chore: import upstream snapshot with attribution

tests/test_sampling_params.py

@@ -0,0 +1,50 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+from dataclasses import dataclass
+
+import pytest
+
+from vllm import SamplingParams
+
+
+@dataclass
+class MockModelConfig:
+    is_diffusion: bool = False
+    max_logprobs: int = 20
+    logits_processors: list | None = None
+
+    def get_vocab_size(self) -> int:
+        return 1024
+
+
+@pytest.mark.parametrize(
+    "kwargs",
+    [
+        {"temperature": 0.7},
+        {"temperature": 0.0},
+        {"min_p": 0.1},
+        {"seed": 42},
+        {"min_tokens": 5},
+        {"logit_bias": {0: 1.0}},
+        {"bad_words": ["foo"]},
+        {"allowed_token_ids": [0, 1]},
+    ],
+)
+def test_diffusion_rejects_unsupported_params(kwargs: dict):
+    params = SamplingParams(**kwargs)
+    with pytest.raises(ValueError, match="not yet supported with diffusion"):
+        params.verify(MockModelConfig(is_diffusion=True), None, None, None)
+
+
+def test_diffusion_accepts_default_params():
+    SamplingParams().verify(MockModelConfig(is_diffusion=True), None, None, None)
+
+
+def test_diffusion_accepts_top_k_top_p():
+    params = SamplingParams(top_p=0.9, top_k=10)
+    params.verify(MockModelConfig(is_diffusion=True), None, None, None)
+
+
+def test_non_diffusion_models_unaffected():
+    params = SamplingParams(temperature=0.7, top_k=10, seed=42)
+    params.verify(MockModelConfig(), None, None, None)