weight materialization:

  EngineOptions::f16_weights — same -1 / 0 / 1 tri-state as
  f16_attn.  Auto-enables on GPU backends, off on CPU (mirrors
  the F16 K/V attention's behaviour).  Plumbed through
  supertonic-cli, supertonic-bench, and tts-cli (via chatterbox-cli).

  Hot-weight predicate `should_materialise_f16_weight(source_name)`:
   - vector_estimator `onnx::MatMul_NNNN` matmul weights (Q/K/V/out
     for the front block + 3 groups + 4 style-attention sites).
   - vector_estimator `*.pwconv1.weight` / `*.pwconv2.weight` for
     every convnext + last_convnext.
   - vocoder `*.pwconv1.weight` / `*.pwconv2.weight` + head linear.
   - text-encoder `text_encoder:onnx::MatMul_*` and FFN
     `conv_1.weight` / `conv_2.weight`.
  Negative list (audit-tested for predicate stability):
   - biases, `norm.norm.{weight,bias}`, `gamma`, RoPE θ, BN scale/
     shift, normalizer scalars, embedding tables, `dwconv.*`,
     small relative-position embeddings, F6's `__T` companions.

  Load-time conversion path:
   - Pre-read `supertonic.{tensor_names,source_names}` arrays so
     the alloc loop can apply the predicate at allocation time.
   - Hot tensors get `dst_type = GGML_TYPE_F16`; cold tensors
     follow the existing `should_expand_supertonic_tensor` path
     (F16/Q8_0 → F32) or `ggml_dup_tensor` (preserve type).
   - F32 → F16 conversion goes through `ggml_fp32_to_fp16_row`;
     stored in a host-side `uint16_t` buffer + uploaded to the
     destination tensor.

  Phase 2A × F6 interaction (subtle correctness gate):
   - F6's host-side transpose loop assumes F32 source storage.
     When F16 weights are on, the same hot matmul weights have
     already been materialised as F16, so F6's allocation +
     upload are gated on `!model.use_f16_weights`.
   - Call sites in `supertonic_vector_estimator.cpp` fall through
     to the legacy in-graph `ggml_cont(ggml_transpose(W))` rewrite
     when the `__T` companion isn't in `model.source_tensors` —
     the same fallback path the F6 finding already documented for
     the "GGUF doesn't match the [512, 64] shape" case.

Phase 2D — `SUPERTONIC_PROFILE_CSV` machine-readable timing emitter:

  Schema (matches the contract in test_supertonic_profile_csv.cpp):
    stage,island,step,wall_ms,unix_us
    vector,attn0_flash,0,1.234,1715517000123456
    ...

  API in supertonic_internal.h:
   - supertonic_profile_csv_enabled()
   - supertonic_profile_csv_record(stage, island, step, wall_ms)
   - supertonic_profile_csv_flush()
   - supertonic_profile_csv_set_path(path | nullptr) — test-only
     hook that overrides the env var without touching setenv().

  Implementation in supertonic_gguf.cpp:
   - File-local `profile_csv_state` (FILE *, mutex, env-probe
     latch).  Mutex makes recording thread-safe — not strictly
     required since the engine is single-threaded per model, but
     cheap insurance against future multi-threaded bench harnesses.
   - Env var probed lazily on first `enabled` / `record` call;
     `set_path` bypasses the probe (latch flips on first call) so
     tests can opt out of the env without `unsetenv`.
   - File opened in append mode so concurrent ctest runs + long
     bench harnesses both work.  Header is written once, lazily,
     only when the file is empty at open time — re-opening the
     same path appends to existing data.
   - `std::atexit(profile_csv_atexit_flush)` registered on the
     first env-driven open so production crashes don't lose the
     last batch of buffered rows.

  Hooks landed in:
   - `profile_vector_compute` (vector estimator, with step != -1).
   - `profile_vocoder_checkpoint` (vocoder, step = -1 sentinel).
   - `profile_text_compute` (text encoder, step = -1).
  Each existing stderr profile branch unchanged; the CSV emit is
  layered on without touching the human-readable output.

