Add QDQ build feature

[Copilot]

Adds an opt-in build feature for emitting QDQ operators when validating quantized Gemma 4-style exports. --features qdq forces quantized MatMulNBits weights through the existing standard ONNX QDQ lowering path.

• CLI feature

  • Registers qdq in the cargo-style --features set.
  • Passes the toggle through mobius build.

• Build / optimization plumbing

  • Adds qdq to build() and build_from_module().
  • Updates optimize_model() so com.microsoft::MatMulNBits is inlined to DequantizeLinear + MatMul when requested, independent of EP defaults.

• Docs and coverage

  • Documents qdq in README and CLI reference.
  • Adds focused tests for CLI pass-through and CPU-side QDQ lowering.

mobius build --model google/gemma-4-12B out/ \
  --features qdq

• Fixes Validate QDQ with gemma 4 #332

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[github-actions]

🏗️ Architecture Diff

Comparing 9567144 → 3c9c4b4

Model	Sub-model	Changes	Status

No architecture changes detected. ✅

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Legend: ⚪ No change · 🔵 Minor (attrs/inits) · 🟡 Moderate (nodes added/removed) · 🔴 Major (interface changed)

[github-actions]

Performance Comparison

Comparing 9567144 → 3c9c4b4

Model	Metric	Baseline	Current	Delta
bert (feature-extraction)	model_size_bytes	359 KB	359 KB	+0.0%	⚪
bert (feature-extraction)	num_nodes	60	60	+0.0%	⚪
falcon	model_size_bytes	364 KB	364 KB	+0.0%	⚪
falcon	num_nodes	68	68	+0.0%	⚪
gemma2	model_size_bytes	428 KB	428 KB	+0.0%	⚪
gemma2	num_nodes	107	107	+0.0%	⚪
gpt2	model_size_bytes	388 KB	388 KB	+0.0%	⚪
gpt2	num_nodes	54	54	+0.0%	⚪
llama	model_size_bytes	425 KB	425 KB	+0.0%	⚪
llama	num_nodes	62	62	+0.0%	⚪
llama (static-cache)	model_size_bytes	425 KB	425 KB	+0.0%	⚪
llama (static-cache)	num_nodes	58	58	+0.0%	⚪
mamba (ssm-text-generation)	model_size_bytes	296 KB	296 KB	+0.0%	⚪
mamba (ssm-text-generation)	num_nodes	98	98	+0.0%	⚪
phi3	model_size_bytes	421 KB	421 KB	+0.0%	⚪
phi3	num_nodes	60	60	+0.0%	⚪
phi3 (static-cache)	model_size_bytes	421 KB	421 KB	+0.0%	⚪
phi3 (static-cache)	num_nodes	56	56	+0.0%	⚪
qwen2	model_size_bytes	425 KB	425 KB	+0.0%	⚪
qwen2	num_nodes	62	62	+0.0%	⚪
qwen2 (static-cache)	model_size_bytes	425 KB	425 KB	+0.0%	⚪
qwen2 (static-cache)	num_nodes	58	58	+0.0%	⚪
qwen3_5_moe (hybrid-text-generation)	model_size_bytes	506 KB	506 KB	+0.0%	⚪
qwen3_5_moe (hybrid-text-generation)	num_nodes	275	275	+0.0%	⚪
qwen3_5_text (hybrid-text-generation)	model_size_bytes	458 KB	458 KB	+0.0%	⚪
qwen3_5_text (hybrid-text-generation)	num_nodes	129	129	+0.0%	⚪
qwen3_5_vl (hybrid-qwen-vl)	model_size_bytes	977 KB	977 KB	+0.0%	⚪
qwen3_5_vl (hybrid-qwen-vl)	num_nodes	431	431	+0.0%	⚪
t5 (seq2seq)	model_size_bytes	836 KB	836 KB	+0.0%	⚪
t5 (seq2seq)	num_nodes	166	166	+0.0%	⚪
whisper (speech-to-text)	model_size_bytes	1008 KB	1008 KB	+0.0%	⚪
whisper (speech-to-text)	num_nodes	128	128	+0.0%	⚪

No performance regressions.