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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

.omo/boulder.json

@@ -0,0 +1,16 @@
+{
+  "schema_version": 2,
+  "active_work_id": null,
+  "works": {
+    "qwen3-dense-w8a16-quantization": {
+      "work_id": "qwen3-dense-w8a16-quantization",
+      "active_plan": ".omo/plans/qwen3-dense-w8a16-quantization.md",
+      "plan_name": "qwen3-dense-w8a16-quantization",
+      "session_ids": [
+        "codex:qwen3-w8a16-20260729"
+      ],
+      "status": "completed",
+      "worktree_path": "/tmp/opencode/vllm-qwen3-w8a16"
+    }
+  }
+}

.omo/drafts/qwen3-dense-w8a16-quantization.md

@@ -0,0 +1,74 @@
+---
+slug: qwen3-dense-w8a16-quantization
+status: awaiting-approval
+intent: clear
+review_required: false
+pending-action: write .omo/plans/qwen3-dense-w8a16-quantization.md
+approach: Four approximately 2-point subtasks covering compressed-tensors plus W8A16 scheme registration, packed-weight loading/finalization, Dynamo-safe custom-op wrapping of the kernel contract, and engine plus graph-capture validation; no kernel implementation, generation, accuracy, or attention changes.
+---
+
+# Draft: qwen3-dense-w8a16-quantization
+
+## Components (topology ledger)
+<!-- Lock the SHAPE before depth. One row per top-level component that can succeed or fail independently. -->
+<!-- id | outcome (one line) | status: active|deferred | evidence path -->
+registration | compressed-tensors metadata resolves to the HyperAccel WNA16 scheme | active | vllm_hyperaccel/platform.py; branch compressed-tensors-qwen3-w8a16
+loading | packed INT8 weights, per-channel scales, and shape metadata load correctly for plain and fused Qwen3 linears | active | branch compressed-tensors-qwen3-w8a16:f75ca7706
+kernel-op | the W8A16 scheme calls a registered opaque torch.ops.vllm op with a fake implementation so Dynamo does not trace the kernel launcher | active | vllm_hyperaccel/ops/register_custom_ops.py; vllm-ascend quantization/methods/w8a16.py
+engine-load | a self-contained quantization integration test initializes the local checkpoint and targeted Dynamo capture contains the opaque W8A16 op without executing the unfinished kernel | active | tests/python/integration/quantization; tests/python/unit_test/compilation
+
+## Open assumptions (announced defaults)
+<!-- Record any default you adopt instead of asking, so the user can veto it at the gate. -->
+<!-- assumption | adopted default | rationale | reversible? -->
+activation dtype | BF16, not FP16 | checkpoint config dtype and upstream trace both specify bfloat16; BerthaPlatform forces float16 to bfloat16 | yes
+runtime representation | retain checkpoint-native packed INT8 plus channel scales through the kernel boundary | the existing branch's eager BF16 dequantization defeats the requested quantized execution path | yes
+kernel dependency | register a Dynamo-visible op whose runtime implementation hard-fails immediately before the future legato_kernels call | the missing kernel must block every real W8A16 matmul; fake/meta behavior is tracing-only and must never become an execution fallback | yes
+integration depth | a new self-contained quantization integration suite owns engine/model initialization and weight-loading coverage without generate/forward | the temporary model_smoke suite is expected to be removed | yes
+
+## Findings (cited - path:lines)
+
+- The current checked-out branch has no compressed-tensors source; the implementation exists on local branch `compressed-tensors-qwen3-w8a16` in commits `f75ca7706` and `d2aaeb6bf`.
+- That branch correctly adds exact scheme gating, registration, packed parameter creation, and synthetic fused-loader tests, but `process_weights_after_loading()` permanently dequantizes to a dense BF16 weight and `apply_weights()` calls `torch.nn.functional.linear`; this does not preserve a quantized kernel-ready path.
+- The checkpoint declares `dtype=bfloat16`, `quant_method=compressed-tensors`, packed static symmetric channel-wise INT8 weights, and ignores `lm_head`: `/root/qwen3-awq-w8a16/Qwen3-8B-AWQ-W8A16-Channelwise/config.json:8,59-95`.
+- Upstream resolves `CompressedTensorsConfig -> CompressedTensorsWNA16 -> AllSparkLinearKernel`; attention is independent: `/root/qwen3-awq-w8a16/Qwen3-8B-AWQ-W8A16-Channelwise/upstream-vllm-basic-compressed-tensors-paths.md:228-293,316-339`.
+- HyperAccel has no usable W8A16 kernel yet: `3rd_party/legato-custom-kernels/legato_kernels/gemm/gemm_int8.py` is an A8W8 docstring-only placeholder and its GEMM test is skipped.
+- `vllm.LLM(...)` construction is the intended engine boundary, but coverage must live in a new durable `tests/python/integration/quantization/` suite rather than the soon-to-be-removed `model_smoke` suite.
+- The kernel team has now selected the established `direct_register_custom_op` pattern: until the real kernel exists, the runtime implementation raises `NotImplementedError` exactly where the future `legato_kernels` call will go; `fake_impl` exists only for graph capture.
+- vLLM-Ascend uses two independent registries: `@register_scheme("W8A16", "linear")` for method selection and dispatcher-visible runtime ops for graph-safe execution. Its native `torch_npu` W8A16 matmul is already dispatcher-visible; HyperAccel's Python/Legato launcher requires explicit custom-op registration.
+
+## Decisions (with rationale)
+
+- Split into four independently verifiable, approximately 2-point subtasks: config/scheme registration; packed parameter loading/finalization; opaque custom-op registration and `apply()` wiring; engine initialization plus no-graph-break capture tests.
+- Refactor the branch implementation rather than treating its eager BF16 fallback as complete.
+- Test strategy is tests-after against existing plugin patterns: CPU/host-mock unit tests for the first three tickets and the existing model-smoke harness for the fourth.
+- The checkpoint state remains packed and no permanent dense BF16 fallback is allowed. Runtime execution must remain blocked until the real kernel and any required post-load layout transformation are supplied together.
+
+## Scope IN
+
+- compressed-tensors detection and HyperAccel platform registration
+- exact W8A16 scheme gating for static symmetric channel-wise INT8 weights with no activation quantization
+- packed checkpoint parameter creation/loading for ordinary, QKV-fused, and gate/up-fused Linear modules
+- validation-only post-load finalization that preserves checkpoint-native packed state
+- a `direct_register_custom_op` W8A16 op with accurate fake/meta behavior and a runtime `NotImplementedError` blocker immediately before the future kernel call
+- scheme `apply()` routed through `torch.ops.vllm.<w8a16-op>`
+- local-checkpoint vLLM engine initialization, loaded-model assertions, and targeted Dynamo no-graph-break proof without real kernel execution
+
+## Scope OUT (Must NOT have)
+
+- AllSpark port, Legato W8A16 kernel, A8W8 kernel, or any other quantized kernel implementation
+- eager conversion of the full INT8 checkpoint to BF16 runtime weights
+- generation, accuracy comparison, throughput benchmarking, or attention-backend work
+- AWQLinearMethod/AWQMarlin routing; the directory name does not override compressed-tensors metadata
+- any executable fallback or successful real W8A16 matmul before the production kernel exists
+
+## Open questions
+
+None. The registered plugin op has a plugin-owned logical schema for graph capture, while its runtime implementation intentionally blocks at the future kernel-call line.
+
+## Approval gate
+status: approved
+approach: Produce four Jira-ready subtasks at roughly 2 story points each, ordered by dependency, with exact paths, acceptance criteria, QA, and execution prompts. The implementation wraps but does not implement the frozen W8A16 kernel, and proves Dynamo capture without real kernel execution.
+next action: Complete `.omo/plans/qwen3-dense-w8a16-quantization.md`, run Metis gap analysis, and hand off the executable plan without implementing product code.
+approved: true
+<!-- When exploration is exhausted and unknowns are answered, set status: awaiting-approval. -->
+<!-- That durable record is the loop guard: on a later turn read it and resume at the gate instead of re-running exploration. -->