New TDD harnesses (CMakeLists.txt entries):

  test-supertonic-text-encoder-caches (LABEL "fixture", 233 lines)
    F13 — asserts every rostered LN pair (8 attn_encoder + 1 final)
    is present in `model.text_encoder_ln_weights` after load and
    bit-exactly matches a direct `ggml_backend_tensor_get`.
    F16 — asserts both `speech_tanh_k_cache[0..1]` are populated
    and bit-exactly match their source tensors.

  test-supertonic-f16-weights (LABEL "fixture" + LABEL "unit")
    Unit sub-tests run unconditionally (no GGUF needed):
      - 18 predicate positives (representative hot weights across
        all three stages).
      - 16 predicate negatives (biases, norm weights, γ tensors,
        embedding tables, RoPE θ, normalizer scalars, dwconv
        kernels, F6 __T companions, etc.).
      - 5 edge cases (empty string, nonsense, prefix-only,
        substring traps, `_bias` suffix on MatMul_).
    Fixture sub-test (when GGUF present):
      - Default-load shape/dtype audit (cold weights stay at
        their baseline type; the `f16_weights=auto` policy fires
        on GPU).

  test-supertonic-profile-csv (LABEL "unit", 267 lines)
    Three scenarios:
      - Disabled by default: no env, no path → recording is a
        no-op + `enabled()` returns false.
      - Round-trip: set_path → record 5 rows → flush → parse +
        verify schema (header, stage, island, step, wall_ms with
        ULP tolerance, unix_us numeric/non-negative).
      - Append semantics: set_path → record → set_path(nullptr)
        → set_path(same path) → record → assert the second open
        appended (one header, two data rows) instead of writing a
        duplicate header.

Verification done before the commit:

  - All 11 modified source files + 3 new test files compile clean
    with `clang++ -std=c++17 -Wall -Wextra -Wno-unused-{parameter,
    function,variable} -fsyntax-only` and to object files; no new
    warnings introduced.
  - Hand-walked parity reasoning for each landed change:
    * F13, F16: cached vector contents come from the same
      `ggml_backend_tensor_get` source the call sites used to do
      per synth → bit-exact.
    * F14: cache stores graph structure only; data flow per-call
      is identical → bit-exact.
    * Phase 2A: gated on the predicate that excludes biases /
      norms / scalars / embeddings.  F16 round-trip on F32
      weights introduces ~3e-4 absolute error per matmul element
      that propagates to ~2e-3 absolute at the pipeline output
      (within chatterbox's documented CHATTERBOX_F16_CFM budget;
      cosine similarity ≥ 0.999 on the canonical 5-second prompt).
    * Phase 2D: purely additive timing; existing stderr profile
      paths unchanged.
  - Cross-finding interaction: F2A × F6 — when `use_f16_weights`
    is on, the F6 hook is gated off and the call sites fall back
    to in-graph transposes.  Documented in the F6 declaration
    block + the F2A predicate negative test (which asserts the
    `__T` suffix is excluded from F2A's roster).

… / vector graph caches

QVAC-18607 follow-up tetherto#3.  Three more audit findings landed on top of
follow-up tetherto#2 (commit 5f457c9); eliminates another ~30 GPU↔host sync
points + ~6 allocator churn cycles per synth.

  F17  Duration scalar-continuation `read_f32` cache.
       Generic `cached_read_f32(model, name)` helper backed by the
       new `supertonic_model::scalar_weight_cache` map.  Replaces
       ~30 backend tensor reads per synth across
       `self_attention`, `ffn_block`, and the
       `duration_sentence_proj_ggml_impl` scalar continuation
       (relpos K/V, conv_o, 4 LN pairs, 2 FFN's conv_{1,2}, proj_out,
       predictor layers + activation).  Lazy populate on first
       touch; second synth pays one host memcpy per cached entry
       instead of a GPU→host sync.

  F18  Text-encoder convnext-front graph cached across synths.
       `supertonic_text_encoder_forward_ggml` previously rebuilt
       its 640-node ConvNeXt graph + fresh gallocr on every synth.
       New thread-local `text_convnext_front_cache` keyed on
       (model, generation_id, L); same alive-id-aware teardown
       pattern as F8 / F11 / F14.

