address feedback:I

docs/spec.md

@@ -6691,18 +6691,18 @@ of the expressed type into corresponding integer values of the storage type
 using the zero point and scale associated with the quantized element type.
 
 ```python
-def quantize(x: Value, type: Type) -> Value:
-  assert is_float(x) and is_quantized(type)
-  zero_points = compute_zero_points(type, type(shape(x), storage_type(type)))
-  converted_zero_points = convert(zero_points, expressed_type(type))
-  converted_min = convert(storage_min(type), expressed_type(type))
-  converted_max = convert(storage_max(type), expressed_type(type))
-
-  x_scaled = x / compute_scales(type, type(x))
+def quantize(x: Value, result_type: Type) -> Value:
+  assert is_float(x) and is_quantized(result_type)
+  zero_points = compute_zero_points(result_type, TensorType(shape(x), storage_type(result_type)))
+  converted_zero_points = convert(zero_points, expressed_type(result_type))
+  converted_min = convert(storage_min(result_type), expressed_type(result_type))
+  converted_max = convert(storage_max(result_type), expressed_type(result_type))
+
+  x_scaled = x / compute_scales(result_type, type(x))
   x_scaled_add_zp = x_scaled + converted_zero_points
   x_clamped = clamp(converted_min, x_scaled_add_zp, converted_max)
   x_rounded = round_nearest_even(x_clamped)
-  return convert(x_rounded, type)
+  return convert(x_rounded, result_type)
 ```
 
 * `dequantize_op_quantize` is used to specify element-wise computations on