feat(apr-cli): apr trace --json --payload — wire JSON output for FAST PATH Step 2 exit criterion by noahgift · Pull Request #1401 · paiml/aprender

noahgift · 2026-05-02T10:02:25Z

TL;DR

apr trace --json --payload <gguf> was silently ignoring --json when --payload was set. The FAST PATH Step 2 exit criterion in paiml/claude-code-parity-apr explicitly calls for JSON output. Now mechanically satisfied.

Schema

{
  "format": "GGUF (qwen3moe)",
  "architecture": "qwen3moe",
  "num_layers": 48, "hidden_dim": 2048, "vocab_size": 151936,
  "prompt": "What is 2+2?",
  "encoded_tokens": [...],
  "embedding": { "min": ..., "max": ..., "mean": ..., "std_dev": ..., "count": 2048 },
  "layers": [
    { "layer_idx": 0,
      "attn_norm": {...}, "qkv": {...}, "attn_out": {...},
      "ffn_norm": {...}, "ffn_out": {...}, "output": {...} },
    /* 47 more */
  ],
  "final_norm": {...},
  "logits": { "vocab_size": 151936, "l2_norm": 1025.75, "top_k": [...] }
}

Live verification

$ apr trace --json --payload <17.3 GB Qwen3-Coder GGUF> 2>/dev/null | jq '
  {arch: .architecture, layers: (.layers | length),
   all_finite: ([.layers[].output.std_dev] | all(isfinite))}'
{
  "arch": "qwen3moe",
  "layers": 48,
  "all_finite": true
}

Implementation notes

New handle_special_modes_with_json — old handle_special_modes preserved as thin wrapper (existing test callers unbroken).
New run_traced_inference_json — mirrors text-mode trace but emits JSON via serde_json::to_string_pretty.
Skips the Model: ... / Contract: ... preamble that would break | jq consumers.

Hot-path safety

apr trace --payload (no --json): text mode UNCHANGED
apr trace --json (no --payload): static-layer JSON UNCHANGED
Only branches when both --json && --payload set
All 5 callers of handle_special_modes continue to work

What this PR does NOT ship

Custom prompt flag
Per-token-position trace (LAST token only, per existing semantics)
Sub-FFN MoE breakdown
SafeTensors JSON path (same encoding, different format string)

Test plan

cargo check -p apr-cli --features inference — clean
cargo clippy -p apr-cli --features inference --lib -- -D warnings — clean
cargo fmt -p apr-cli --check — clean
Live apr trace --json --payload <Qwen3-Coder GGUF> produces valid JSON, parses with python json.load + jq
All 48 transformer_block entries have finite L2 norms (FAST PATH Step 2 exit criterion)

Refs

M32d Step 2 exit criterion (M34 FAST PATH plan)
feat(apr-cli): M32d Step 2.5 — wire apr trace --payload to forward_qwen3_moe_traced #1226 (Step 2.5: apr trace dispatch)
feat(aprender-serve): M32d Step 2 — forward_qwen3_moe_traced for per-layer ActivationStats #1222 (Step 2: forward_qwen3_moe_traced)

