[SPARK-29093][PYTHON][ML] Remove automatically generated param setter…

…s in _shared_params_code_gen.py

### What changes were proposed in this pull request?
Remove automatically generated param setters in _shared_params_code_gen.py

### Why are the changes needed?
To keep parity between scala and python

### Does this PR introduce any user-facing change?
Yes
Add some setters in Python ML XXXModels

### How was this patch tested?
unit tests

Closes apache#26232 from huaxingao/spark-29093.

Authored-by: Huaxin Gao <[email protected]>
Signed-off-by: zhengruifeng <[email protected]>

mllib/src/main/scala/org/apache/spark/ml/feature/QuantileDiscretizer.scala

@@ -31,7 +31,7 @@ import org.apache.spark.sql.types.StructType
  * Params for [[QuantileDiscretizer]].
  */
 private[feature] trait QuantileDiscretizerBase extends Params
-  with HasHandleInvalid with HasInputCol with HasOutputCol {
+  with HasHandleInvalid with HasInputCol with HasOutputCol with HasInputCols with HasOutputCols {
 
   /**
    * Number of buckets (quantiles, or categories) into which data points are grouped. Must
@@ -129,8 +129,7 @@ private[feature] trait QuantileDiscretizerBase extends Params
  */
 @Since("1.6.0")
 final class QuantileDiscretizer @Since("1.6.0") (@Since("1.6.0") override val uid: String)
-  extends Estimator[Bucketizer] with QuantileDiscretizerBase with DefaultParamsWritable
-    with HasInputCols with HasOutputCols {
+  extends Estimator[Bucketizer] with QuantileDiscretizerBase with DefaultParamsWritable {
 
   @Since("1.6.0")
   def this() = this(Identifiable.randomUID("quantileDiscretizer"))

python/pyspark/ml/base.py

@@ -194,6 +194,18 @@ class UnaryTransformer(HasInputCol, HasOutputCol, Transformer):
     .. versionadded:: 2.3.0
     """
 
+    def setInputCol(self, value):
+        """
+        Sets the value of :py:attr:`inputCol`.
+        """
+        return self._set(inputCol=value)
+
+    def setOutputCol(self, value):
+        """
+        Sets the value of :py:attr:`outputCol`.
+        """
+        return self._set(outputCol=value)
+
     @abstractmethod
     def createTransformFunc(self):
         """