Sync from v0.13

tests/models/test_registry.py

@@ -0,0 +1,120 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import warnings
+
+import pytest
+import torch.cuda
+
+from vllm.model_executor.models import (
+    is_pooling_model,
+    is_text_generation_model,
+    supports_multimodal,
+)
+from vllm.model_executor.models.adapters import (
+    as_embedding_model,
+    as_seq_cls_model,
+)
+from vllm.model_executor.models.registry import (
+    _MULTIMODAL_MODELS,
+    _SPECULATIVE_DECODING_MODELS,
+    _TEXT_GENERATION_MODELS,
+    ModelRegistry,
+)
+from vllm.platforms import current_platform
+
+from ..utils import create_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):
+    # Skip if transformers version is incompatible
+    model_info = HF_EXAMPLE_MODELS.get_hf_info(model_arch)
+    model_info.check_transformers_version(on_fail="skip")
+    # Ensure all model classes can be imported successfully
+    model_cls = ModelRegistry._try_load_model_cls(model_arch)
+    assert model_cls is not None
+
+    if model_arch in _SPECULATIVE_DECODING_MODELS:
+        return  # Ignore these models which do not have a unified format
+
+    if model_arch in _TEXT_GENERATION_MODELS or model_arch in _MULTIMODAL_MODELS:
+        assert is_text_generation_model(model_cls)
+
+    # All vLLM models should be convertible to a pooling model
+    assert is_pooling_model(as_seq_cls_model(model_cls))
+    assert is_pooling_model(as_embedding_model(model_cls))
+
+    if model_arch in _MULTIMODAL_MODELS:
+        assert supports_multimodal(model_cls)
+
+
+@create_new_process_for_each_test()
+@pytest.mark.parametrize(
+    "model_arch,is_mm,init_cuda,is_ce",
+    [
+        ("LlamaForCausalLM", False, False, False),
+        ("LlavaForConditionalGeneration", True, True, False),
+        ("BertForSequenceClassification", False, False, True),
+        ("RobertaForSequenceClassification", False, False, True),
+        ("XLMRobertaForSequenceClassification", False, False, True),
+    ],
+)
+def test_registry_model_property(model_arch, is_mm, init_cuda, is_ce):
+    model_info = ModelRegistry._try_inspect_model_cls(model_arch)
+    assert model_info is not None
+
+    assert model_info.supports_multimodal is is_mm
+    assert model_info.supports_cross_encoding is is_ce
+
+    if init_cuda and current_platform.is_cuda_alike():
+        assert not torch.cuda.is_initialized()
+
+        ModelRegistry._try_load_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,
+            )
+
+
+@create_new_process_for_each_test()
+@pytest.mark.parametrize(
+    "model_arch,is_pp,init_cuda",
+    [
+        # TODO(woosuk): Re-enable this once the MLP Speculator is supported
+        # in V1.
+        # ("MLPSpeculatorPreTrainedModel", False, False),
+        ("DeepseekV2ForCausalLM", True, False),
+        ("Qwen2VLForConditionalGeneration", True, True),
+    ],
+)
+def test_registry_is_pp(model_arch, is_pp, init_cuda):
+    model_info = ModelRegistry._try_inspect_model_cls(model_arch)
+    assert model_info is not None
+
+    assert model_info.supports_pp is is_pp
+
+    if init_cuda and current_platform.is_cuda_alike():
+        assert not torch.cuda.is_initialized()
+
+        ModelRegistry._try_load_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()
+    )
+
+    assert not untested_archs, (
+        "Please add the following architectures to "
+        f"`tests/models/registry.py`: {untested_archs}"
+    )