.omo/evidence/task-1-registration.txt

@@ -0,0 +1,71 @@
+Task 1 - compressed-tensors W8A16 registry
+Worktree: /tmp/opencode/vllm-qwen3-w8a16/vllm
+Initial HEAD: 6ef0f6bb8ae1dacf80d5c46eb931b5188b4865c1
+
+TDD evidence
+============
+Added test_qwen3_w8a16_config_selects_registered_linear_scheme before the
+registry implementation. The normal bootstrap commands were unavailable:
+
+  pytest tests/python/unit_test/quantization/test_compressed_tensors.py tests/python/unit_test/platform/test_platform.py -q
+  -> /usr/bin/bash: pytest: command not found
+
+  uv run pytest tests/python/unit_test/quantization/test_compressed_tensors.py tests/python/unit_test/platform/test_platform.py -q
+  -> dependency build failed before collection because
+     legato/csrc/3rdparty/doctest/CMakeLists.txt is absent.
+
+For the executable red/green proof, the cached CPU dependency environment was
+used (PYTHONPATH includes the cached pytest, vLLM, torch, compressed-tensors,
+and their locked transitive packages). The following exact test selector was
+run with the W8A16 decorator temporarily removed:
+
+  /usr/bin/python3.10 -m pytest tests/python/unit_test/quantization/test_compressed_tensors.py::test_qwen3_w8a16_config_selects_registered_linear_scheme -q
+  -> FAILED: NotImplementedError: HyperAccel has no scheme for quantization
+     'W8A16' and layer type 'linear'.
+
+The decorator was restored and the same selector was run in the same cached
+environment:
+
+  /usr/bin/python3.10 -m pytest tests/python/unit_test/quantization/test_compressed_tensors.py::test_qwen3_w8a16_config_selects_registered_linear_scheme -q
+  -> 1 passed, 15 warnings in 6.89s.
+
+Focused verification
+====================
+  /usr/bin/python3.10 -m pytest tests/python/unit_test/quantization/test_compressed_tensors.py tests/python/unit_test/platform/test_platform.py -q
+  -> 23 passed, 15 warnings in 13.62s.
+
+  /usr/bin/python3.10 -m pytest tests/python/unit_test/quantization/test_quant_config.py -q
+  -> 5 passed, 15 warnings in 6.94s.
+
+  uvx ruff@0.9.2 check vllm_hyperaccel/quantization/compressed_tensors.py vllm_hyperaccel/quantization/methods/__init__.py vllm_hyperaccel/quantization/methods/registry.py vllm_hyperaccel/quantization/methods/w8a16.py tests/python/unit_test/quantization/test_compressed_tensors.py
+  -> All checks passed.
+
+Type diagnostics
+================
+The LSP tool reported no installed Python server and no active Python client.
+`uvx ty@0.0.5 check` was attempted but could not resolve external vLLM, torch,
+compressed-tensors, and pytest imports because the checkout's normal `uv` sync
+cannot finish without the missing Legato doctest submodule. No source-code type
+diagnostics were reported beyond those unavailable external imports.
+
+Manual surface exercised: the real vLLM config parser built a LinearBase,
+resolved the registered W8A16 class, retained lm_head as unquantized, rejected
+activation quantization, verified repeated scheme-package imports preserve the
+same registered class, and preserved existing FP8 registration behavior.
+
+Follow-up size remediation
+==========================
+Only verbose W8A16 method docstrings were shortened; no executable statement,
+registry/config selection, parameter shape, loader, or test behavior changed.
+
+  wc -l vllm_hyperaccel/quantization/methods/w8a16.py
+  -> 252 vllm_hyperaccel/quantization/methods/w8a16.py
+
+  awk '!/^[[:space:]]*$/ && !/^[[:space:]]*(\/\/|#|--)/' vllm_hyperaccel/quantization/methods/w8a16.py | wc -l
+  -> 225
+
+  /usr/bin/python3.10 -m pytest tests/python/unit_test/quantization/test_compressed_tensors.py tests/python/unit_test/platform/test_platform.py tests/python/unit_test/quantization/test_quant_config.py -q
+  -> 28 passed, 15 warnings in 11.33s (cached CPU dependency environment).
+
+  uvx ruff@0.9.2 check vllm_hyperaccel/quantization/methods/w8a16.py
+  -> All checks passed.

.omo/evidence/task-2-packed-loading.txt

@@ -0,0 +1,83 @@
+Task 2: packed Qwen3 W8A16 loading and validation-only finalization
+
+Baseline
+========
+Worktree: /tmp/opencode/vllm-qwen3-w8a16/vllm
+HEAD: fc552f02dea0ccfb6e4ad0decf667f4f81d15585
+Command: git status --short && git rev-parse HEAD && git log --oneline -3
+Result: git status --short was empty; HEAD was fc552f02dea0ccfb6e4ad0decf667f4f81d15585.
+
+TDD red
+=======
+Command:
+PYTHONPATH=. uv run --no-project --python 3.10 --with 'torch==2.10.0' --with 'vllm==0.19.1+empty' --with pytest pytest tests/python/unit_test/quantization/test_compressed_tensors.py::test_packed_int8_loading_retains_checkpoint_tensors -q
+
+Result: exit 1. The new contract test failed at the retained-state assertion because the baseline
+process_weights_after_loading() removed layer.weight_packed. The failure was:
+AttributeError: 'LinearBase' object has no attribute 'weight_packed'
+The captured layer parameters instead contained only a dense ModelWeightParameter named weight.
+
+TDD green and focused tests
+==========================
+Command:
+PYTHONPATH=. uv run --no-project --python 3.10 --with 'torch==2.10.0' --with 'vllm==0.19.1+empty' --with pytest pytest tests/python/unit_test/quantization/test_compressed_tensors.py tests/python/unit_test/quantization/test_w8a16_loading.py tests/python/unit_test/quantization/test_w8a16_validation.py -q
+
+Result: exit 0; 20 passed. Coverage includes ordinary packed state retention, eager kernel blocker,
+QKV q/k/v ordering, merged gate/up ordering, packed dtype/rank, BF16 scale dtype/shape/count,
+int64 shape metadata, packing divisibility, aggregate output, and component output validation.
+
+Required regressions
+====================
+Command:
+PYTHONPATH=. uv run --no-project --python 3.10 --with 'torch==2.10.0' --with 'vllm==0.19.1+empty' --with pytest pytest tests/python/unit_test/platform/test_platform.py tests/python/unit_test/quantization/test_quant_config.py -q
+Result: exit 0; 18 passed.
+
+Command:
+PYTHONPATH=. uv run --no-project --python 3.10 --with 'torch==2.10.0' --with 'vllm==0.19.1+empty' --with pytest pytest tests/python/unit_test/ops/test_linear.py -q
+Result: exit 0; 12 passed.
+
+Quality checks
+==============
+Command:
+uv run --no-project --python 3.10 --with 'ruff==0.9.2' ruff check vllm_hyperaccel/quantization/methods/w8a16.py tests/python/unit_test/quantization/test_compressed_tensors.py tests/python/unit_test/quantization/conftest.py tests/python/unit_test/quantization/test_w8a16_loading.py tests/python/unit_test/quantization/test_w8a16_validation.py
+Result: exit 0; All checks passed.
+
+Command:
+uv run --no-project --python 3.11 /root/.cache/opencode/packages/oh-my-openagent@latest/node_modules/oh-my-openagent/dist/skills/programming/scripts/python/check-no-excuse-rules.py vllm_hyperaccel/quantization/methods/w8a16.py tests/python/unit_test/quantization/test_compressed_tensors.py tests/python/unit_test/quantization/conftest.py tests/python/unit_test/quantization/test_w8a16_loading.py tests/python/unit_test/quantization/test_w8a16_validation.py
+Result: exit 0; no violations in 5 file(s).
+
+Command: GIT_MASTER=1 git diff --check
+Result: exit 0.
+
+Pure LOC
+========
+vllm_hyperaccel/quantization/methods/w8a16.py: 241
+tests/python/unit_test/quantization/test_compressed_tensors.py: 108
+tests/python/unit_test/quantization/conftest.py: 118
+tests/python/unit_test/quantization/test_w8a16_loading.py: 75
+tests/python/unit_test/quantization/test_w8a16_validation.py: 94
+
+Manual data-surface proof
+=========================
+An isolated Python 3.10 driver initialized the same TP=1 shim used by the real-loader tests,
+created an ordinary W8A16 scheme, loaded int32 packed words, BF16 scales, and int64 shape
+metadata, then called post-load processing and apply_weights(). It printed:
+torch.int32 torch.bfloat16 torch.int64 False
+HyperAccel W8A16 kernel is unavailable: packed W8A16 execution is blocked until the runtime kernel is registered.
+
+This proves packed state remains attached, no dense weight exists, and real W8A16 execution is blocked.
+
+Environment limitations
+=======================
+- The starting worktree had no project pytest or vLLM environment: `uv run --no-sync pytest ...` could not spawn pytest.
+- `uv sync` could resolve dependencies but failed building sibling legato because
+  /tmp/opencode/vllm-qwen3-w8a16/legato/csrc/3rdparty/doctest has no CMakeLists.txt.
+- Tests therefore used isolated `uv run --no-project` environments with torch 2.10.0 and vllm 0.19.1+empty.
+- Test runs emitted pre-existing host-mock and torch.jit deprecation warnings; all requested tests passed.
+- LSP diagnostics could not run: the LSP tool request cwd is the original workspace and rejects files under /tmp,
+  and basedpyright is not installed. Ruff and no-excuse checks completed successfully instead.
+
+Cleanup
+=======
+No commit, push, branch switch, staging, kernel code, custom-op registration, torch.ops call, F.linear fallback,
+dequantization, runtime-device/dtype state, or unpack helper was added. The target worktree remains uncommitted.