🤖 Generated with Claude Code

… PATH Step 2 exit criterion `apr trace --json --payload <gguf>` was silently ignoring `--json` when `--payload` was set, falling back to the human-readable text format. The FAST PATH Step 2 exit criterion in paiml/claude-code-parity-apr docs/specifications/claude-code-parity-apr-poc.md explicitly says: "apr trace --json --payload <gguf> --prompt 'What is 2+2?' returns non-null output_stats for every transformer_block_N entry, with finite L2 norms." Now mechanically satisfied. Schema: ```jsonc { "format": "GGUF (qwen3moe)", "architecture": "qwen3moe", "num_layers": 48, "hidden_dim": 2048, "vocab_size": 151936, "num_heads": 32, "num_kv_heads": 4, "prompt": "What is 2+2?", "encoded_tokens": [3838, 374, 220, 17, 10, 17, 30], "embedding": { "min": ..., "max": ..., "mean": ..., "std_dev": ..., "nan_count": 0, "inf_count": 0, "zero_count": 0, "count": 2048 }, "layers": [ { "layer_idx": 0, "attn_norm": {...stats...}, "qkv": {...stats...}, "attn_out": {...}, "ffn_norm": {...}, "ffn_out": {...}, "output": {...} }, /* 47 more, one per decoder layer */ ], "final_norm": {...stats...}, "logits_stats": {...stats...}, "logits": { "vocab_size": 151936, "l2_norm": 1025.7530, "top_k": [{"token_id": 3555, "logit": 16.96}, ...] } } ``` Implementation ============== - `handle_special_modes_with_json` (new) — JSON-aware variant of `handle_special_modes`. Old function preserved as a thin wrapper so existing test callers don't break. - `run_traced_inference_json` (new) — JSON output path. Mirrors `run_traced_inference_gguf` for trace computation but emits one JSON object via serde_json::to_string_pretty. - Skips the human-readable "Model: ..." / "Contract: ..." preamble that `resolve_model_path` + `preflight_contract_check` would print — those would break `apr trace --json --payload | jq` consumers. Live verification on lambda-vector RTX 4090 ============================================ $ apr trace --json --payload ~/.cache/pacha/models/2b88b180a790988f.gguf \ 2>/dev/null | python3 -c ' import sys, json d = json.load(sys.stdin) print(f"arch: {d[\"architecture\"]}") print(f"num_layers: {d[\"num_layers\"]}") print(f"layers in payload: {len(d[\"layers\"])}") all_finite = all( isinstance(la[\"output\"][\"std_dev\"], (int, float)) and abs(la[\"output\"][\"std_dev\"]) < float(\"inf\") for la in d[\"layers\"] ) print(f"all 48 layers finite: {all_finite}") ' arch: qwen3moe num_layers: 48 layers in payload: 48 all 48 layers finite: True Stdout is now strictly valid JSON; `2>/dev/null` discards BOS-FALLBACK warnings on stderr. What this PR does NOT ship ========================== - Custom prompt via `--prompt <str>` flag (test prompt is hardcoded "What is 2+2?"; matches text-mode default). - Per-token-position trace (only LAST token captured per the GGUF forward_traced + forward_qwen3_moe_traced semantics). - Sub-FFN MoE breakdown (router output, per-expert contribution) — those are zero in qwen3_moe traced forward; left for Step 4 work. - SafeTensors JSON output — same encoding works there, just the format string differs. Hot-path safety =============== - Existing `apr trace --payload` (no --json) text mode unchanged. - Existing `apr trace --json` (no --payload) static-layer JSON mode unchanged — `handle_special_modes_with_json` only branches when BOTH json && payload are set. - All 5 callers of `handle_special_modes` continue to work (signature preserved via thin wrapper). Refs M32d Step 2 exit criterion (M34 FAST PATH plan) Refs PR #1226 (Step 2.5: apr trace dispatch — wired qwen3_moe arch) Refs PR #1222 (Step 2: forward_qwen3_moe_traced — supplies the data) Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

Locks in the JSON output schema that satisfies the M34 FAST PATH Step 2 exit criterion. Asserts: - stdout is valid JSON (no preamble lines breaking jq consumers) - all 11 top-level fields present (format, architecture, num_layers, hidden_dim, vocab_size, prompt, encoded_tokens, embedding, layers, final_norm, logits) - 48 layers (Qwen3-Coder-30B-A3B-Instruct) - per-layer 7 fields present (layer_idx + 6 stat slots) - every layer.output.std_dev is finite - every layer.output.nan_count == 0 && inf_count == 0 - logits.l2_norm is finite and > 0 Skipped when GGUF or apr binary absent (fixture-absent ≠ defect, per M32c.2.2.2.1.4 convention). Live PASS on lambda-vector RTX 4090 in 5.38s. Refs M32d Step 2 exit criterion (M34 FAST PATH plan) Refs the JSON schema in this PR's main commit Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

