[None][feat] Rubin fp4 mla core (P1) - #18478
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Actionable comments posted: 2
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Inline comments:
In `@tensorrt_llm/_torch/pyexecutor/_util.py`:
- Around line 150-151: Annotate all four modified functions: in
tensorrt_llm/_torch/pyexecutor/_util.py lines 150-151, add the return annotation
to get_kv_cache_manager_cls; in the same file lines 757-758, add the return
annotation to _validate_or_fallback_kv_cache_manager_v2; in
tensorrt_llm/_torch/pyexecutor/resource_manager.py lines 1580-1581, add -> int
to KVCacheManager.get_cache_size_per_token; and in tensorrt_llm/_utils.py lines
831-834, add parameter and return annotations to QuantModeWrapper.__getattr__,
using the appropriate existing types and conventions.
In `@tensorrt_llm/_utils.py`:
- Around line 831-834: Add a regression unit test for QuantModeWrapper that
deep-copies the wrapper and verifies quant_mode.has_fp4_kv_cache() remains
callable and returns the expected FP4 MLA configuration result, covering the
protocol-hook guard in the wrapper attribute handling.
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📒 Files selected for processing (6)
tensorrt_llm/_torch/pyexecutor/_util.pytensorrt_llm/_torch/pyexecutor/config_utils.pytensorrt_llm/_torch/pyexecutor/model_loader.pytensorrt_llm/_torch/pyexecutor/resource_manager.pytensorrt_llm/_utils.pytests/integration/defs/accuracy/test_llm_api_pytorch.py
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PR_Github #72844 [ run ] triggered by Bot. Commit: |
Signed-off-by: Tracin <10434017+Tracin@users.noreply.github.com>
Signed-off-by: Tracin <10434017+Tracin@users.noreply.github.com>
Signed-off-by: Tracin <10434017+Tracin@users.noreply.github.com>
Signed-off-by: root <root@hecate0124.hecate.clusters.nvidia.com>
Signed-off-by: Tracin <10434017+Tracin@users.noreply.github.com>
Signed-off-by: Tracin <10434017+Tracin@users.noreply.github.com>
Signed-off-by: Tracin <10434017+Tracin@users.noreply.github.com>
Signed-off-by: Tracin <10434017+Tracin@users.noreply.github.com>
Signed-off-by: Tracin <10434017+Tracin@users.noreply.github.com>
Signed-off-by: Tracin <10434017+Tracin@users.noreply.github.com>
Align FP4 routing and V2 selection with resolved quantization, validate unsupported profiles before allocation, and configure draft-cache sharing before model construction. Drain auxiliary work on context failures, remove duplicate cache append and unrelated executor/V1 changes, scope MTP metadata updates, and consolidate kernel helpers. Strengthen existing routing and GSM8K checks and register the Rubin accuracy case in the QA test list. Signed-off-by: Tracin <10434017+Tracin@users.noreply.github.com>
Normalize integer quant modes while preserving QuantModeWrapper behavior in the FP4 KV-cache predicate. Share the predicate across routing, validation, and FP4 cache guards, and extend existing tests to cover integer, enum, and wrapper representations. Signed-off-by: Tracin <10434017+Tracin@users.noreply.github.com>
Do not forward missing Python protocol hooks through QuantModeWrapper query aggregation. This prevents an eagerly cached quant_mode from becoming an integer during deepcopy. Remove the integer-mode compatibility workaround and restore test_model_config.py to the PR base. Signed-off-by: Tracin <10434017+Tracin@users.noreply.github.com>
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Use a real QuantConfig and expose the backend, MLA dimensions, and sparse configuration required by FP4 MLA routing. Preserve the existing test cases and map the unquantized sentinel to the native None value. Signed-off-by: Tracin <10434017+Tracin@users.noreply.github.com>
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Dev Engineer Review
SELFKONLYand FP4 MLA cache configurations toFp4MlaKVCacheManagerV2.has_fp4_kv_cachehelper and readsquant_config.quant_modedirectly. Verify callers with missing configuration and copied quantization modes.QuantModeWrapperprotocol handling sodeepcopydoes not convertquant_modeto an integer.QA Engineer Review