.omo/evidence/task-3-opaque-op.txt

@@ -0,0 +1,102 @@
+Task 3: opaque W8A16 custom op evidence
+Repository: /tmp/opencode/vllm-qwen3-w8a16/vllm
+
+Baseline
+========
+$ GIT_MASTER=1 git rev-parse HEAD
+e3a952b3fb79b015828ca33f9c3acbcfefdef8e5
+
+$ GIT_MASTER=1 git status --short
+(no output; clean before Task 3 edits)
+
+$ uv run --no-sync pytest tests/python/unit_test/quantization/test_w8a16_loading.py tests/python/unit_test/quantization/test_w8a16_validation.py -q
+14 passed, 15 warnings in 0.16s
+
+The bare pytest executable was unavailable initially. A normal uv run attempted
+to build the incomplete local legato package and failed on its missing doctest
+submodule. The pre-existing workspace .venv was then populated with the CPU/dev
+test dependencies; all recorded test commands use uv run --no-sync and passed.
+
+TDD Red
+=======
+$ uv run --no-sync pytest tests/python/unit_test/ops/test_w8a16.py::test_w8a16_linear_registration_exposes_torch_op -q
+FAILED: AttributeError: '_OpNamespace' 'vllm' object has no attribute 'w8a16_linear'
+
+$ uv run --no-sync pytest tests/python/unit_test/quantization/test_w8a16_loading.py::test_apply_weights_raises_until_w8a16_runtime_kernel_is_implemented -q
+FAILED before the implementation because the old scheme blocker message did not
+match the required legato_kernels.w8a16_linear unavailable message.
+
+Targeted Green
+==============
+$ uv run --no-sync pytest tests/python/unit_test/ops/test_w8a16.py tests/python/unit_test/quantization/test_w8a16_loading.py -q
+10 passed, 15 warnings in 0.27s
+
+This covers dispatcher registration, repeated registration, rank-three meta
+shape/dtype/device, symbolic-leading-dimension torch.export capture of
+torch.ops.vllm.w8a16_linear.default through the thin wrapper, exact eager
+NotImplementedError, preserved packed loading, and scheme-to-wrapper routing.
+
+Manual Export And Eager Probe
+=============================
+$ uv run --no-sync python -c $'import torch\nfrom vllm_hyperaccel.ops.register_custom_ops import register_legato_kernel_ops, w8a16_linear\n\nclass W8A16ExportProbe(torch.nn.Module):\n    def __init__(self) -> None:\n        super().__init__()\n        self.register_buffer("weight_packed", torch.zeros((5, 1), dtype=torch.int32))\n        self.register_buffer("weight_scale", torch.ones((5, 1), dtype=torch.bfloat16))\n\n    def forward(self, x: torch.Tensor) -> torch.Tensor:\n        return w8a16_linear(x, self.weight_packed, self.weight_scale)\n\nregister_legato_kernel_ops()\nprogram = torch.export.export(W8A16ExportProbe(), (torch.empty((2, 3, 4), dtype=torch.bfloat16),), dynamic_shapes=({0: torch.export.Dim("batch"), 1: torch.export.Dim("tokens")},))\nassert any(node.target is torch.ops.vllm.w8a16_linear.default for node in program.graph.nodes)\ntry:\n    w8a16_linear(torch.ones((2, 4), dtype=torch.bfloat16), torch.ones((5, 1), dtype=torch.int32), torch.ones((5, 1), dtype=torch.bfloat16))\nexcept NotImplementedError as error:\n    assert str(error) == "HyperAccel W8A16 kernel is unavailable: legato_kernels.w8a16_linear has not been implemented."\nelse:\n    raise AssertionError("real W8A16 call unexpectedly succeeded")\nprint("export_target=torch.ops.vllm.w8a16_linear.default; eager_blocker=confirmed")'
+export_target=torch.ops.vllm.w8a16_linear.default; eager_blocker=confirmed
+
+Focused Regressions
+===================
+$ uv run --no-sync pytest tests/python/unit_test/ops -q
+29 passed, 3 skipped, 1 warning in 10.87s
+The three skips are pre-existing dummy gated-RMSNorm kernel tests.
+
+$ uv run --no-sync pytest tests/python/unit_test/quantization -q
+26 passed, 15 warnings in 0.77s
+This includes the existing FP8 quantization tests.
+
+$ uv run --no-sync pytest tests/python/unit_test/platform/test_platform.py -q
+13 passed, 15 warnings in 9.32s
+
+Quality Checks
+==============
+$ uv run --no-sync ruff check vllm_hyperaccel/ops/register_custom_ops.py vllm_hyperaccel/quantization/methods/w8a16.py tests/python/unit_test/ops/test_w8a16.py tests/python/unit_test/quantization/test_w8a16_loading.py
+All checks passed.
+
+$ uv run --no-sync ruff format --check vllm_hyperaccel/ops/register_custom_ops.py vllm_hyperaccel/quantization/methods/w8a16.py tests/python/unit_test/ops/test_w8a16.py tests/python/unit_test/quantization/test_w8a16_loading.py
+4 files already formatted.
+
+$ GIT_MASTER=1 git diff --check
+(no output)
+
+$ uv run --no-sync python /root/.cache/opencode/packages/oh-my-openagent@latest/node_modules/oh-my-openagent/dist/skills/programming/scripts/python/check-no-excuse-rules.py vllm_hyperaccel/ops/register_custom_ops.py vllm_hyperaccel/quantization/methods/w8a16.py tests/python/unit_test/ops/test_w8a16.py tests/python/unit_test/quantization/test_w8a16_loading.py
+Exit 1 with two pre-existing register_custom_ops.py findings:
+- line 41 generic-exception (existing ValueError)
+- oversized-module, 325 pure LOC; baseline was already 290 pure LOC
+Neither was suppressed or refactored because Task 3 explicitly requires the
+new registration to mirror this file and forbids broadly refactoring custom ops.
+
+Pure LOC measurements (current / baseline)
+===========================================
+register_custom_ops.py: 325 / 290
+w8a16.py: 239 / 241
+test_w8a16.py: 69 / new
+test_w8a16_loading.py: 111 / existing
+
+LSP
+===
+LSP diagnostics were attempted for every changed Python file. basedpyright is
+not installed, and the environment records that its installation was previously
+declined; no Python LSP diagnostics could run.
+
+Final Scope
+===========
+$ GIT_MASTER=1 git status --short
+ M tests/python/unit_test/quantization/test_w8a16_loading.py
+ M vllm_hyperaccel/ops/register_custom_ops.py
+ M vllm_hyperaccel/quantization/methods/w8a16.py
+?? tests/python/unit_test/ops/test_w8a16.py
+
+No commit, push, branch switch, kernel import/implementation, F.linear fallback,
+or attention/generation/integration/model-smoke change occurred. No .omo plan or
+state file was edited; this requested evidence file is the sole .omo write.
+
+DoneClaim: W8A16 now registers as a functional opaque vllm custom op with a
+symbolic fake path, emits torch.ops.vllm.w8a16_linear.default during export, and
+hard-blocks every real eager execution at the future Legato launcher seam.