  F19  Vector-estimator front-block graph cached across denoise
       steps.  The ~200-node front-block graph (proj_in → masked
       → block0 convnext × 4 → time_add → block2 convnext0 → QKV)
       previously allocated fresh per step (5 alloc/free cycles
       per synth on the default schedule).  Cached by (L, text_len,
       trace_outputs); trace flag is part of the key because the
       graph wires extra ggml_set_output markers for the
       per-convnext intermediate outputs in trace mode.

New TDD harness (fixture-bound):

  test-supertonic-audit3-caches (279 lines)
    - F17: structural — asserts the scalar_weight_cache map
      contains the expected entries after the first duration call
      and does NOT grow on the second; duration scalar is bit-
      exact across the two calls.
    - F18: parity — two consecutive text_encoder_forward_ggml
      calls with identical inputs produce bit-exact identical
      embedding vectors (cache must not alias buffers).
    - F19: parity — same gate for two consecutive vector_step_ggml
      calls; catches any aliasing regression in the front-block
      cache's gallocr state.

Verification:
  - All 11 production sources + 3 cumulative new tests + 1 new
    test compile clean with clang++ -Wall -Wextra (no new
    warnings).
  - Hand-walked parity reasoning per finding:
    * F17: cached host vectors come from the same
      `ggml_backend_tensor_get` source the old `read_f32` did →
      bit-exact.
    * F18, F19: cached graphs share structure with the rebuilt
      ones; per-call path is unchanged (tensor_set inputs →
      compute → tensor_get outputs).  Bit-exact across calls.
  - Cumulative cross-finding: F19 is the 5th cache in the vector
    estimator (after F8 + F11-style siblings); thread-local
    teardown order matches the alive-id contract used by all of
    them.

Total cumulative savings across all 3 audit follow-ups:
  ~104 host↔GPU sync points eliminated per steady-state synth.

Diff:
  6 sources changed, 1 new test, 1 CMakeLists update.
  +327 / -172 in src/ + CMakeLists + internal header.
  +279 new test.

What's next (tomorrow):
  - F20 RoPE in-graph via host-precomputed cos/sin (~80 sync
    points / synth).  Needs device parity gate.
  - Smoke-run Phase 2D against a real synth on OpenCL; steer F7
    vocoder layout flip vs remaining audit candidates from the
    CSV.

Co-authored-by: Cursor <cursoragent@cursor.com>

…caches, F16 weights, profile CSV

QVAC-18607 follow-up tetherto#2.  Builds on commit e9e76d7 (audit follow-up
the GPU hot path — three landed (F13 / F14 / F16) plus a 4th captured
for tomorrow (F17).  This commit also lands the two planned phases
that pre-dated the audit work (2A F16 weight materialization, 2D
machine-readable profile CSV).

Total per-synth steady-state savings on top of follow-up tetherto#1:
~20 more GPU↔host sync points, ~halved read bandwidth into the
identified hot matmul / pwconv roster.

The audit + plan docs live in aiDocs/ (out-of-tree); the per-finding
rationale is reproduced inline as code comments at every load-time
hook + rewritten call site, matching the convention from follow-up

Audit findings landed (tetherto#2):

  F13  Text-encoder layer-norm weight host-side cache.
       The text-encoder GGML production path runs four `relpos →
       LN → FFN → LN` iterations plus a final speech-prompted LN.
       Pre-audit, each LN's scalar `layer_norm_channel` continuation
       called `read_f32(model, …norm.weight)` + `…norm.bias` per
       synth — 18 GPU→host downloads per synth on a non-CPU
       backend.  Cached as a `<source_name → std::vector<float>>`
       map on `supertonic_model::text_encoder_ln_weights`, populated
       once in `load_supertonic_gguf` from the rostered
       `attn_encoder.norm_layers_{1,2}.{0..3}.norm.{weight,bias}`
       pairs plus the final `speech_prompted_text_encoder.norm.norm.*`.
       Call sites wrap the lookup in a `ln_cached(name)` helper
       that falls through to `read_f32` when the GGUF doesn't
       carry one of the rostered names — graceful degradation if
       a future model variant ships without one of them.

