Expand L4/L5 test coverage: golden data, seq2seq generation, ci_skip_reason - #183
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…der edge cases New L4 golden files (15): - encoder: clip-text-model, deberta-v3-base, flaubert-base, roformer-chinese-small, xmod-base - vision: cvt-13, depth-anything-small, mobilevit-small, mobilevitv2-1.0, pvt-v2-b0, segformer-b0, swin2sr, yolos-tiny - seq2seq: fsmt-wmt19, plbart-base New L5 generation files (2): fsmt-wmt19, plbart-base Generator fixes: - Handle 4D vision outputs [B,C,H,W] by flattening to 1D - Add vision task types: depth-estimation, image-segmentation, image-to-image, object-detection - Handle CLIP text sub-model extraction in encoder generator - Handle X-MOD language setting in encoder generator - Fall back to specific AutoModel variants for vision models (DepthEstimation, SemanticSegmentation, ImageToImage) - Handle missing decoder_start_token_id in seq2seq generator Added skip_reasons for 7 models requiring special inputs or unsupported architectures: bros-base (bbox), ernie-m-tiny (tokenizer), layoutlmv2-base (detectron2), mega-base (model_type), nezha-cn-base (model_type), layoutlmv3-base (bbox+image+text), trocr-small (vision-encoder-decoder) Coverage: 89→104 L4 tests, 60→62 L5 tests Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Signed-off-by: Justin Chu <justinchu@microsoft.com>
Move the pass/xfail/skip breakdown from a separate card into the L3 level card as an annotation, consistent with L4/L5 cards that show skipped/awaiting-data counts inline. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Signed-off-by: Justin Chu <justinchu@microsoft.com>
🏗️ Architecture Diff
No architecture changes detected. ✅ Legend: ⚪ No change · 🔵 Minor (attrs/inits) · 🟡 Moderate (nodes added/removed) · 🔴 Major (interface changed) |
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Pull request overview
Adds missing L4/L5 golden reference outputs for additional HuggingFace models and hardens the golden-data generator to handle more vision/encoder edge cases (multi-modal wrappers, task routing, and non-standard output shapes).
Changes:
- Added golden reference JSONs for new encoder, vision, and seq2seq models (including L5 generation markers for seq2seq).
- Updated golden generation + torch reference helpers to support additional AutoModel fallbacks, CLIP text-only submodules, X-MOD language setup, and broader vision output handling.
- Added explicit
skip_reasonentries for models that require unsupported inputs or incompatible tooling.
Reviewed changes
Copilot reviewed 27 out of 27 changed files in this pull request and generated 3 comments.
Show a summary per file
| File | Description |
|---|---|
scripts/generate_golden.py |
Generator updates for CLIP text extraction, X-MOD language setup, PLBart decoder start token fallback, vision output flattening, and new task-type routing. |
src/mobius/_testing/torch_reference.py |
Vision model loading now tries multiple AutoModel variants; vision forward now falls back across multiple output fields. |
testdata/golden/vision/yolos-tiny.json |
New golden reference for YOLOS tiny. |
testdata/golden/vision/swin2sr.json |
New golden reference for Swin2SR. |
testdata/golden/vision/segformer-b0.json |
New golden reference for SegFormer B0. |
testdata/golden/vision/pvt-v2-b0.json |
New golden reference for PVTv2 B0. |
testdata/golden/vision/mobilevitv2-1.0.json |
New golden reference for MobileViTv2 1.0. |
testdata/golden/vision/mobilevit-small.json |
New golden reference for MobileViT small. |
testdata/golden/vision/depth-anything-small.json |
New golden reference for Depth Anything small. |
testdata/golden/vision/cvt-13.json |
New golden reference for CvT-13. |
testdata/golden/seq2seq/plbart-base.json |
New L4 golden reference for PLBart base. |
testdata/golden/seq2seq/plbart-base_generation.json |
New L5 generation marker/reference for PLBart base. |
testdata/golden/seq2seq/fsmt-wmt19.json |
New L4 golden reference for tiny WMT19 EN→DE FSMT. |
testdata/golden/seq2seq/fsmt-wmt19_generation.json |
New L5 generation marker/reference for tiny WMT19 EN→DE FSMT. |
testdata/golden/encoder/xmod-base.json |
New golden reference for X-MOD base. |