.omo/evidence/task-4-engine-load.txt

@@ -0,0 +1,56 @@
+Task 4: durable Qwen3 W8A16 engine-load integration coverage
+Date: 2026-07-29
+Target worktree: /tmp/opencode/vllm-qwen3-w8a16/vllm
+Checkpoint: /root/qwen3-awq-w8a16/Qwen3-8B-AWQ-W8A16-Channelwise
+
+Baseline
+- Verified clean baseline at HEAD 2b150092ce891feb743d43fdf89cf42ac38b7e84.
+- PYTHONPATH=. /root/hyperaccel-sdk/.venv/bin/pytest tests/python/unit_test/quantization/test_compressed_tensors.py -q
+  Result: 6 passed in 1.77s (14 upstream torch deprecation warnings).
+- The direct virtualenv command was used because `uv run pytest` attempted to rebuild the workspace Legato package and failed on the pre-existing absent legato/csrc/3rdparty/doctest CMake source; no source or environment workaround was committed.
+
+TDD evidence
+- Initial engine test red: FSim had no opened LPU device (HaGetDeviceCount=0), requiring the suite-local import-time FSim bootstrap.
+- Second engine test red: upstream compressed-tensors assigned CompressedTensorsKVCacheMethod despite the checkpoint's kv_cache_scheme: null. The method attempted an LPU quant-scale allocation.
+- Focused unit regression red: test_qwen3_w8a16_config_leaves_unquantized_kv_cache_unmodified received CompressedTensorsKVCacheMethod instead of None.
+- Minimal production fix: BerthaCompressedTensorsConfig leaves Attention unquantized when kv_cache_scheme is None. Focused unit regression then passed.
+- FSim-only test support keeps temporary post-load W8A16 validation on CPU because FSim rejects the upstream host-pointer copy; final parameters are CPU-resident after upstream validation in any case. The suite locally bypasses EngineCore's compile-or-warmup hook and guards HAModelRunner.warmup_model, so no forward, warmup, generation, or compile occurs.
+
+Real-checkpoint integration
+- Command:
+  time -p env PYTHONPATH=. /root/hyperaccel-sdk/.venv/bin/pytest tests/python/integration/quantization/test_qwen3_w8a16_model_load.py -q
+- Result: 1 passed in 36.38s pytest time; shell wall time 38.04s, user 44.23s, sys 29.45s.
+- Observed engine behavior: FSim LPU was opened by the suite, both safetensor shards were loaded, 875 surplus tensors were filtered by the one-layer Qwen3 override, and the bounded 128 MiB KV budget created 32,768 cache blocks/tokens.
+- Assertions exercised: compressed-tensors resolution, TP=1, block_size=1, one Qwen3 layer, HAWorker -> HAModelRunner -> HyperAccel Qwen3 type, registered W8A16 scheme, retained int32 packed weights, BF16 channel scales, valid int64 shape metadata, no dense quantized-linear weight, unquantized lm_head, and the deliberate real W8A16 wrapper call raising the exact NotImplementedError.
+- The external checkpoint is skipped only when VLLM_QWEN3_W8A16_CHECKPOINT (or its default path) is absent. This run used the default existing checkpoint and passed, not skipped.
+
+Focused regressions
+- PYTHONPATH=. /root/hyperaccel-sdk/.venv/bin/pytest tests/python/unit_test/quantization tests/python/unit_test/platform/test_platform.py tests/python/unit_test/ops/test_w8a16.py -q
+  Result: 45 passed in 4.29s (14 upstream torch deprecation warnings).
+  Coverage includes compressed-tensors/W8A16 loading and validation, FP8 quantization, platform registration, opaque-op export, and explicit eager blocker assertion.
+
+Static and scope checks
+- /root/hyperaccel-sdk/.venv/bin/ruff check <all 4 changed Python files>: All checks passed.
+- /root/hyperaccel-sdk/.venv/bin/ty check tests/python/integration/quantization/test_qwen3_w8a16_model_load.py tests/python/integration/quantization/conftest.py: All checks passed.
+- uv run check-no-excuse-rules.py <all 4 changed Python files>: no violations in 4 files.
+- Pure nonblank/noncomment LOC: compressed_tensors.py=97; test_compressed_tensors.py=105; integration conftest.py=41; integration engine-load test=163. All are below 200 LOC.
+- git diff --check: clean. Scope is exactly the new tests/python/integration/quantization suite, the null-KV-cache compressed-tensors fix, and its unit regression. No model_smoke files or imports changed.
+- No commit, push, branch switch, kernel implementation, fallback, model forward, generate, serve, sampling, or TP>1 path was used.
+
+DoneClaim: PASS. The self-contained real-checkpoint engine-load integration test is passing against the local checkpoint while real W8A16 execution remains explicitly blocked.
+
+Verifier follow-up after fixture cleanup and representative-projection coverage
+- Exact real-checkpoint verifier command:
+  time -p env PYTHONPATH=. VLLM_QWEN3_W8A16_CLEANUP_RECEIPT=/tmp/vllm-qwen3-w8a16-task4-cleanup-receipt.txt /root/hyperaccel-sdk/.venv/bin/pytest tests/python/integration/quantization/test_qwen3_w8a16_model_load.py -q
+  Result: 1 passed in 33.50s pytest time; shell wall time 34.84s, user 44.21s, sys 28.59s.
+- Observed packed W8A16 projection names from the loaded one-layer model:
+  model.layers.0.mlp.down_proj, model.layers.0.mlp.gate_up_proj, model.layers.0.self_attn.o_proj, model.layers.0.self_attn.qkv_proj.
+- Exact external cleanup receipt from the verifier command:
+  runtime_root=/tmp/vllm-w8a16-engine-load-sp51cdln
+  runtime_root_removed=True
+  fsim_device_reset=True
+- A second direct named-module inspection observed the same four projections and wrote a separate receipt with runtime_root_removed=True and fsim_device_reset=True.
+- Post-change focused regressions:
+  PYTHONPATH=. /root/hyperaccel-sdk/.venv/bin/pytest tests/python/unit_test/quantization tests/python/unit_test/platform/test_platform.py tests/python/unit_test/ops/test_w8a16.py -q
+  Result: 45 passed in 7.18s (14 upstream torch deprecation warnings).
+- Post-change static gates: Ruff and ty both passed; no-excuse reported no violations in all four changed files; pure LOC is compressed_tensors.py=97, test_compressed_tensors.py=105, integration conftest.py=65, and integration engine-load test=184.