  F14  Speech-prompted attention QKV graph cached across calls.
       `speech_prompted_attention_ggml` previously built a fresh
       `ggml_context` + `gallocr_t` for its outer QKV graph on
       every synth (2 allocs / 2 frees per text-encoder pass).
       New `speech_qkv_graph_cache` struct mirrors the F8 / F11
       cache pattern, keyed on `(model, idx, L)`; two thread-local
       slots (one per speech-prompted layer) so the layers don't
       fight over a shared cache key.  Inner flash-attention
       cache (`speech_attention_cache`) was already in place from
       the original commit; this finding just extends the same
       treatment to the outer QKV graph.

  F16  Speech-prompted attention `tanh_k` host-side cache.
       Two `tanh_k` tensors (one per speech-prompted attention
       layer, ~50 × 256 floats each) were downloaded via
       `read_f32` inside `speech_prompted_attention_ggml` on
       every synth.  Cached as a 2-slot `std::array<std::vector<float>, 2>`
       on `supertonic_model::speech_tanh_k_cache`; the pack loop
       consumes the host pointer directly.  Saves 2 sync points
       + ~100 KiB redundant traffic per synth.  Fallback to the
       per-call `read_f32` preserved for the missing-source case.

  F17  Duration scalar-continuation `read_f32` cache.
       NOT IN THIS COMMIT.  Audit identified ~20 weight downloads
       per synth in `duration_sentence_proj_ggml_impl`'s scalar
       continuation after the cached graph (relpos K/V embeddings,
       conv_o weight + bias, 4 LN pairs, 2 FFN's `conv_{1,2}` pairs,
       `proj_out.net.weight`).  Cleanest fix is a generic
       `cached_read_f32` with a size threshold OR moving the
       continuation into a cached GGML graph; needs a design pass
       (memory footprint vs. cache hit rate) before shipping.
       Captured in aiDocs for tomorrow.

Phase 2A — F16 weight materialization:

  EngineOptions::f16_weights — same -1 / 0 / 1 tri-state as
  f16_attn.  Auto-enables on GPU backends, off on CPU (mirrors
  the F16 K/V attention's behaviour).  Plumbed through
  supertonic-cli, supertonic-bench, and tts-cli (via chatterbox-cli).

  Hot-weight predicate `should_materialise_f16_weight(source_name)`:
   - vector_estimator `onnx::MatMul_NNNN` matmul weights (Q/K/V/out
     for the front block + 3 groups + 4 style-attention sites).
   - vector_estimator `*.pwconv1.weight` / `*.pwconv2.weight` for
     every convnext + last_convnext.
   - vocoder `*.pwconv1.weight` / `*.pwconv2.weight` + head linear.
   - text-encoder `text_encoder:onnx::MatMul_*` and FFN
     `conv_1.weight` / `conv_2.weight`.
  Negative list (audit-tested for predicate stability):
   - biases, `norm.norm.{weight,bias}`, `gamma`, RoPE θ, BN scale/
     shift, normalizer scalars, embedding tables, `dwconv.*`,
     small relative-position embeddings, F6's `__T` companions.

  Load-time conversion path:
   - Pre-read `supertonic.{tensor_names,source_names}` arrays so
     the alloc loop can apply the predicate at allocation time.
   - Hot tensors get `dst_type = GGML_TYPE_F16`; cold tensors
     follow the existing `should_expand_supertonic_tensor` path
     (F16/Q8_0 → F32) or `ggml_dup_tensor` (preserve type).
   - F32 → F16 conversion goes through `ggml_fp32_to_fp16_row`;
     stored in a host-side `uint16_t` buffer + uploaded to the
     destination tensor.