…e_theta + chat template Squashes 4 substantive M32d FAST PATH fixes (Step 5 + 5b + 6 + 7) + regression test + evidence into a single commit on top of fresh main. Replaces the original messy stacked-PR chain that conflicted on rebase after sibling PRs (#1401, #1405) landed. Live verification on lambda-vector RTX 4090 (post-rebuild): $ apr run <Qwen3-Coder-30B-A3B-Instruct-Q4_K_M.gguf> \ --prompt "What is 2+2?" --max-tokens 8 Output: 2 + 2 = 4 Completed in 40.24s (cached) Step 5 — per-head Q/K RMSNorm in forward_qwen3_moe (rank-3 prior, 15%) ==================================================================== Qwen3 GH-279 per-head Q/K RMSNorm was wired into the dense path (adaptive_ffn.rs:174-179) but missing from forward_qwen3_moe.rs. Now applied AFTER bias, BEFORE RoPE — same code as adaptive_ffn. Pre-fix: layer std-dev grew 40× over 48 layers (signature of attention scores compounding without per-head Q/K norm). Output `%%%%%%%%`. Step 5b — rope_theta default 10K → 1M for qwen3_moe (rank-4 prior, 10%) ======================================================================= GGUF for Qwen3-Coder-30B-A3B-Instruct-Q4_K_M ships WITHOUT `qwen3moe.rope.freq_base` metadata. config.rs's default lookup had `"qwen2" | "qwen3" => 1_000_000.0` but no qwen3_moe entry — fell to catch-all 10K. Off by 100×. Added qwen3_moe to the 1M arm. Step 6 — chat template (qwen3_moe → ChatML, no <think>) ======================================================== `detect_format_from_name` routed any "qwen3" name to Qwen3NoThink (PMAT-181), which pre-injects empty `<think>\n</think>\n` into the assistant turn. Qwen3-Coder does NOT have thinking mode (verified via the Jinja `tokenizer.chat_template` in the GGUF) — empty think block caused the model to emit `<|endoftext|>` immediately. Route qwen3_moe to plain ChatML before the generic qwen3 → NoThink rule. PMAT-181 preserved for thinking-mode dense Qwen3. Step 7 — sync forward_qwen3_moe_traced with Step 5 Q/K norm ============================================================ forward_qwen3_moe_traced (created in PR #1222 on main) was authored mirroring the OLD pre-Q/K-norm forward_qwen3_moe. Without sync, `apr trace --payload` shows DIFFERENT numerics from `apr run` — silent diagnostic-vs-production drift. Mirror the same Q/K norm into the traced variant. Component priors discharge status (M34 FAST PATH) | Rank | Component | Prior | Status | |------|-----------|-------|------------| | 1 | LAYOUT | 30% | not at issue | | 2 | Q4_K_M | 20% | not at issue | | 3 | Q/K norm | 15% | FIXED (this commit) | | 4 | RoPE θ | 10% | FIXED (this commit) | | 5 | router sm | 10% | not at issue | | 6 | token emb | 10% | not at issue | | 7 | other | 5% | n/a | | n/a | chat tpl | n/a | FIXED (this commit) | Output transition pre-fix → "%%%%%%%%" (gibberish) + Step 5 → "Human: What is 2+" (coherent English, partial) + Step 5b → "Human: What is 2+2?" (full prompt reproduced) + Step 6 → "2 + 2 = 4" (correct answer) + Step 7 → diagnostic trace matches production Multi-domain verification (also passes): "Capital of France:" → "The capital of France is Paris." "Translate to Spanish: Hello world" → "¡Hola mundo!" "Count to 5:" → "1, 2, 3, 4, 5" "Solve x^2 - 5x + 6 = 0:" → "I need to solve the quadratic equation x² - 5x + 6 = 0..." Hot-path safety - Production text-generation path (`apr run` → run_qwen3_moe_generate → forward_qwen3_moe) now applies the norm. - `apr trace --payload` (forward_qwen3_moe_traced) syncs the same fix. - Sibling tests pass unchanged. - `forward_qwen3_moe_traced` reads `self.config.rope_theta` which is set at model load from the default lookup — Step 5b auto-applies via config. - Dense Qwen3 path UNCHANGED (Qwen3NoThink preserved for thinking-mode variants). Regression test `crates/aprender-serve/tests/qwen3_moe_qk_norm_regression.rs` F-QW3-MOE-STEP5-001 asserts the context-awareness invariant: two distinct prompts must produce distinct argmax tokens, top-2 logit gap < 50. Live PASS on lambda-vector RTX 4090 in 6.60s. Stack research - HuggingFace transformers Qwen3MoeForCausalLM applies per-head q_norm/k_norm in Qwen3MoeAttention.forward - llama.cpp ggml_qwen3_moe_kv_norm in llama-arch.cpp does the same (attn_q_norm.weight / attn_k_norm.weight) - HF Qwen3MoeConfig.rope_theta default = 1_000_000.0 - Qwen3-Coder Jinja chat_template generation prompt is plain `<|im_start|>assistant\n` (no thinking) Refs M32d FAST PATH plan (M34, paiml/claude-code-parity-apr) Refs GH-279 (Qwen3 per-head Q/K RMSNorm) Refs PMAT-181 (Qwen3NoThink preserved for thinking variants) Refs FALSIFY-QW3-MOE-FORWARD-003 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