.omo/evidence/task-5-review-fixes.txt

@@ -0,0 +1,96 @@
+Task 5: W8A16 final-review fixes
+Date: 2026-07-29
+Worktree: /tmp/opencode/vllm-qwen3-w8a16/vllm
+
+Baseline
+========
+- Verified a clean worktree at HEAD 3ab8ecba7af6e06a4cf8aa3d497858807fa8a12a before edits.
+- Read Todo 5, prior evidence, repository rules, pinned vLLM 0.19.1 source APIs, test surfaces, and README.
+- No commit, push, branch switch, PR/workflow mutation, kernel implementation/import/call, fallback, generation, inference, attention execution support, or TP>1 support was added.
+
+TDD red evidence
+================
+- `PYTHONPATH=. /root/hyperaccel-sdk/.venv/bin/pytest tests/python/unit_test/quantization/test_compressed_tensors.py::test_rejects_non_null_output_activations_before_scheme_selection -q`
+  failed with `DID NOT RAISE NotImplementedError`.
+- `PYTHONPATH=. /root/hyperaccel-sdk/.venv/bin/pytest tests/python/unit_test/quantization/test_compressed_tensors.py::test_rejects_non_null_kv_cache_scheme_at_config_boundary -q`
+  failed with `DID NOT RAISE NotImplementedError`. A direct pinned-vLLM probe showed `CompressedTensorsKVCacheMethod` would be returned upstream.
+- A constructible exact vLLM 0.19.1 `FusedMoE` test entered upstream `CompressedTensorsWNA16MoEMethod` before failing its Marlin/group assertion, proving the delegation path existed.
+- `PYTHONPATH=. /root/hyperaccel-sdk/.venv/bin/pytest tests/python/unit_test/quantization/test_w8a16_loading.py::test_loader_rejects_wrong_checkpoint_source_dtype_before_default_cast -q`
+  failed all three parametrizations: int16 packed words, float32 scales, and int32 shape metadata were silently cast.
+- The supplied-loader red regression showed the supplied shard loader was called for an int16 packed source before validation.
+- The integration conftest import probe created `/tmp/.../vllm-w8a16-engine-load-*` with `ha-home`, `tmp`, and `vllm-cache`; the collection-isolation regression failed on that root.
+
+Implementation
+==============
+- `vllm_hyperaccel/quantization/compressed_tensors.py` now rejects every non-null raw config-group `output_activations` before upstream parsing/scheme selection and every non-null `kv_cache_scheme` at config parsing. Null KV keeps Attention unquantized. Exact vLLM 0.19.1 `FusedMoE` is rejected before superclass delegation.
+- `vllm_hyperaccel/quantization/methods/loading.py` owns `W8A16ValidationError` and `W8A16SourceDtypeLoader`; the wrapper checks the checkpoint source before default or supplied loaders, preserves `*args/**kwargs`, and reports parameter role, expected dtype, actual dtype, and layer.
+- `w8a16.py` wraps packed int32 words, BF16 scales, and int64 shape metadata loaders. The default loader no longer contains a dtype cast. Correct ordinary and fused QKV/gate-up loaders remain unchanged through their real loader contracts.
+- The integration conftest computes only string paths at import. The yield fixture owns root/subdirectory creation and teardown before importing torch/hart; all vLLM/plugin imports moved behind that fixture into local test/helper imports or `TYPE_CHECKING`.
+- README documents the exact checkpoint format, including ignored/unquantized `lm_head`, BF16/TP=1 loading plus Dynamo-preparation-only scope, no generation/inference, and the hard `legato_kernels.w8a16_linear` blocker with no fallback.
+
+Green tests
+===========
+- Focused new behavior:
+  `PYTHONPATH=. /root/hyperaccel-sdk/.venv/bin/pytest tests/python/unit_test/quantization/test_compressed_tensors.py tests/python/unit_test/quantization/test_w8a16_loading.py tests/python/unit_test/quantization/test_w8a16_integration_isolation.py -q`
+  -> 21 passed in 4.36s.
+- Full focused matrix:
+  `PYTHONPATH=. /root/hyperaccel-sdk/.venv/bin/pytest tests/python/unit_test/quantization tests/python/unit_test/platform/test_platform.py tests/python/unit_test/ops/test_w8a16.py tests/python/unit_test/ops/test_linear.py tests/python/unit_test/attention/test_attention.py -q`
+  -> 74 passed in 7.08s, including FP8, compressed-tensors, W8A16 op/blocker, platform, linear, and attention coverage.
+- Final exact real-checkpoint commands, both with `/root/hyperaccel-sdk/.venv/bin/pytest`, both collected 1, passed 1, skipped 0:
+  1. `time -p env PYTHONPATH=. VLLM_QWEN3_W8A16_CLEANUP_RECEIPT=/tmp/vllm-qwen3-w8a16-task5-final-real-1.cleanup.txt /root/hyperaccel-sdk/.venv/bin/pytest tests/python/integration/quantization/test_qwen3_w8a16_model_load.py -q`
+     -> 1 passed in 33.97s pytest time, 35.15s wall time.
+  2. `time -p env PYTHONPATH=. VLLM_QWEN3_W8A16_CLEANUP_RECEIPT=/tmp/vllm-qwen3-w8a16-task5-final-real-2.cleanup.txt /root/hyperaccel-sdk/.venv/bin/pytest tests/python/integration/quantization/test_qwen3_w8a16_model_load.py -q`
+     -> 1 passed in 33.34s pytest time, 34.48s wall time.
+
+Cleanup probes and receipts
+===========================
+- Normal real-load receipts `/tmp/vllm-qwen3-w8a16-task5-final-real-{1,2}.cleanup.txt` each record `runtime_root_removed=True`, `fsim_device_reset=True`; both recorded roots are absent after teardown.
+- Missing-checkpoint skip command completed as `1 skipped`; `/tmp/vllm-qwen3-w8a16-task5-skip.cleanup.txt` records root removal and FSim reset.
+- Separate `pytest --collect-only` in an isolated TMPDIR collected 1 test with no runtime roots and no receipt, as no fixture owned a runtime resource.
+- An isolated import-and-interrupt collection probe returned timeout status 124 with no runtime roots or receipt.
+- A real model-load `timeout --signal=INT --kill-after=30s 15s ...pytest...` interrupted during load, produced pytest KeyboardInterrupt, and wrote `/tmp/vllm-qwen3-w8a16-task5-timeout.cleanup.txt` with `runtime_root_removed=True` and `fsim_device_reset=True`; its root is absent.
+- Final `psutil` probe reported `active_runtime_roots=()` and `active_related_processes=[]`.
+
+Static/scope checks
+===================
+- Ruff: `ruff check` passed and `ruff format --check` reported all 8 changed Python files already formatted.
+- No-excuse: `uv run --no-project --python 3.11 .../check-no-excuse-rules.py <8 changed Python files>` -> no violations in 8 files.
+- `git diff --check` passed.
+- Pure LOC: compressed_tensors.py=137; loading.py=35; w8a16.py=234; all changed Python files are at or below 234 pure LOC.
+- `ty check` reports 19 pre-existing dynamic-vLLM attribute/type diagnostics in existing W8A16 tests/scheme dispatch; the new config-boundary return diagnostic was eliminated and the new loader module has no ty diagnostic. LSP diagnostics cannot inspect `/tmp/opencode/...` because the LSP request cwd is `/root/qwen3-awq-w8a16/Qwen3-8B-AWQ-W8A16-Channelwise`.
+- Targeted fallback scan finds the W8A16 scheme only routes to `w8a16_linear`; the registered implementation remains the exact kernel-unavailable `NotImplementedError`. No executable W8A16 fallback exists.
+
+Changed worktree files
+======================
+- README.md
+- tests/python/integration/quantization/conftest.py
+- tests/python/integration/quantization/test_qwen3_w8a16_model_load.py
+- tests/python/unit_test/quantization/test_compressed_tensors.py
+- tests/python/unit_test/quantization/test_w8a16_loading.py
+- tests/python/unit_test/quantization/test_w8a16_integration_isolation.py
+- vllm_hyperaccel/quantization/compressed_tensors.py
+- vllm_hyperaccel/quantization/methods/loading.py
+- vllm_hyperaccel/quantization/methods/w8a16.py
+
+DoneClaim: PASS
+
+Fresh verifier follow-up: empty config_groups fail-closed edge
+=============================================================
+- Repro before the fix: `BerthaCompressedTensorsConfig.from_config({})` returned a config whose real `LinearBase` selected `UnquantizedLinearMethod`.
+- TDD red command:
+  `PYTHONPATH=. /root/hyperaccel-sdk/.venv/bin/pytest tests/python/unit_test/quantization/test_compressed_tensors.py::test_rejects_missing_or_empty_config_groups_before_unquantized_fallback -q`
+  -> 2 failed: both missing `{}` and empty `{"config_groups": {}}` reported `DID NOT RAISE NotImplementedError`.
+- Minimal fix: `BerthaCompressedTensorsConfig.from_config` now rejects absent or empty `config_groups` before upstream parsing with `NotImplementedError("HyperAccel compressed-tensors requires non-empty config_groups metadata.")`. A non-empty group lacking a global format already reaches scheme selection and fails closed, so no broader schema validation was added.
+- Green focused regression: the same command -> 2 passed in 1.02s.
+- Full matrix:
+  `PYTHONPATH=. /root/hyperaccel-sdk/.venv/bin/pytest tests/python/unit_test/quantization tests/python/unit_test/platform/test_platform.py tests/python/unit_test/ops/test_w8a16.py tests/python/unit_test/ops/test_linear.py tests/python/unit_test/attention/test_attention.py -q`
+  -> 76 passed in 5.24s. This retains valid W8A16, ignored lm_head, FP8, output activation, KV, FusedMoE, source-dtype, op-blocker, linear, platform, and attention coverage.
+- Real checkpoint:
+  `time -p env PYTHONPATH=. VLLM_QWEN3_W8A16_CLEANUP_RECEIPT=/tmp/vllm-qwen3-w8a16-task5-empty-config-real.cleanup.txt /root/hyperaccel-sdk/.venv/bin/pytest tests/python/integration/quantization/test_qwen3_w8a16_model_load.py -q`
+  -> 1 passed, 0 skipped, in 32.91s pytest time (33.88s wall). Receipt records `runtime_root_removed=True` and `fsim_device_reset=True`; its root is absent.
+- Static checks: ruff check passed; ruff format --check reported 2 changed Python files already formatted; no-excuse reported no violations in 2 files; `git diff --check` passed.
+- Pure LOC after the follow-up: `test_compressed_tensors.py=169`, `compressed_tensors.py=140`.
+- Final cleanup probe: `active_runtime_roots=()` and `active_related_processes=[]`.
+- No commit, push, PR mutation, kernel, fallback, or scope expansion was added.
+
+DoneClaim: PASS

.omo/evidence/task-6-review-cycle2.txt

@@ -0,0 +1,33 @@
+Review cycle 2 evidence
+Head before fixes: e58c5f3865066960c73a2400a3fd88e64fd1dcef
+Worktree: /tmp/opencode/vllm-qwen3-w8a16
+
+Red evidence
+- Qwen3 model-to-loader dtype test failed with `DID NOT RAISE W8A16ValidationError`; float32 weight_scale was cast to BF16 before validation.
+- Nine config/registry cases failed before source changes: sparse metadata, multiple groups, empty/missing/non-Linear targets, broadened ignore, silent unquantized dispatch, and bare duplicate ValueError.
+- Six fixture probes failed before source changes: default receipt, symlink clobber, unnamespaced Inductor/Legato paths, normal cleanup, and SIGINT cleanup.
+
+Green evidence
+- Entire unit quantization directory: 52 passed, 0 skipped, 14 warnings in 7.81s.
+- Real checkpoint `vllm.LLM` load: 1 passed, 0 skipped, 15 warnings in 33.23s.
+- Genuine timeout SIGINT during real checkpoint load: KeyboardInterrupt, timeout status accepted as 124, no tests completed.
+- Normal receipt: runtime_root=/tmp/vllm-w8a16-engine-load-d87503a229614839b853c17aae12d8ef, runtime_root_removed=True, fsim_device_reset=True.
+- Interrupted receipt: runtime_root=/tmp/vllm-w8a16-engine-load-d29b2f1d5f8b42a99ecad59d3910fc68, runtime_root_removed=True, fsim_device_reset=True.
+- No new external legato_lm_head, torchinductor_root, or default cleanup receipt paths; all observed shared-/tmp artifacts predated these runs.
+- No residual pytest/Qwen/vLLM worker process.
+- Ruff check passed; Ruff format check reported 7 files already formatted; no-excuse reported no violations in 7 files; git diff --check passed.
+- LSP diagnostics unavailable because the configured request cwd excludes the task worktree.
+
+Verifier delta
+- First fresh verifier withheld confirmation because an empty parsed scheme map reached upstream `UnquantizedLinearMethod` construction before the local postcondition raised.
+- Red trap observed `UPSTREAM_UNQUANTIZED_CONSTRUCTOR_REACHED`.
+- Dispatch now calls `self.get_scheme` first, raises unless it is Bertha W8A16, assigns that scheme, and constructs `CompressedTensorsLinearMethod` directly.
+- Trap is green without touching upstream unquantized construction.
+- Post-delta unit quantization suite: 52 passed in 7.89s; Ruff/format/no-excuse/diff clean.
+- Post-delta real checkpoint load: 1 passed, 0 skipped in 32.38s; runtime_root=/tmp/vllm-w8a16-engine-load-4b3278858d954200902b4f19d0147e85, runtime_root_removed=True, fsim_device_reset=True.
+
+Fix scope
+- Preserve serialized W8A16 weight_packed/weight_scale/weight_shape source tensors through Qwen3 host casting.
+- Accept only the real dense one-group targets=[Linear], ignore=[lm_head], no-sparsity compressed-tensors boundary; require Bertha W8A16 for every other Linear.
+- Use typed duplicate scheme registration error.
+- Namespace all integration temp/cache paths under one UUID root and make receipt writing opt-in, exclusive, no-follow, and mode 0600.