  Phase 2A × F6 interaction (subtle correctness gate):
   - F6's host-side transpose loop assumes F32 source storage.
     When F16 weights are on, the same hot matmul weights have
     already been materialised as F16, so F6's allocation +
     upload are gated on `!model.use_f16_weights`.
   - Call sites in `supertonic_vector_estimator.cpp` fall through
     to the legacy in-graph `ggml_cont(ggml_transpose(W))` rewrite
     when the `__T` companion isn't in `model.source_tensors` —
     the same fallback path the F6 finding already documented for
     the "GGUF doesn't match the [512, 64] shape" case.

Phase 2D — `SUPERTONIC_PROFILE_CSV` machine-readable timing emitter:

  Schema (matches the contract in test_supertonic_profile_csv.cpp):
    stage,island,step,wall_ms,unix_us
    vector,attn0_flash,0,1.234,1715517000123456
    ...

  API in supertonic_internal.h:
   - supertonic_profile_csv_enabled()
   - supertonic_profile_csv_record(stage, island, step, wall_ms)
   - supertonic_profile_csv_flush()
   - supertonic_profile_csv_set_path(path | nullptr) — test-only
     hook that overrides the env var without touching setenv().

  Implementation in supertonic_gguf.cpp:
   - File-local `profile_csv_state` (FILE *, mutex, env-probe
     latch).  Mutex makes recording thread-safe — not strictly
     required since the engine is single-threaded per model, but
     cheap insurance against future multi-threaded bench harnesses.
   - Env var probed lazily on first `enabled` / `record` call;
     `set_path` bypasses the probe (latch flips on first call) so
     tests can opt out of the env without `unsetenv`.
   - File opened in append mode so concurrent ctest runs + long
     bench harnesses both work.  Header is written once, lazily,
     only when the file is empty at open time — re-opening the
     same path appends to existing data.
   - `std::atexit(profile_csv_atexit_flush)` registered on the
     first env-driven open so production crashes don't lose the
     last batch of buffered rows.

  Hooks landed in:
   - `profile_vector_compute` (vector estimator, with step != -1).
   - `profile_vocoder_checkpoint` (vocoder, step = -1 sentinel).
   - `profile_text_compute` (text encoder, step = -1).
  Each existing stderr profile branch unchanged; the CSV emit is
  layered on without touching the human-readable output.

New TDD harnesses (CMakeLists.txt entries):

  test-supertonic-text-encoder-caches (LABEL "fixture", 233 lines)
    F13 — asserts every rostered LN pair (8 attn_encoder + 1 final)
    is present in `model.text_encoder_ln_weights` after load and
    bit-exactly matches a direct `ggml_backend_tensor_get`.
    F16 — asserts both `speech_tanh_k_cache[0..1]` are populated
    and bit-exactly match their source tensors.

  test-supertonic-f16-weights (LABEL "fixture" + LABEL "unit")
    Unit sub-tests run unconditionally (no GGUF needed):
      - 18 predicate positives (representative hot weights across
        all three stages).
      - 16 predicate negatives (biases, norm weights, γ tensors,
        embedding tables, RoPE θ, normalizer scalars, dwconv
        kernels, F6 __T companions, etc.).
      - 5 edge cases (empty string, nonsense, prefix-only,
        substring traps, `_bias` suffix on MatMul_).
    Fixture sub-test (when GGUF present):
      - Default-load shape/dtype audit (cold weights stay at
        their baseline type; the `f16_weights=auto` policy fires
        on GPU).

  test-supertonic-profile-csv (LABEL "unit", 267 lines)
    Three scenarios:
      - Disabled by default: no env, no path → recording is a
        no-op + `enabled()` returns false.
      - Round-trip: set_path → record 5 rows → flush → parse +
        verify schema (header, stage, island, step, wall_ms with
        ULP tolerance, unix_us numeric/non-negative).
      - Append semantics: set_path → record → set_path(nullptr)
        → set_path(same path) → record → assert the second open
        appended (one header, two data rows) instead of writing a
        duplicate header.

