Merge d42acdde324375a4c460a30423251c54b4b2336d into 553741557a57df44a46fb3ab72b6aafeaf945337

deepinfer/sampling_params.py

@@ -86,9 +86,11 @@ class SamplingParams:
     def _make_seed(seed: int | None) -> int:
         if seed is None:
             return random.getrandbits(64)
-        if isinstance(seed, int):
-            return seed & 0xFFFF_FFFF_FFFF_FFFF
-        raise TypeError()
+        if not isinstance(seed, int):
+            raise TypeError(f"seq_seed must be an int or None, got {type(seed).__name__}.")
+        if seed < 0:
+            raise ValueError(f"seq_seed must be in range of uint64, got {seed}.")
+        return seed & 0xFFFF_FFFF_FFFF_FFFF
 
     def _verify_args(self) -> None:
         if self.temperature < 0.0:

tests/engine/test_sampling_params.py

@@ -0,0 +1,36 @@
+"""Unit tests for SamplingParams seq_seed handling."""
+
+import pytest
+import torch  # noqa: F401  Load torch's shared libraries before deepinfer.
+
+from deepinfer.sampling_params import SamplingParams
+
+pytestmark = [pytest.mark.ci, pytest.mark.ci_npu]
+
+
+def test_seq_seed_none_is_random_uint64() -> None:
+    params = SamplingParams()
+    assert 0 <= params.seq_seed < 2**64
+
+
+def test_seq_seed_valid_is_preserved() -> None:
+    assert SamplingParams(seq_seed=42).seq_seed == 42
+    assert SamplingParams(seq_seed=2**64 - 1).seq_seed == 2**64 - 1
+
+
+def test_seq_seed_wraps_to_uint64() -> None:
+    assert SamplingParams(seq_seed=2**64 + 5).seq_seed == 5
+
+
+def test_seq_seed_negative_raises() -> None:
+    with pytest.raises(ValueError, match="seq_seed"):
+        SamplingParams(seq_seed=-1)
+    with pytest.raises(ValueError, match="seq_seed"):
+        SamplingParams(seq_seed=-(2**64) + 5)
+
+
+def test_seq_seed_wrong_type_raises() -> None:
+    with pytest.raises(TypeError, match="seq_seed"):
+        SamplingParams(seq_seed="42")  # type: ignore[arg-type]
+    with pytest.raises(TypeError, match="seq_seed"):
+        SamplingParams(seq_seed=1.5)  # type: ignore[arg-type]