[Misc] Disambiguate quantized types via a new ScalarType (#6396)

tests/test_scalartype.py

@@ -0,0 +1,36 @@
+import pytest
+import torch
+
+from vllm.scalar_type import scalar_types
+
+
+@pytest.mark.parametrize("type_tuple", (
+    (-8, 7, scalar_types.int4),
+    (0, 15, scalar_types.uint4),
+    (-8, 7, scalar_types.uint4b8),
+    (-128, 127, scalar_types.uint8b128),
+    (-28., 28., scalar_types.float6_e3m2f),
+    (torch.int8, scalar_types.int8),
+    (torch.uint8, scalar_types.uint8),
+    (torch.float8_e5m2, scalar_types.float8_e5m2),
+    (torch.float8_e4m3fn, scalar_types.float8_e4m3fn),
+    (torch.bfloat16, scalar_types.float16_e8m7),
+    (torch.float16, scalar_types.float16_e5m10),
+),
+                         ids=lambda x: str(x))
+def test_scalar_type_min_max(type_tuple):
+    print(type_tuple)
+    if len(type_tuple) == 3:
+        min, max, t = type_tuple
+    else:
+        torch_type, t = type_tuple
+        if torch_type.is_floating_point:
+            min = torch.finfo(torch_type).min
+            max = torch.finfo(torch_type).max
+        else:
+            min = torch.iinfo(torch_type).min
+            max = torch.iinfo(torch_type).max
+
+    print(t, min, max, t.min(), t.max())
+    assert min == t.min()
+    assert max == t.max()