tests/unittest/_torch/attention/test_fp4_mla.pyadds 12 tests for page tables, CUDA-graph lengths, cache sizing, cache roles, packed V data, decode accuracy, block reuse, speculative-decoding tails, and full, selected, and page-boundary-crossing V-cache repacking. The file is not shown in atest-db/orqa/test list.tests/integration/defs/accuracy/test_llm_api_pytorch.pyupdates NVFP4 MLA detection to usequant_config.quant_mode.has_fp4_kv_cache(). Verify configured and missing-configuration paths.tests/integration/test_lists/qa/llm_function_core.txtaddsTestDeepSeekV3Lite::test_nvfp4_mla_gsm8k, marked for SM107 manual QA. The entry is in the appropriate QA list.Per-File QA Perspective
cpp/tensorrt_llm/batch_manager/kvCacheManager.cpp: Verify the V1 rejection for NVFP4SELFKONLYand the expected V2 routing.tensorrt_llm/_torch/pyexecutor/_util.py: Verify FP4 detection and manager routing when quantization configuration is absent.tensorrt_llm/_torch/pyexecutor/py_executor_creator.py: Verify 128-token FP4 blocks, disabled reuse, warnings, and unchanged non-FP4 behavior.tensorrt_llm/_torch/pyexecutor/resource_manager.py: Verify V1 rejection and FP4 MLA cache-size calculations.tensorrt_llm/_torch/speculative/mtp.py: Verify metadata refresh after KV-length changes.tensorrt_llm/_torch/attention/ATTENTION_DEVELOPER_GUIDE.md: Verify that documented FP4 MLA restrictions match runtime behavior.tensorrt_llm/_torch/attention/backends/fmha/__init__.py: Verify stable export ofFp4MlaFmha.tensorrt_llm/_torch/attention/backends/fmha/fallback.py: Verify fallback is unavailable for FP4 MLA caches.tensorrt_llm/_torch/attention/backends/fmha/fp4_mla.py: Verify context and generation dispatch, validation, temporary-state cleanup, and cache updates.tensorrt_llm/_torch/attention/backends/fmha/registry.py: Verifyfp4_mlabackend discovery.tensorrt_llm/_torch/attention/backends/fp4_mla/cache_manager.py: Verify cache roles, page geometry, capacity, page tables, and memory accounting.tensorrt_llm/_torch/attention/backends/fp4_mla/fp4_mla_context.py: Verify architecture gates, FP8 context execution, asynchronous updates, and capacity errors.tensorrt_llm/_torch/attention/backends/fp4_mla/fp4_mla_cutedsl_v_repack.py: Verify reference and CuTeDSL repacking for indexed pages, generation lengths, alignment, and page boundaries.tensorrt_llm/_torch/attention/backends/fp4_mla/fp4_mla_kernels.py: Verify quantization, RoPE, cache writes, masking, synchronization, and dtype handling.tensorrt_llm/_torch/attention/backends/fp4_mla/fp4_mla_triton.py: Verify TMA, prepacked-V, partial-page, and CUDA-graph dispatch paths.tensorrt_llm/_torch/attention/backends/trtllm.py: Verify metadata refresh, page-table updates, cache scattering, and fused query quantization.tensorrt_llm/_torch/attention/mla.py: Verify compatibility errors, fused FP4 query quantization, and skip-RoPE generation.tensorrt_llm/_torch/pyexecutor/kv_cache/kv_cache_manager_v2.py: Verify MLA roles, generation-capacity sizing, SWA quotas, and warmup batches.tensorrt_llm/_torch/pyexecutor/config_utils.py: Verify removal ofhas_fp4_kv_cacheand all updated imports and callers.tensorrt_llm/_torch/pyexecutor/model_loader.py: Verify FP4 MLA validation during model loading.tests/integration/defs/accuracy/test_llm_api_pytorch.py: Verify NVFP4 MLA setup and accuracy behavior.tests/unittest/_torch/attention/test_fp4_mla.py: Verify all listed cache, kernel, metadata, repacking, and speculative-decoding cases; no test-list entry is shown.tests/integration/test_lists/qa/llm_function_core.txt: Verify the SM107 selector and manual-QA execution of the Dense FP4 MLA GSM8K test.tensorrt_llm/_utils.py: Verifydeepcopyand other protocol operations onQuantModeWrapper.Description
Support W4A4 in dense MLA.
Test Coverage
E2E GSM8K test for DSV3.2
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