.omo/plans/qwen3-dense-w8a16-quantization.md

@@ -0,0 +1,153 @@
+# qwen3-dense-w8a16-quantization - Work Plan
+
+## TL;DR (For humans)
+**What you'll get:** The HyperAccel plugin will recognize the Qwen3 compressed-tensors W8A16 checkpoint, load and preserve its packed INT8 weights and BF16 channel scales, and expose the future matmul as an opaque Dynamo-safe operation.
+
+**Why this approach:** It follows the vLLM-Ascend split between quantization-scheme registration and runtime-op registration, while making the missing production kernel an explicit hard blocker instead of silently running a fallback.
+
+**What it will NOT do:** It will not implement the kernel, dequantize the model to BF16, run generation, change attention, or allow any W8A16 matmul to succeed before the real kernel exists.
+
+**Effort:** Medium (four approximately 2-point subtasks)
+**Risk:** Medium - checkpoint loading is understood, but packed fused-layer behavior must remain compatible with the later kernel layout.
+**Decisions to sanity-check:** The plugin-owned custom-op schema is logical rather than kernel-physical, and its runtime implementation intentionally raises until replaced by the real Legato call.
+
+Your next move: execute this plan in dependency order. Full execution detail follows below.
+
+---
+
+> TL;DR (machine): 4 sequential implementation todos plus 4 final verifiers; register W8A16, load packed weights, register a hard-blocked opaque op, and prove load/capture without inference.
+
+## Scope
+### Must have
+- Detect the exact local checkpoint format: `compressed-tensors`, `pack-quantized`, static symmetric channel-wise INT8 weights, no activation quantization, BF16 model dtype, and ignored `lm_head`.
+- Register the HyperAccel compressed-tensors config and an Ascend-style `("W8A16", "linear")` scheme in a dedicated `w8a16.py`.
+- Create and load checkpoint-native `weight_packed`, `weight_scale`, and `weight_shape` for ordinary and fused Qwen3 Linear modules at TP=1.
+- Preserve packed state through validation-only post-load finalization; do not create a dense runtime weight.
+- Register a functional `torch.ops.vllm.w8a16_linear` through `direct_register_custom_op`, with a correct fake implementation for output shape/dtype.
+- Route the W8A16 scheme's `apply()` through the registered op.
+- Make the real runtime implementation raise `NotImplementedError` immediately before the future `legato_kernels.w8a16_linear(...)` call site.
+- Prove local-checkpoint engine initialization in a self-contained `tests/python/integration/quantization/` suite and targeted Dynamo graph capture without executing a W8A16 matmul.
+
+### Must NOT have (guardrails, anti-slop, scope boundaries)
+- No AllSpark, Marlin, AWQ, A8W8, Legato kernel, or other kernel implementation.
+- No `torch.nn.functional.linear`, unpack/dequantize-to-BF16, CPU matmul, or successful execution fallback.
+- No speculative kernel-specific transpose, memory kind, packing conversion, offset tensor, or physical layout.
+- No generation, warmup, accuracy comparison, benchmark, attention change, KV-cache quantization, distributed support, or TP>1 work.
+- No broad refactor of existing FP8 or unrelated custom-op code.
+- No dependency on `tests/python/integration/model_smoke`; that suite is expected to be removed.
+- No commit, branch switch, cherry-pick, or modification outside `/root/hyperaccel-sdk/vllm` unless the user separately requests it.
+
+## Verification strategy
+> Zero human intervention - all verification is agent-executed.
+- Test decision: tests-after with pytest, following existing quantization/platform/custom-op/model-smoke patterns.
+- Evidence: <attemptDir>/task-<N>-qwen3-dense-w8a16-quantization.<ext> (attemptDir = currentAttemptDir from 'omo ulw-loop status --json', .omo/evidence/ulw/<session>/<goalId>/a<attempt>; outside ulw-loop use .omo/evidence/)
+- Fast checks: focused pytest files after each todo, then `ruff check` and configured type diagnostics on every changed Python file.
+- Integration boundary: a new self-contained quantization integration suite constructs `vllm.LLM(...)` only. Do not call `warmup_model()`, `generate()`, or a real forward.
+- Dynamo boundary: export/capture a minimal module or function that invokes `torch.ops.vllm.w8a16_linear`; assert the opaque op appears in the graph and the runtime blocker is not executed during fake/meta capture.
+
+## Execution strategy
+### Parallel execution waves
+> Target 5-8 todos per wave. Fewer than 3 (except the final) means you under-split.
+- Wave 1: Todo 1.
+- Wave 2: Todo 2.
+- Wave 3: Todo 3.
+- Wave 4: Todo 4.
+- Final wave: F1-F4 run in parallel after all implementation todos.
+
+### Dependency matrix
+| Todo | Depends on | Blocks | Can parallelize with |
+| --- | --- | --- | --- |
+| 1 | none | 2, 3, 4 | none |
+| 2 | 1 | 3, 4 | none |
+| 3 | 1, 2 | 4 | none |
+| 4 | 1, 2, 3 | F1-F4 | none |
+
+## Todos
+> Implementation + Test = ONE todo. Never separate.
+<!-- APPEND TASK BATCHES BELOW THIS LINE WITH edit/apply_patch - never rewrite the headers above. -->
+- [x] 1. Register compressed-tensors and the HyperAccel W8A16 linear scheme (2 points)
+  What to do: Work in `/root/hyperaccel-sdk/vllm`. Inspect local branch `compressed-tensors-qwen3-w8a16` and commits `f75ca7706`/`d2aaeb6bf` read-only for reusable parsing and platform registration. Keep the compressed-tensors config/adapter separate from an Ascend-style scheme registry. Add a minimal registry keyed by `(quant_type, layer_type)`, import the scheme package for registration side effects, and put the only initial concrete scheme in `vllm_hyperaccel/quantization/methods/w8a16.py` with `@register_scheme("W8A16", "linear")`. Register `compressed-tensors` with vLLM, add it to `BerthaPlatform.supported_quantization` and CLI choices, parse config groups, detect only the exact supported W8A16 format, honor `lm_head` ignore/fused mappings, and select the registered scheme through the config's `get_quant_method()` path. Preserve existing FP8 registration.
+  Must NOT do: Do not create/load weights yet beyond the minimum interfaces needed for construction; do not select upstream GPU kernels; do not add W4/W8A8/MoE schemes; do not infer AWQ routing from the directory name.
+  Parallelization: Wave 1 | Blocked by: none | Blocks: 2, 3, 4.
+  References: `/root/qwen3-awq-w8a16/Qwen3-8B-AWQ-W8A16-Channelwise/config.json:8,59-95`; `upstream-vllm-basic-compressed-tensors-paths.md:193-293,538-587`; `/root/hyperaccel-sdk/vllm/vllm_hyperaccel/platform.py:60-123`; `/root/hyperaccel-sdk/vllm/vllm_hyperaccel/quantization/quant_config.py:18-147`; vLLM-Ascend `quantization/methods/registry.py`, `methods/w8a16.py`, and `compressed_tensors_config.py`; `tests/python/unit_test/platform/test_platform.py:106-124`.
+  Acceptance criteria: `get_quantization_config("compressed-tensors")` returns the HyperAccel config; the checkpoint's metadata resolves to the registered W8A16 linear scheme; `lm_head` resolves unquantized; unsupported activation quantization, bit width, strategy, symmetry, grouping, dynamic mode, or format raises a precise `NotImplementedError`; FP8 tests remain green.
+  QA scenarios: Happy - run `pytest tests/python/unit_test/quantization tests/python/unit_test/platform/test_platform.py -q` and record output. Failure - parameterize unsupported configs and assert each fails before any weight or kernel path. Evidence `<attemptDir>/task-1-qwen3-dense-w8a16-quantization.txt`.
+  Commit: N | User did not request commits.
+
+- [x] 2. Load and validate packed Qwen3 W8A16 weights without a fallback (2 points)
+  What to do: Implement scheme-driven `create_weights()` for TP=1 using vLLM parameter/loader contracts. Preserve checkpoint-native `weight_packed` int32 words, BF16 per-output-channel `weight_scale`, and int64 `weight_shape`. Support ordinary Linear, `QKVParallelLinear` q/k/v shards, and `MergedColumnParallelLinear` gate/up shards through the real vLLM loaders. Make `process_weights_after_loading()` validation-only: verify required attributes, dtypes, ranks, packing divisibility, logical input size, aggregate/component output sizes, scale counts, and fused component ordering, then leave all packed parameters attached unchanged.
+  Must NOT do: Do not unpack/dequantize, delete packed parameters, create `layer.weight`, call `F.linear`, add zero-point/offset for this symmetric checkpoint, move to a guessed kernel layout, stamp a speculative LPU memory kind, or implement TP>1.
+  Parallelization: Wave 2 | Blocked by: 1 | Blocks: 3, 4.
+  References: local branch commit `f75ca7706`; checkpoint `model.safetensors.index.json` and `config.json:59-95`; upstream document `Weight-Loading Path:436-465`; `/root/hyperaccel-sdk/vllm/vllm_hyperaccel/models/qwen3.py:21-62`; vLLM parameter classes used in the branch adapter; `tests/python/unit_test/quantization/test_compressed_tensors.py` from branch `compressed-tensors-qwen3-w8a16`.
+  Acceptance criteria: synthetic ordinary, QKV, and gate/up loads preserve exact packed values/scales/order; post-load processing retains `weight_packed`, `weight_scale`, and `weight_shape`; no dense `weight` exists; malformed dtype, shape, scale count, packing, or fused component metadata fails deterministically before execution.
+  QA scenarios: Happy - run the focused compressed-tensors tests plus `pytest tests/python/unit_test/ops/test_linear.py -q`. Failure - corrupt each required tensor/metadata field and assert validation raises the expected message. Evidence `<attemptDir>/task-2-qwen3-dense-w8a16-quantization.txt`.
+  Commit: N | User did not request commits.
+
+- [x] 3. Register the opaque W8A16 op and hard-block runtime execution (2 points)
+  What to do: In `vllm_hyperaccel/ops/register_custom_ops.py`, mirror the existing `_rotary_embedding_impl` / fake / `direct_register_custom_op` / thin-wrapper pattern. Define the plugin-owned logical op `w8a16_linear(x, weight_packed, weight_scale, bias=None) -> Tensor`. Its fake implementation must return an empty tensor on `x.device` and `x.dtype` with shape `(*x.shape[:-1], weight_packed.shape[0])`, preserving symbolic leading dimensions. Register it idempotently with `mutates_args=[]` through `direct_register_custom_op`. Add the thin `torch.ops.vllm.w8a16_linear(...)` wrapper. Route the W8A16 scheme's `apply()` through this wrapper. The runtime implementation must immediately raise a specific `NotImplementedError` at the exact location where a future lazy `import legato_kernels` and `legato_kernels.w8a16_linear(...)` call will replace it.
+  Must NOT do: Do not call any existing GEMM, `F.linear`, CPU reference, dequantizer, or mock kernel; do not return fake data from the runtime implementation; do not mark any mutation; do not let a real invocation succeed.
+  Parallelization: Wave 3 | Blocked by: 1, 2 | Blocks: 4.
+  References: `/root/hyperaccel-sdk/vllm/vllm_hyperaccel/ops/register_custom_ops.py:1-21,203-277,280-329,332-377`; `/root/hyperaccel-sdk/vllm/vllm_hyperaccel/ops/utils.py:44-70`; vLLM-Ascend `ops/linear.py` custom-op registration and W8A16 scheme `apply()`; vLLM `direct_register_custom_op` documentation.
+  Acceptance criteria: `torch.ops.vllm.w8a16_linear` is registered once; fake/meta invocation produces the exact symbolic output shape/dtype/device; scheme `apply()` emits/calls the registered op; a real eager call raises the explicit kernel-unavailable `NotImplementedError`; there is no successful runtime path.
+  QA scenarios: Happy - use `torch.export.export` or the repository's established Dynamo export helper on a minimal module and assert the graph contains `torch.ops.vllm.w8a16_linear.default` without graph breaks or runtime-kernel execution. Failure - call the op with real tensors and assert the blocker is raised; call registration twice and assert idempotence. Evidence `<attemptDir>/task-3-qwen3-dense-w8a16-quantization.txt`.
+  Commit: N | User did not request commits.
+
+- [x] 4. Add durable real-checkpoint engine-load coverage without inference (2 points)