testdata/golden/encoder/roformer-chinese-small.json |
New golden reference for RoFormer Chinese small. |
testdata/golden/encoder/flaubert-base.json |
New golden reference for FlauBERT base. |
testdata/golden/encoder/deberta-v3-base.json |
New golden reference for DeBERTa-v3 base. |
testdata/golden/encoder/clip-text-model.json |
New golden reference for CLIP text model encoder path. |
testdata/cases/vision/layoutlmv3-base.yaml |
Adds skip reason for LayoutLMv3 (requires mixed modality inputs). |
testdata/cases/seq2seq/trocr-small.yaml |
Adds skip reason for TrOCR (vision-encoder-decoder inputs). |
testdata/cases/encoder/nezha-cn-base.yaml |
Adds skip reason (unrecognized model type in current transformers). |
testdata/cases/encoder/mega-base.yaml |
Adds skip reason (unrecognized model type in current transformers). |
testdata/cases/encoder/layoutlmv2-base.yaml |
Adds skip reason (requires detectron2 + bbox/image inputs). |
testdata/cases/encoder/ernie-m-tiny.yaml |
Adds skip reason (tokenizer incompatibility). |
testdata/cases/encoder/bros-base.yaml |
Adds skip reason (requires bbox inputs not supported). |
Performance Comparison
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Codecov Report❌ Patch coverage is
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rui-ren
approved these changes
Apr 21, 2026
- Use safe getattr chain for generation_config to avoid AttributeError when model lacks generation_config attribute - Handle tuple/list outputs in torch_vision_forward generic fallback, not just dict-like ModelOutput - Branch by output rank in _generate_image_classification: CLS token for 2-D (seq_len, hidden), flatten for 3-D+ (C, H, W) feature maps Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Signed-off-by: Justin Chu <justinchu@microsoft.com>
- Add OnnxSeq2SeqGenerator for encoder-decoder L5 generation tests - Add seq2seq to _GENERATION_SUPPORTED_TASKS in e2e_golden_test.py - Add ci_skip_reason YAML field + schema + dashboard support - Generate golden data for ~30 new models across all task types - Add skip_reason for models with no safetensors or code bugs - Set min_token_match_ratio=0.1 for zamba2 (known Mamba divergence) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Signed-off-by: Justin Chu <justinchu@microsoft.com>
justinchuby
changed the title
…ministral-3-3b - Add output_proj_dims field to Gemma4AudioConfig - Extract output_proj_dims from HF audio config in from_transformers - Remove skip_reason from gemma-4-e4b-it (VL), gemma-4-e4b (text), gemma-4-e4b-it-audio (speech), and ministral-3-3b - Update test configs with output_proj_dims Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Signed-off-by: Justin Chu <justinchu@microsoft.com>
The model weights are natively float8_e4m3fn with per-tensor scales. HF inference requires w8a8_fp8_matmul Triton kernel which is not available in our environment. mobius build() handles FP8 dequantization, but we cannot generate HF reference golden data. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Signed-off-by: Justin Chu <justinchu@microsoft.com>
- Fix 5 seq2seq YAML files using "L4,L5" (invalid) to "L4+L5" (valid per schema enum) - Remove gemma4_text static-cache entry from arch_diff: Gemma4DecoderLayer inherits from nn.Module, not DecoderLayer, so static cache is not supported Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Signed-off-by: Justin Chu <justinchu@microsoft.com>
- Add AutoModelForObjectDetection to vision model auto_classes fallback - Clarify ci_skip_reason schema: document skip_reason precedence - Fix OnnxSeq2SeqGenerator docstring: document text-only limitation - Fix _GENERATION_SUPPORTED_TASKS comment: seq2seq is implemented - Split speech-to-text from seq2seq in L5 dispatch: skip with clear message instead of routing to incompatible seq2seq generator Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Signed-off-by: Justin Chu <justinchu@microsoft.com>
justinchuby
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Apr 22, 2026
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Addressed all open review comments in b690181:
AutoModelForObjectDetection (torch_reference.py:390): ✅ Added to auto_classes list.
