import warnings

import pytest
import torch.cuda

from vllm.model_executor.models import ModelRegistry
from vllm.platforms import current_platform

from ..utils import fork_new_process_for_each_test


@pytest.mark.parametrize("model_arch", ModelRegistry.get_supported_archs())
def test_registry_imports(model_arch):
    # Ensure all model classes can be imported successfully
    ModelRegistry.resolve_model_cls(model_arch)


@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)