+  What to do: Create a self-contained `tests/python/integration/quantization/` suite with its own import-time HyperAccel environment fixture and `test_qwen3_w8a16_model_load.py`; do not import from or modify `model_smoke`. Construct `vllm.LLM(...)` directly with `/root/qwen3-awq-w8a16/Qwen3-8B-AWQ-W8A16-Channelwise`, a short max length, `block_size=1`, disabled multiprocessing/log stats, a bounded KV-memory estimator, and `hf_overrides={"num_hidden_layers": 1}` (raise to 2 only if one layer cannot exercise all required fused Linear types). Reach the loaded `HAModelRunner` model through explicit type-checked helper code owned by this suite. Assert resolved quantization, HyperAccel Qwen3 model class, at least one W8A16 scheme, packed int32 weights, BF16 channel scales, valid shape metadata, no dense fallback weight on quantized linears, and unquantized `lm_head`. Keep the targeted minimal Dynamo export from Todo 3 as the graph-readiness proof; do not export or execute the entire model.
+  Must NOT do: Do not depend on `model_smoke`, YAML parametrization, warmup, model forward, `generate`, serve, sampling, full compile, or the runtime custom-op implementation. Do not weaken the blocker to make initialization pass.
+  Parallelization: Wave 4 | Blocked by: 1, 2, 3 | Blocks: F1-F4.
+  References: `/root/hyperaccel-sdk/vllm/tests/python/integration/forward_test/conftest.py:33-43` for import-time plugin environment only; `/root/hyperaccel-sdk/vllm/vllm_hyperaccel/worker/ha_worker.py`; `/root/hyperaccel-sdk/vllm/vllm_hyperaccel/worker/ha_model_runner.py`; `/root/hyperaccel-sdk/vllm/vllm_hyperaccel/models/qwen3.py:21-62`; checkpoint config and upstream validation checklist `upstream-vllm-basic-compressed-tensors-paths.md:478-517` excluding execution assertions.
+  Acceptance criteria: `LLM(...)` completes without invoking `apply()`; model config reports `compressed-tensors`; loaded quantized modules retain valid packed state and use the HyperAccel W8A16 scheme; `lm_head` is unquantized; a guard monkeypatch on the runtime W8A16 implementation proves model initialization never crosses the blocker.
+  QA scenarios: Happy - run `pytest tests/python/integration/quantization/test_qwen3_w8a16_model_load.py -v`. Failure - monkeypatch the runtime op implementation to raise a sentinel and assert initialization still succeeds, then assert a deliberate real op invocation raises. Evidence `<attemptDir>/task-4-qwen3-dense-w8a16-quantization.txt`.
+  Commit: N | User did not request commits.
+
+- [x] 5. Resolve final review blockers without expanding execution support
+  What to do: Fail closed on every unsupported compressed-tensors path discovered by adversarial review: reject non-null output activation quantization before scheme selection, reject non-null KV-cache quantization, explicitly reject FusedMoE instead of delegating to upstream GPU/Marlin-oriented implementations, and validate packed/scale/shape source dtypes before any loader can cast them. Refactor the integration fixture so no runtime directory is created during collection; fixture setup may create resources only after it owns teardown, and interruption/collection probes must leave no roots. Add minimal user-facing documentation that W8A16 currently supports checkpoint loading/Dynamo preparation only and every real matmul hard-fails until the Legato kernel lands.
+  Must NOT do: Do not implement or call a kernel, add a fallback, loosen the runtime blocker, add TP>1/generation/attention support, rewrite the PR history, or broaden unrelated code.
+  Parallelization: Review-fix wave | Blocked by: 1-4 | Blocks: F1-F4.
+  References: final review findings for head `3ab8ecba7`; `vllm_hyperaccel/quantization/compressed_tensors.py`; `quantization/methods/w8a16.py`; `tests/python/integration/quantization/conftest.py`; project PR review policy sections C, D, G, H, J.
+  Acceptance criteria: adversarial output-activation, non-null KV, FusedMoE, and malformed source-dtype tests fail before the fix and pass afterward; real checkpoint load still passes; no fallback exists; collection interruption creates no runtime root; focused unit/integration tests and static checks pass.
+  QA scenarios: Happy - rerun the complete focused matrix and real-checkpoint load. Failure - directly probe each rejected unsupported path and interrupt collection/model load, asserting explicit errors and zero leaked roots. Evidence `<attemptDir>/task-5-review-fixes.txt`.
+  Commit: Y | `Fix W8A16 review blockers`, then normal push to the PR branch.
+
+- [x] 6. Close second-wave fail-closed and cleanup review gaps
+  What to do: Preserve serialized W8A16 checkpoint tensors through Qwen3 host casting so source dtypes reach their validating loaders unchanged; enforce the exact dense one-group `targets=["Linear"]`, `ignore=["lm_head"]`, no-sparsity config contract; resolve Bertha W8A16 before constructing any non-ignored Linear method; replace the new bare duplicate-registration error with a typed error; and contain all integration temp/cache paths under one owned root with opt-in no-follow cleanup receipts.
+  Must NOT do: Do not add a fallback, kernel implementation, transform/sparsity/attention/MoE support, broaden ignored layers, delete shared temporary paths, or weaken the runtime blocker.
+  Parallelization: Review-fix wave 2 | Blocked by: 1-5 | Blocks: F1-F4.
+  References: final review findings for head `e58c5f386`; `vllm_hyperaccel/models/qwen3.py`; `vllm_hyperaccel/quantization/compressed_tensors.py`; `tests/python/integration/quantization/conftest.py`.
+  Acceptance criteria: malformed scale dtypes fail before mutation through the full model loader; sparse/empty/attention-only/extra-ignore metadata fails before unquantized dispatch; only `lm_head` may be unquantized; normal and interrupted real loads remove their exact runtime root and reset FSim; explicit receipts are private and cannot follow symlinks; fresh adversarial verification confirms no upstream fallback constructor is reached.
+  QA scenarios: Run the full quantization unit directory, the real-checkpoint engine-load test, a genuine SIGINT load, static/no-excuse checks, and a fresh trapped-constructor verifier. Evidence `<attemptDir>/task-6-review-cycle2.txt`.
+  Commit: Y | three atomic source-plus-test commits, each normally pushed to the PR branch.
+
+- [x] 7. Collapse W8A16 to the minimal Ascend-style production and test surface
+  What to do: Follow the compact vLLM-Ascend organization while retaining the local compressed-tensors packed format. Keep exactly one custom-op test and one path-free in-memory Qwen3 model-loader test. Delete the dedicated integration fixture, runtime-root/receipt machinery, isolation coverage, and micro config/loading/validation tests. Remove the one-scheme registry and separate loader module; direct-import the W8A16 scheme and keep only behavior required for packed loading, fused routing, source dtype protection, strict no-fallback selection, and the opaque runtime blocker.
+  Must NOT do: Do not hardcode or configure a checkpoint path, use checkpoint/network I/O, create test-owned temp/cache roots, add FSim/hardware branches, implement a kernel/fallback, or retain hidden parameterized W8A16 tests.
+  Acceptance criteria: Filesystem contains exactly two W8A16 test files/functions; both pass under the available FSim build; the Qwen test uses a tiny real model with in-memory packed tensors and in-process HashStore; FP8/platform regressions and static checks pass; production/test diff removes substantially more code than it adds.
+  Evidence: commits `4fb89de53` through `9f5868134`; FSim two-test run `2 passed`; FP8/platform `18 passed`; refactor delta approximately `+292/-2015`.
+  Commit: Y | five atomic cleanup commits, each pushed normally.
+
+- [x] 8. Make the in-memory Qwen test share CI distributed state
+  What to do: Detect whether the default process group already exists, initialize HashStore only when the test owns it, always establish vLLM model-parallel state, and destroy only state owned by the test with nested cleanup. Remove the final unused scheme constant and redundant exception-class body.
+  Must NOT do: Do not add ordering/skip markers, TCP/FileStore/temp paths, global distributed monkeypatches, or change unrelated compiled-lm-head tests.
+  Acceptance criteria: CI-order reproduction passes; exact two W8A16 tests pass; the full unit suite passes with only expected FSim skips; Ruff/format/no-excuse/diff checks pass.
+  Evidence: commit `731aff39d`; local full suite `209 passed, 13 skipped`; prior CI double-init failure no longer reproduces.
+  Commit: Y | `Make W8A16 model test share distributed state`, pushed normally.
+
+## Final verification wave
+> Runs in parallel after ALL todos. ALL must APPROVE. Surface results and wait for the user's explicit okay before declaring complete.
+- [x] F1. Plan compliance audit - use Read/Grep plus `pytest tests/python/unit_test/quantization tests/python/unit_test/platform/test_platform.py tests/python/unit_test/ops/test_linear.py -q`; verify every numbered acceptance criterion against code and captured output. PASS only if tests exit 0, packed parameters remain after post-load validation, the graph-facing op is registered, and a real call is asserted to raise. Evidence `<attemptDir>/final-F1-plan-compliance.txt`.
+- [x] F2. Code quality review - run `ruff check` on every changed Python file and `lsp_diagnostics` on each; inspect registration idempotence, import side effects, annotations, parameter-loader ownership, fake/runtime signature parity, and actionable errors. PASS only with zero new diagnostics and no `any` suppression, ignored exception, duplicate registry side effect, or implicit executable fallback. Evidence `<attemptDir>/final-F2-code-quality.txt`.
+- [x] F3. Real manual QA - run `pytest tests/python/integration/quantization/test_qwen3_w8a16_model_load.py -v`, then run the targeted Dynamo-export test and the explicit eager blocker test from the focused custom-op suite. PASS only if engine initialization and export succeed without invoking the runtime implementation, the exported graph contains `torch.ops.vllm.w8a16_linear.default`, and eager invocation raises the exact kernel-unavailable `NotImplementedError`. Evidence `<attemptDir>/final-F3-manual-qa.txt`.
+- [x] F4. Scope fidelity - use `git diff --name-only`, `git diff --stat`, and `git diff` read-only; compare every changed hunk with Must have/Must NOT have. Also rerun the existing FP8 quantization tests. PASS only if changes are confined to W8A16 config/scheme, custom-op registration, and their unit plus self-contained quantization integration tests; no `model_smoke` dependency, kernel body, successful fallback, generation, attention, TP>1, unrelated refactor, or FP8 regression is present. Evidence `<attemptDir>/final-F4-scope-fidelity.txt`.
+
+## Commit strategy
+- Do not create commits unless the user explicitly requests them during execution.
+- If commits are later requested, keep one atomic commit per numbered todo with its tests in the same commit, in dependency order.
+
+## Success criteria
+- The local checkpoint automatically resolves to the HyperAccel compressed-tensors W8A16 linear scheme.
+- Ordinary and fused Qwen3 packed weights/scales/shape metadata load and remain intact after validation.
+- Dynamo captures one opaque `torch.ops.vllm.w8a16_linear` node using the fake implementation without tracing into a kernel launcher.
+- Every real W8A16 matmul attempt raises the intentional kernel-unavailable error; no fallback can produce output.
+- The self-contained quantization integration suite uses `vllm.LLM(...)` to initialize the local reduced-layer checkpoint and exposes the expected packed quantized model state without forward execution or `model_smoke` dependency.
+- Focused unit, platform, linear, and self-contained quantization integration tests pass; diagnostics are clean on changed files.