2D output handling in golden extraction (generate_golden.py:764): Acknowledged — the current ndim == 2 → take first row heuristic works for all models we generate golden data for today (image classification, depth estimation, segmentation). Object detection models that produce (num_queries, num_classes) 2D outputs aren't generating golden data yet (they're skipped). When we add them, we'll need to flatten instead. Leaving as-is since changing it now would affect existing golden data.
OnnxSeq2SeqGenerator scope (generation.py:264): ✅ Added docstring clarifying this is text-to-text only and NOT suitable for speech-to-text (Whisper) which needs input_features + decoder_input_ids + position_ids.
ci_skip_reason schema (schema.json:143): ✅ Updated description to document skip_reason precedence.
_GENERATION_SUPPORTED_TASKS comment (e2e_golden_test.py:1310): ✅ Fixed stale comment — seq2seq IS implemented now. Updated to note only speech-to-text is pending.
speech-to-text routing (e2e_golden_test.py:1480): ✅ Split speech-to-text from seq2seq dispatch — now pytest.skips with clear message about needing audio features + decoder_input_ids/position_ids instead of routing to incompatible seq2seq generator.
Implement OnnxSpeechToTextGenerator for Whisper-style encoder-decoder models. Add _run_speech_to_text_generation() test function that handles the full pipeline: audio loading, encoder forward, decoder generation with forced prefix stripping. Key changes: - New OnnxSpeechToTextGenerator class in generation.py - Speech-to-text dispatch in e2e_golden_test.py - Add eos_token_id to YAML generation schema - Configure whisper-tiny.yaml with eos_token_id for proper stopping - Remove empty skip_reason from whisper-tiny and qwen3-asr Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Signed-off-by: Justin Chu <justinchu@microsoft.com>
gramalingam
approved these changes
Apr 22, 2026
…riant Implement _run_speech_language_generation() for the 3-model speech pipeline (audio_encoder → embedding → decoder). Supports 3D position_ids for models like Qwen3-ASR. Add two Qwen3-ASR test cases: - qwen3-asr: auto language detection (no text prompt) - qwen3-asr-en: forced English via decoder prefix tokens Update generate_golden.py to support forced language prefix for Qwen3-ASR when prompts are specified in the YAML. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Signed-off-by: Justin Chu <justinchu@microsoft.com>
justinchuby
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Apr 22, 2026
Move the pass/xfail/skip breakdown from a separate card into the L3 level card as an annotation, consistent with L4/L5 cards that show skipped/awaiting-data counts inline. This change was lost in PR #183 when a later commit on the branch accidentally reverted the dashboard template. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Signed-off-by: Justin Chu <justinchu@microsoft.com>
justinchuby
added a commit
that referenced
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Apr 22, 2026
Move the pass/xfail/skip breakdown from a separate card into the L3 level card as an annotation, consistent with L4/L5 cards that show skipped/awaiting-data counts inline. This change was made in commit d0e6d49 on the `justinchu/generate-golden-data` branch but was accidentally reverted by a later commit (2fb6b80) that overwrote the dashboard template from a stale working copy. The squash merge in PR #183 faithfully reflected the branch tip, which had already lost the change. **Only file changed**: `scripts/templates/dashboard.html.j2` (+11, -15) Signed-off-by: Justin Chu <justinchu@microsoft.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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Summary
Expands L4/L5 test coverage with golden data for ~45 models, adds seq2seq L5 generation support, introduces
ci_skip_reasoninfrastructure, and fixes Gemma4 audio config extraction.Bug fixes
output_proj_dims: Added missing field toGemma4AudioConfigand extraction infrom_transformers— was defaulting to text hidden_size (2560) instead of actual audio output dim (1536), causing weight shape mismatchInfrastructure
OnnxSeq2SeqGeneratorinsrc/mobius/_testing/generation.py— encoder-decoder L5 generation loop with cross-attention + self-attention KV cache managementci_skip_reasonYAML field — separates "too large for CI" from "fundamentally broken" (skip_reason)GITHUB_ACTIONSenv var;ci_skip_reasoncases skip in CI onlyci_skip_reasonGolden data generation fixes
getattrforgeneration_configNew golden data (~45 models)
Skip reason triage
skip_reasonskip_reasonci_skip_reasonmin_token_match_ratio=0.1(known Mamba state divergence)