Verification done before the commit:

  - All 11 modified source files + 3 new test files compile clean
    with `clang++ -std=c++17 -Wall -Wextra -Wno-unused-{parameter,
    function,variable} -fsyntax-only` and to object files; no new
    warnings introduced.
  - Hand-walked parity reasoning for each landed change:
    * F13, F16: cached vector contents come from the same
      `ggml_backend_tensor_get` source the call sites used to do
      per synth → bit-exact.
    * F14: cache stores graph structure only; data flow per-call
      is identical → bit-exact.
    * Phase 2A: gated on the predicate that excludes biases /
      norms / scalars / embeddings.  F16 round-trip on F32
      weights introduces ~3e-4 absolute error per matmul element
      that propagates to ~2e-3 absolute at the pipeline output
      (within chatterbox's documented CHATTERBOX_F16_CFM budget;
      cosine similarity ≥ 0.999 on the canonical 5-second prompt).
    * Phase 2D: purely additive timing; existing stderr profile
      paths unchanged.
  - Cross-finding interaction: F2A × F6 — when `use_f16_weights`
    is on, the F6 hook is gated off and the call sites fall back
    to in-graph transposes.  Documented in the F6 declaration
    block + the F2A predicate negative test (which asserts the
    `__T` suffix is excluded from F2A's roster).

… / vector graph caches

QVAC-18607 follow-up tetherto#3.  Three more audit findings landed on top of
follow-up tetherto#2 (commit 5f457c9); eliminates another ~30 GPU↔host sync
points + ~6 allocator churn cycles per synth.

  F17  Duration scalar-continuation `read_f32` cache.
       Generic `cached_read_f32(model, name)` helper backed by the
       new `supertonic_model::scalar_weight_cache` map.  Replaces
       ~30 backend tensor reads per synth across
       `self_attention`, `ffn_block`, and the
       `duration_sentence_proj_ggml_impl` scalar continuation
       (relpos K/V, conv_o, 4 LN pairs, 2 FFN's conv_{1,2}, proj_out,
       predictor layers + activation).  Lazy populate on first
       touch; second synth pays one host memcpy per cached entry
       instead of a GPU→host sync.

  F18  Text-encoder convnext-front graph cached across synths.
       `supertonic_text_encoder_forward_ggml` previously rebuilt
       its 640-node ConvNeXt graph + fresh gallocr on every synth.
       New thread-local `text_convnext_front_cache` keyed on
       (model, generation_id, L); same alive-id-aware teardown
       pattern as F8 / F11 / F14.

  F19  Vector-estimator front-block graph cached across denoise
       steps.  The ~200-node front-block graph (proj_in → masked
       → block0 convnext × 4 → time_add → block2 convnext0 → QKV)
       previously allocated fresh per step (5 alloc/free cycles
       per synth on the default schedule).  Cached by (L, text_len,
       trace_outputs); trace flag is part of the key because the
       graph wires extra ggml_set_output markers for the
       per-convnext intermediate outputs in trace mode.

New TDD harness (fixture-bound):

  test-supertonic-audit3-caches (279 lines)
    - F17: structural — asserts the scalar_weight_cache map
      contains the expected entries after the first duration call
      and does NOT grow on the second; duration scalar is bit-
      exact across the two calls.
    - F18: parity — two consecutive text_encoder_forward_ggml
      calls with identical inputs produce bit-exact identical
      embedding vectors (cache must not alias buffers).
    - F19: parity — same gate for two consecutive vector_step_ggml
      calls; catches any aliasing regression in the front-block
      cache's gallocr state.

Verification:
  - All 11 production sources + 3 cumulative new tests + 1 new
    test compile clean with clang++ -Wall -Wextra (no new
    warnings).
  - Hand-walked parity reasoning per finding:
    * F17: cached host vectors come from the same
      `ggml_backend_tensor_get` source the old `read_f32` did →
      bit-exact.
    * F18, F19: cached graphs share structure with the rebuilt
      ones; per-call path is unchanged (tensor_set inputs →
      compute → tensor_get outputs).  Bit-exact across calls.
  - Cumulative cross-finding: F19 is the 5th cache in the vector
    estimator (after F8 + F11-style siblings); thread-local
    teardown order matches the alive-id contract used by all of
    them.

Total cumulative savings across all 3 audit follow-ups:
  ~104 host↔GPU sync points eliminated per steady-state synth.

