[mlir][python][quant] Fixed functions without return value and incorrect type hins.

Author: 牛奕博

mlir/lib/Bindings/Python/DialectQuant.cpp

@@ -250,6 +250,7 @@ static void populateDialectQuantSubmodule(const py::module &m) {
           double scale = mlirUniformQuantizedPerAxisTypeGetScale(type, i);
           scales.push_back(scale);
         }
+        return scales;
       },
       "The scales designate the difference between the real values "
       "corresponding to consecutive quantized values differing by 1. The ith "
@@ -265,6 +266,7 @@ static void populateDialectQuantSubmodule(const py::module &m) {
               mlirUniformQuantizedPerAxisTypeGetZeroPoint(type, i);
           zeroPoints.push_back(zeroPoint);
         }
+        return zeroPoints;
       },
       "the storage values corresponding to the real value 0 in the affine "
       "equation. The ith zero point corresponds to the ith slice in the "

mlir/python/mlir/_mlir_libs/_mlir/dialects/quant.pyi

@@ -101,7 +101,7 @@ class UniformQuantizedPerAxisType(QuantizedType):
   def scales(self) -> list[float]: ...
 
   @property
-  def zero_points(self) -> list[float]: ...
+  def zero_points(self) -> list[int]: ...
 
   @property
   def quantized_dimension(self) -> int: ...

mlir/test/python/dialects/quant.py

@@ -108,9 +108,9 @@ def test_uniform_per_axis_type():
             ),
         )
 
-        # CHECK: scales: None
+        # CHECK: scales: [200.0, 0.99872]
         print(f"scales: {per_axis.scales}")
-        # CHECK: zero_points: None
+        # CHECK: zero_points: [0, 120]
         print(f"zero_points: {per_axis.zero_points}")
         # CHECK: quantized dim: 1
         print(f"quantized dim: {per_axis.quantized_dimension}")