.omo/run-continuation/ses_04e6f52a3ffeP0kwyFgLj4zn8r.json

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.omo/run-continuation/ses_04ec94d42ffeFdEBgGHz224ZfK.json

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.omo/run-continuation/ses_04ed0a91effe8bBTkHMWUQol6o.json

@@ -0,0 +1,10 @@
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.omo/run-continuation/ses_04efee597ffeqnTHUit7ZE0m9q.json

@@ -0,0 +1,10 @@
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.omo/run-continuation/ses_04efee605ffej6PFkSteD4OwRq.json

@@ -0,0 +1,10 @@
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.omo/run-continuation/ses_04efee691ffeyxLdMf4CZr8aPD.json

@@ -0,0 +1,10 @@
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.omo/run-continuation/ses_04effab79ffe1jqSma4bwZeE3Q.json

@@ -0,0 +1,10 @@
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.omo/run-continuation/ses_04f09ee16ffeo0xqR7QNmJyy1O.json

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.omo/run-continuation/ses_04f1680f2ffema0IM0okrcFtKB.json

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.omo/run-continuation/ses_04f168335ffe34vT8Rr7PpoNpy.json

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.omo/run-continuation/ses_04f168562ffeCY43U7B1nUSrOQ.json

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.omo/run-continuation/ses_04f168583ffeWrcsHKzSRpTqCB.json

@@ -0,0 +1,10 @@
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.omo/run-continuation/ses_04f168a79ffeYLY2cKbTMnaOeb.json

@@ -0,0 +1,10 @@
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.omo/run-continuation/ses_04f1a07e3ffe7vGOTeQQqVTnvA.json

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.omo/run-continuation/ses_04f236f0cffe1LYnzJQQtDu6gz.json

@@ -0,0 +1,10 @@
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.omo/run-continuation/ses_04f238077ffe9m3gBLOW5YM7ae.json

@@ -0,0 +1,10 @@
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.omo/run-continuation/ses_04f239262ffejNUjpNYEWV186C.json

@@ -0,0 +1,10 @@
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.omo/run-continuation/ses_04f245b36ffeF5wlxHP81Za9eb.json

@@ -0,0 +1,10 @@
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