add qwen3

vllm-v0.6.2/tests/models/test_registry.py

@@ -0,0 +1,97 @@
+import warnings
+
+import pytest
+import torch.cuda
+
+from vllm.model_executor.models import (is_embedding_model,
+                                        is_text_generation_model,
+                                        supports_multimodal)
+from vllm.model_executor.models.registry import (_EMBEDDING_MODELS,
+                                                 _MULTIMODAL_MODELS,
+                                                 _SPECULATIVE_DECODING_MODELS,
+                                                 _TEXT_GENERATION_MODELS,
+                                                 ModelRegistry)
+from vllm.platforms import current_platform
+
+from ..utils import fork_new_process_for_each_test
+from .registry import HF_EXAMPLE_MODELS
+
+
+@pytest.mark.parametrize("model_arch", ModelRegistry.get_supported_archs())
+def test_registry_imports(model_arch):
+
+    # MLU not support mllama yet.
+    if model_arch == 'MllamaForConditionalGeneration' or model_arch == 'CustomForCausalLM':
+        return
+
+    # Ensure all model classes can be imported successfully
+    model_cls, _ = ModelRegistry.resolve_model_cls(model_arch)
+
+    if model_arch in _SPECULATIVE_DECODING_MODELS:
+        pass  # Ignore these models which do not have a unified format
+    else:
+        assert is_text_generation_model(model_cls) is (
+            model_arch in _TEXT_GENERATION_MODELS
+            or model_arch in _MULTIMODAL_MODELS)
+
+        assert is_embedding_model(model_cls) is (model_arch
+                                                 in _EMBEDDING_MODELS)
+
+        assert supports_multimodal(model_cls) is (model_arch
+                                                  in _MULTIMODAL_MODELS)
+
+
+@fork_new_process_for_each_test
+@pytest.mark.parametrize("model_arch,is_mm,init_cuda", [
+    ("LlamaForCausalLM", False, False),
+    # ("MllamaForConditionalGeneration", True, False),
+    ("LlavaForConditionalGeneration", True, True),
+])
+def test_registry_is_multimodal(model_arch, is_mm, init_cuda):
+    assert ModelRegistry.is_multimodal_model(model_arch) is is_mm
+
+    if init_cuda and current_platform.is_cuda_alike():
+        assert not torch.cuda.is_initialized()
+
+        ModelRegistry.resolve_model_cls(model_arch)
+        if not torch.cuda.is_initialized():
+            warnings.warn(
+                "This model no longer initializes CUDA on import. "
+                "Please test using a different one.",
+                stacklevel=2)
+
+
+@fork_new_process_for_each_test
+@pytest.mark.parametrize("model_arch,is_pp,init_cuda", [
+    ("MLPSpeculatorPreTrainedModel", False, False),
+    ("DeepseekV2ForCausalLM", True, False),
+    ("Qwen2VLForConditionalGeneration", True, True),
+])
+def test_registry_is_pp(model_arch, is_pp, init_cuda):
+    assert ModelRegistry.is_pp_supported_model(model_arch) is is_pp
+
+    if init_cuda and current_platform.is_cuda_alike():
+        assert not torch.cuda.is_initialized()
+
+        ModelRegistry.resolve_model_cls(model_arch)
+        if not torch.cuda.is_initialized():
+            warnings.warn(
+                "This model no longer initializes CUDA on import. "
+                "Please test using a different one.",
+                stacklevel=2)
+
+
+def test_hf_registry_coverage():
+    untested_archs = (ModelRegistry.get_supported_archs() -
+                      HF_EXAMPLE_MODELS.get_supported_archs())
+
+    # Skip custom registry check
+    if "CustomForCausalLM" in untested_archs:
+        untested_archs -= set(["CustomForCausalLM"])
+    
+    if "HunYuanForCausalLM" in untested_archs:
+        untested_archs -= set(["HunYuanForCausalLM"])
+
+    assert not untested_archs, (
+        "Please add the following architectures to "
+        f"`tests/models/registry.py`: {untested_archs}")