Add LogisticRegressionOperator with API training support and integration test

python/src/pywy/basic/model/models.py

@@ -27,3 +27,10 @@ def __init__(self, out: Op):
 
     def get_out(self):
         return self.out
+
+class LogisticRegression(Op):
+    def __init__(self, name=None):
+        super().__init__(Op.DType.FLOAT32, name)
+
+    def inputs_required(self):
+        return 2

python/src/pywy/basic/model/ops.py

@@ -221,13 +221,6 @@ def get_dType(self):
     def inputs_required(self):
         return 1
 
-class LogisticRegression(Op):
-    def __init__(self, name=None):
-        super().__init__(Op.DType.FLOAT32, name)
-
-    def inputs_required(self):
-        return 2  # features + labels
-
 
 class Softmax(Op):
     def __init__(self, name=None):

python/src/pywy/dataquanta.py

@@ -23,8 +23,8 @@
 from pywy.operators import *
 from pywy.basic.data.record import Record
 from pywy.basic.model.option import Option
-from pywy.basic.model.models import Model
-from pywy.basic.model.ops import LogisticRegression
+from pywy.basic.model.models import (Model, LogisticRegression)
+
 
 
 class Configuration:
@@ -200,8 +200,6 @@ def train_logistic_regression(
             labels: "DataQuanta[In]",
             fit_intercept: bool = True
     ) -> "DataQuanta[Out]":
-        from pywy.basic.model.ops import LogisticRegression
-
         op = LogisticRegression()
         self._connect(op, 0)
         labels._connect(op, 1)

wayang-api/wayang-api-scala-java/src/main/scala/org/apache/wayang/api/DataQuanta.scala

@@ -110,7 +110,7 @@ class DataQuanta[Out: ClassTag](val operator: ElementaryOperator, outputIndex: I
     val operator = new LogisticRegressionOperator(fitIntercept)
     this.connectTo(operator, 0)
     labels.connectTo(operator, 1)
-    new DataQuanta[LogisticRegressionModel](operator)
+    operator
   }