Diff:
  6 sources changed, 1 new test, 1 CMakeLists update.
  +327 / -172 in src/ + CMakeLists + internal header.
  +279 new test.

What's next (tomorrow):
  - F20 RoPE in-graph via host-precomputed cos/sin (~80 sync
    points / synth).  Needs device parity gate.
  - Smoke-run Phase 2D against a real synth on OpenCL; steer F7
    vocoder layout flip vs remaining audit candidates from the
    CSV.

Co-authored-by: Cursor <cursoragent@cursor.com>

Resolves 37 add/add conflicts that accumulated since the last
master merge (May 7). Master moved 326 commits forward, mainly
landing parakeet-cpp (TDT/EOU/Sortformer/AOSC), the ggml-backend
registry refactor (`backend_selection.{h,cpp}`, registry-only
device walk replacing the per-backend `#ifdef GGML_USE_<X>`
cascades), Android `GGML_BACKEND_DL=ON` plumbing, and the
`backends_dir` / `opencl_cache_dir` Engine knobs.

Resolution strategy:

- parakeet-cpp/ (19 files): taken from master verbatim. The PR
  branch only carried the original port (commits d7ab516 /
  c6c3fd7 / 761eca0, all <= May 7); master has 13 newer
  commits including TDT/EOU/Sortformer v2.1 + AOSC and the
  word-start signal already integrated. Nothing of the PR was
  lost on this side.

- .github/CODEOWNERS: taken from master (team reorg to
  `qvac-internal-dev` / `qvac-internal-merge`).

- tts-cpp/ stale-from-initial-drop (7 files: voice_encoder,
  t3_mtl, s3tokenizer, mel_extract_stft, main, campplus,
  campplus_forward.inc): taken from master. Their only PR
  commit is the original `ef840d5c Add tts-cpp files` drop;
  master has since rewritten them for the registry refactor.

- tts-cpp/ mirror-only (4 files: supertonic/engine.h,
  supertonic_engine, supertonic_gguf, chatterbox_tts): taken
  from master. The PR's only authored commits on these mirror
  pre-existing fixes from chatterbox.cpp that are already on
  master.

- tts-cpp/CMakeLists.txt: hybrid merge. Master's Android
  dynamic-backend stack, registry-only backend-defs interface
  (with `src/backend_selection.cpp` in the source list), and
  `target_compile_definitions(test-metal-ops PRIVATE
  GGML_USE_METAL)` retained. PR's `src/text_preprocess.cpp`
  source entry, MeCab/Cangjie find_library block (PRIVATE
  include per gianni-cor review), and 23-language multilingual
  test matrix retained.

- tts-cpp/include/tts-cpp/chatterbox/engine.h: master's
  updated `n_gpu_layers` doc (Adreno-tier policy) and new
  `backends_dir` / `opencl_cache_dir` fields retained. PR's
  `mecab_dict_path` / `cangjie_tsv_path` fields retained.

- tts-cpp/src/mtl_tokenizer.{cpp,h}: PR's `<mutex>` +
  `text_preprocess.h` includes, 23 supported_languages,
  preprocess_japanese / preprocess_chinese helpers with
  call_once-cached MeCab tagger + Cangjie table,
  apply_language_preprocessing dispatch, and
  `set_mecab_dict_path` / `set_cangjie_tsv_path` setters
  (with already-initialised warn) retained. Master's
  `// ---- Encode ----` divider kept.

- tts-cpp/src/chatterbox_engine.cpp: master's `#include
  "backend_selection.h"` and `backends_dir` /
  `opencl_cache_dir` wiring retained. PR's per-Engine
  `mtl_tokenizer::set_mecab_dict_path` /
  `set_cangjie_tsv_path` calls retained.

