Add qwen3 moe experts only test

Author: cjluo-nv

tests/unit/torch/quantization/plugins/test_huggingface.py

@@ -234,6 +234,57 @@ def test_is_homogeneous_hf_model_gpt_oss():
     assert is_homogeneous_hf_model(model)
 
 
+def test_qwen3_moe_nvfp4_experts_only_export_exclude_modules(tmp_path):
+    """Test that NVFP4_EXPERTS_ONLY_CFG correctly excludes non-expert modules in HF export.
+
+    For a Qwen3 MoE model, only routed expert layers (mlp.experts.*) should be quantized.
+    Attention layers and lm_head should appear in the exported hf_quant_config.json
+    exclude_modules.
+
+    Reference: https://huggingface.co/nvidia/Qwen3.5-397B-A17B-NVFP4/blob/main/hf_quant_config.json
+    """
+    from modelopt.torch.export.unified_export_hf import export_hf_checkpoint
+
+    model = get_tiny_qwen3_moe()
+    # from_config doesn't set architectures; export code requires it
+    model.config.architectures = ["Qwen3MoeForCausalLM"]
+
+    # Quantize with NVFP4_EXPERTS_ONLY_CFG (targets only *mlp.experts* patterns)
+    mtq.quantize(model, mtq.NVFP4_EXPERTS_ONLY_CFG, lambda m: m(**m.dummy_inputs))
+
+    # Export
+    export_dir = tmp_path / "qwen3_moe_nvfp4_experts_only"
+    export_hf_checkpoint(model, export_dir=export_dir)
+
+    # Load the generated hf_quant_config.json
+    import json
+
+    hf_quant_config_path = export_dir / "hf_quant_config.json"
+    assert hf_quant_config_path.exists(), "hf_quant_config.json should be generated"
+    with open(hf_quant_config_path) as f:
+        hf_quant_config = json.load(f)
+
+    quant_section = hf_quant_config["quantization"]
+    assert quant_section["quant_algo"] == "NVFP4"
+    exclude_modules = quant_section["exclude_modules"]
+
+    # Attention layers must be excluded
+    assert any("self_attn" in m for m in exclude_modules), (
+        f"self_attn should be in exclude_modules, got: {exclude_modules}"
+    )
+
+    # lm_head must be excluded
+    assert any("lm_head" in m for m in exclude_modules), (
+        f"lm_head should be in exclude_modules, got: {exclude_modules}"
+    )
+
+    # No exclude pattern should match the routed experts
+    for pattern in exclude_modules:
+        assert not ("mlp.experts." in pattern and "shared" not in pattern), (
+            f"Routed expert pattern should NOT be excluded: {pattern}"
+        )
+
+
 def test_hf_decoder_discoverer_registration_path():
     model = get_tiny_llama()
     assert any(