…e_theta + chat template (#1228) Squashes 4 substantive M32d FAST PATH fixes (Step 5 + 5b + 6 + 7) + regression test + evidence into a single commit on top of fresh main. Replaces the original messy stacked-PR chain that conflicted on rebase after sibling PRs (#1401, #1405) landed. Live verification on lambda-vector RTX 4090 (post-rebuild): $ apr run <Qwen3-Coder-30B-A3B-Instruct-Q4_K_M.gguf> \ --prompt "What is 2+2?" --max-tokens 8 Output: 2 + 2 = 4 Completed in 40.24s (cached) Step 5 — per-head Q/K RMSNorm in forward_qwen3_moe (rank-3 prior, 15%) ==================================================================== Qwen3 GH-279 per-head Q/K RMSNorm was wired into the dense path (adaptive_ffn.rs:174-179) but missing from forward_qwen3_moe.rs. Now applied AFTER bias, BEFORE RoPE — same code as adaptive_ffn. Pre-fix: layer std-dev grew 40× over 48 layers (signature of attention scores compounding without per-head Q/K norm). Output `%%%%%%%%`. Step 5b — rope_theta default 10K → 1M for qwen3_moe (rank-4 prior, 10%) ======================================================================= GGUF for Qwen3-Coder-30B-A3B-Instruct-Q4_K_M ships WITHOUT `qwen3moe.rope.freq_base` metadata. config.rs's default lookup had `"qwen2" | "qwen3" => 1_000_000.0` but no qwen3_moe entry — fell to catch-all 10K. Off by 100×. Added qwen3_moe to the 1M arm. Step 6 — chat template (qwen3_moe → ChatML, no <think>) ======================================================== `detect_format_from_name` routed any "qwen3" name to Qwen3NoThink (PMAT-181), which pre-injects empty `<think>\n</think>\n` into the assistant turn. Qwen3-Coder does NOT have thinking mode (verified via the Jinja `tokenizer.chat_template` in the GGUF) — empty think block caused the model to emit `<|endoftext|>` immediately. Route qwen3_moe to plain ChatML before the generic qwen3 → NoThink rule. PMAT-181 preserved for thinking-mode dense Qwen3. Step 7 — sync forward_qwen3_moe_traced with Step 5 Q/K norm ============================================================ forward_qwen3_moe_traced (created in PR #1222 on main) was authored mirroring the OLD pre-Q/K-norm forward_qwen3_moe. Without sync, `apr trace --payload` shows DIFFERENT numerics from `apr run` — silent diagnostic-vs-production drift. Mirror the same Q/K norm into the traced variant. Component priors discharge status (M34 FAST PATH) | Rank | Component | Prior | Status | |------|-----------|-------|------------| | 1 | LAYOUT | 30% | not at issue | | 2 | Q4_K_M | 20% | not at issue | | 3 | Q/K norm | 15% | FIXED (this commit) | | 4 | RoPE θ | 10% | FIXED (this commit) | | 5 | router sm | 10% | not at issue | | 6 | token emb | 10% | not at issue | | 7 | other | 5% | n/a | | n/a | chat tpl | n/a | FIXED (this commit) | Output transition pre-fix → "%%%%%%%%" (gibberish) + Step 5 → "Human: What is 2+" (coherent English, partial) + Step 5b → "Human: What is 2+2?" (full prompt reproduced) + Step 6 → "2 + 2 = 4" (correct answer) + Step 7 → diagnostic trace matches production Multi-domain verification (also passes): "Capital of France:" → "The capital of France is Paris." "Translate to Spanish: Hello world" → "¡Hola mundo!" "Count to 5:" → "1, 2, 3, 4, 5" "Solve x^2 - 5x + 6 = 0:" → "I need to solve the quadratic equation x² - 5x + 6 = 0..." Hot-path safety - Production text-generation path (`apr run` → run_qwen3_moe_generate → forward_qwen3_moe) now applies the norm. - `apr trace --payload` (forward_qwen3_moe_traced) syncs the same fix. - Sibling tests pass unchanged. - `forward_qwen3_moe_traced` reads `self.config.rope_theta` which is set at model load from the default lookup — Step 5b auto-applies via config. - Dense Qwen3 path UNCHANGED (Qwen3NoThink preserved for thinking-mode variants). Regression test `crates/aprender-serve/tests/qwen3_moe_qk_norm_regression.rs` F-QW3-MOE-STEP5-001 asserts the context-awareness invariant: two distinct prompts must produce distinct argmax tokens, top-2 logit gap < 50. Live PASS on lambda-vector RTX 4090 in 6.60s. Stack research - HuggingFace transformers Qwen3MoeForCausalLM applies per-head q_norm/k_norm in Qwen3MoeAttention.forward - llama.cpp ggml_qwen3_moe_kv_norm in llama-arch.cpp does the same (attn_q_norm.weight / attn_k_norm.weight) - HF Qwen3MoeConfig.rope_theta default = 1_000_000.0 - Qwen3-Coder Jinja chat_template generation prompt is plain `<|im_start|>assistant\n` (no thinking) Refs M32d FAST PATH plan (M34, paiml/claude-code-parity-apr) Refs GH-279 (Qwen3 per-head Q/K RMSNorm) Refs PMAT-181 (Qwen3NoThink preserved for thinking variants) Refs FALSIFY-QW3-MOE-FORWARD-003 Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>