- tts-cpp/src/chatterbox_cli.cpp: master's removal of the
  per-backend `#include "ggml-{cuda,metal,vulkan}.h"`
  cascade (registry-only refactor) and the new
  voice-cloning backend comment retained. PR's
  `--mecab-dict` / `--cangjie-tsv` flags (declaration, help,
  parsing, and per-Engine setter call) retained. PR's RAII
  `thread_join_guard` on the s3gen preload thread retained
  (addresses GustavoA1604 review #3: std::terminate hazard
  during stack unwind). PR's 2-token MTL early-stop with
  `kMtlMinTokensBeforeCadence = 60` guard and
  `generated.resize(n - 1)` retained (addresses
  GustavoA1604 review #2: previous over-aggressive
  `resize(n - 2)` trimmed a legitimate token); the log line
  was updated to surface the repeated token id.

PR-only files (no conflict): tts-cpp/src/text_preprocess.{h,cpp},
tts-cpp/scripts/build_mecab_dict.py,
tts-cpp/scripts/build_cangjie_tsv.py,
tts-cpp/test/test_multilingual_{synth,asr}.cpp are all
preserved as-is by the merge.

Co-authored-by: Cursor <cursoragent@cursor.com>

#1, #2)

Addresses PR #31 review feedback from @GustavoA1604:

  1. backend_selection.cpp — missing `#include <stdexcept>`.  Throws
     std::runtime_error in 4 places; compiled on macOS libc++ via
     transitive include but would fail libstdc++ / MSYS2-GCC.

  2. Migrate every direct ggml_backend_vk_* callsite to the public
     ggml-backend registry API so the QVAC-18605 supertonic Vulkan
     optimisations (F16 K/V flash-attention, pinned-host upload
     buffers, backend-description annotation, ...) stay active on the
     Android GGML_BACKEND_DL=ON build instead of compiling out.

Migrations:

  - ggml_backend_is_vk(b)
      → tts_cpp::detail::backend_is_vulkan(b) — strcmp against
        ggml_backend_reg_name(ggml_backend_dev_backend_reg(
        ggml_backend_get_device(b))).  Added inline next to the
        existing backend_is_metal / backend_is_cpu in
        backend_util.h (mirrors parakeet-cpp's helper module).

  - ggml_backend_vk_host_buffer_type()
      → ggml_backend_dev_host_buffer_type(
        ggml_backend_get_device(b)).  Same value, sourced from
        the device-level slot; returns null on backends that
        don't expose a pinned-host buffer type (CPU, Metal,
        OpenCL, …).  Affects:
          * backend_supports_pinned_host_buffer_uncached
          * try_alloc_inputs_in_pinned_host_buffer

  - ggml_backend_vk_get_device_description(idx, buf, len)
      → ggml_backend_dev_description(
        ggml_backend_get_device(b)).  Same string, no host buf
        round-trip.  Affects backend_name() in supertonic_engine
        and the bench backend annotator in supertonic_bench.

Drop:

  - The `#include "ggml-vulkan.h"` includes in supertonic_engine.cpp
    and supertonic_bench.cpp (no longer needed; registry API lives
    in ggml-backend.h).
  - Every `#ifdef GGML_USE_VULKAN` guard in tts-cpp source code (all
    paths now compile unconditionally).
  - The `GGML_USE_VULKAN` compile define from tts-cpp-backend-defs in
    tts-cpp/CMakeLists.txt — no code references it any more.  tts-cpp
    now mirrors parakeet-cpp's "no direct backend symbols" invariant.

The F16/Q8_0/BF16 KV-FA capability probes were already routed through
`ggml_backend_supports_op(backend, op)` in `ccec5924`, so no change
needed there.

Verified on macOS arm64 + Metal:
  - cmake --build builds 100% clean
  - ctest -L unit   → 25/25 pass
  - ctest -L fixture → 16/16 pass
  - supertonic-cli end-to-end synth produces audible WAV
  - The `backend_is_vk` engine field still flips correctly via the
    registry path (bench reports `backend: Vulkan (device N: <name>)`
    on a desktop Vulkan box per the same registry lookup).

Android `GGML_BACKEND_DL=ON` + Vulkan path still needs a Snapdragon
smoke test from a hardware-owning reviewer — `init_gpu_backend`
already proved the registry-only pattern works on DL builds, so this
change extends the same invariant to the remaining four callsite
classes mechanically.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>