…d discharge audit-trail bump (#1078) Source-of-truth bytes pushed by the companion repo. M22 paired-mirror guard via pin.lock (sha256 byte-identity, will be refreshed in companion PR). Net change: bumps top-level contract YAML from v1.22.0 to v1.23.0 with one new status_history entry (M35) recording M32d's functional discharge on aprender main as commit 5235aae (#1228 squash). What M35 records ================ M32d numerical-parity bundle landed across multiple aprender PRs: #1222 (Step 2) forward_qwen3_moe_traced diagnostic surface #1226 (Step 2.5) `apr trace --payload` qwen3_moe dispatch (squashed into #1222) #1242 RUSTSEC-2026-0114 audit unblocker #1401 (Step 2 JSON) `apr trace --json --payload` JSON output (FAST PATH Step 2 exit-criterion shape) #1228 (THE BUNDLE) Step 5 + 5b + 6 + 7 + regression test + evidence — squashed into one commit on main: - per-head Q/K RMSNorm in forward_qwen3_moe (rank-3 prior, 15%) - rope_theta 10K → 1M for qwen3_moe (rank-4 prior, 10%) - chat template: qwen3_moe → ChatML (no `<think>` injection) - sync forward_qwen3_moe_traced with Step 5 - F-QW3-MOE-STEP5-001 regression test - evidence/m32d-discharge-2026-05-01/ Live evidence on lambda-vector RTX 4090 against the 17.3 GB Qwen3-Coder-30B-A3B-Instruct-Q4_K_M.gguf: $ apr run --prompt "What is 2+2?" --max-tokens 8 Output: 2 + 2 = 4 $ apr run --prompt "Capital of France:" --max-tokens 30 Output: The capital of France is Paris. $ apr run --prompt "Translate to Spanish: Hello world" --max-tokens 30 Output: ¡Hola mundo! $ apr run --prompt "Solve x^2 - 5x + 6 = 0:" --max-tokens 30 Output: I need to solve the quadratic equation x² - 5x + 6 = 0. I can solve this by factoring. Output transition timeline: pre-fix "%%%%%%%%" + Step 5 "Human: What is 2+" + Step 5b "Human: What is 2+2?" + Step 6 "2 + 2 = 4" M34 FAST PATH actual cost: 5 PRs / ~6 hours wall — **lucky-case bound** of the 4-6 PRs / 2-3 days estimate. What M35 does NOT discharge ============================ - Cosine vs HF FP16 measurement (operator-confirm — ~60 GB download). The formal flip of `qwen3-moe-forward-v1` v1.3.0 DRAFT → v1.4.0 ACTIVE_RUNTIME waits on that measurement. - GPU MoE path (no forward_qwen3_moe_gpu; CUDA/wgpu kernels TBD). - Other Qwen3-MoE variants. Refs aprender commit 5235aae (#1228) Refs companion M34 (v1.21.0 → v1.22.0 plan) Refs PMAT-CCPA-PARITY-001 Refs M22 paired-mirror invariant Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

…CHARGE (#1409) Status flips DRAFT → ACTIVE_ALGORITHM_LEVEL. M32d numerical parity is functionally discharged on aprender main as of PR #1228 squash 5235aae (2026-05-02 13:42 UTC). Output transition on lambda-vector RTX 4090 against the cached 17.3 GB Qwen3-Coder-30B-A3B- Instruct-Q4_K_M.gguf: pre-fix "%%%%%%%%" (gibberish, repeated argmax) + Step 5 "Human: What is 2+" (coherent English, partial) + Step 5b "Human: What is 2+2?" (full prompt reproduced) + Step 6 "2 + 2 = 4" (correct answer) Multi-domain dogfood (math/geography/translation/code) all correct. Why ACTIVE_ALGORITHM_LEVEL not ACTIVE_RUNTIME ============================================== Per the v1.3.0 (M32d.0) parity-strategy decision, full ACTIVE_RUNTIME discharge requires: 1. F-QW3-MOE-PARITY-001: cosine ≥ 0.99 vs HF FP16 reference logits 2. F-QW3-MOE-PARITY-002: argmax matches llama.cpp top-1 #1 requires running scripts/generate_qwen3_moe_fp16_logits.py which is operator-confirm pending (~60 GB HF download + ~30 min on 30B-A3B multi-device offload). ACTIVE_ALGORITHM_LEVEL is the right intermediate state: forward path is functionally correct (verified by output quality across diverse prompts), but the formal cosine-vs-HF gate hasn't fired yet. Component priors verified empirically (M34 FAST PATH plan) ========================================================== rank-3 Q/K norm (15%) FIXED #1228 Step 5 rank-4 RoPE θ (10%) FIXED #1228 Step 5b outside-priors FIXED #1228 Step 6 (chat template wrapping) The diagnostic surface from PRs #1222 (Step 2) + #1226 (Step 2.5) + #1401 (Step 2 JSON wire) named rank-3 directly via the 40× std-growth signature without needing the HF FP16 fixture. Step 1 of the original plan was bypassed. M34 FAST PATH cost ================== Outcome PRs Wall-clock ACTUAL 5 ~6 hours Lucky estimate 4-6 2-3 days Realistic 8-10 4-6 days Pessimistic 12-15 1-2 weeks Came in at the lucky-case bound. Refs aprender PR #1228 commit 5235aae Refs companion `paiml/claude-code-parity-apr` M35 status_history Refs `project_m32d_discharge_2026_05_02.md` (memory) Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>

noahgift enabled auto-merge (squash) May 2, 2026 10:02

noahgift merged commit be396c6 into main May 2, 2026
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noahgift deleted the feat/apr-trace-json-payload-output branch May 2, 2026 11:58

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feat(apr-cli): apr trace --json --payload — wire JSON output for FAST PATH Step 2 exit criterion#1401

feat(apr-cli): apr trace --json --payload — wire JSON output for FAST PATH Step 2 exit criterion#1401
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feat/apr-trace-json-payload-output

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noahgift commented May 2, 2026

TL;DR

Schema

Live verification

Implementation notes

Hot-path safety

What this PR does NOT ship

Test plan

Refs

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