fix dlframe (intel-analytics#3133)

spark/dl/src/main/scala/com/intel/analytics/bigdl/dlframes/DLClassifier.scala

@@ -0,0 +1,94 @@
+/*
+ * Copyright 2016 The BigDL Authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package com.intel.analytics.bigdl.dlframes
+
+import com.intel.analytics.bigdl.tensor.Tensor
+import com.intel.analytics.bigdl.tensor.TensorNumericMath.TensorNumeric
+import com.intel.analytics.bigdl.{Criterion, Module}
+import org.apache.spark.ml.adapter.SchemaUtils
+import org.apache.spark.ml.param.ParamMap
+import org.apache.spark.ml.util.Identifiable
+import org.apache.spark.sql.types._
+
+import scala.reflect.ClassTag
+
+/**
+ * [[DLClassifier]] is a specialized [[DLEstimator]] that simplifies the data format for
+ * classification tasks. It only supports label column of DoubleType.
+ * and the fitted [[DLClassifierModel]] will have the prediction column of DoubleType.
+ *
+ * @param model BigDL module to be optimized
+ * @param criterion  BigDL criterion method
+ * @param featureSize The size (Tensor dimensions) of the feature data.
+ */
+@deprecated("`DLClassifier` is deprecated." +
+  "com.intel.analytics.bigdl.dlframes is deprecated in BigDL 0.11, " +
+  "and will be removed in future releases", "0.10.0")
+class DLClassifier[T: ClassTag](
+    @transient override val model: Module[T],
+    override val criterion : Criterion[T],
+    override val featureSize : Array[Int],
+    override val uid: String = Identifiable.randomUID("dlClassifier")
+  )(implicit ev: TensorNumeric[T])
+  extends DLEstimator[T](model, criterion, featureSize, Array(1)) {
+
+  override protected def wrapBigDLModel(
+      m: Module[T], featureSize: Array[Int]): DLClassifierModel[T] = {
+    val dlModel = new DLClassifierModel[T](m, featureSize)
+    copyValues(dlModel.setParent(this)).asInstanceOf[DLClassifierModel[T]]
+  }
+
+  override def transformSchema(schema : StructType): StructType = {
+    validateParams(schema)
+    SchemaUtils.appendColumn(schema, $(predictionCol), DoubleType)
+  }
+
+  override def copy(extra: ParamMap): DLClassifier[T] = {
+    copyValues(new DLClassifier(model, criterion, featureSize), extra)
+  }
+}
+
+/**
+ * [[DLClassifierModel]] is a specialized [[DLModel]] for classification tasks.
+ * The prediction column will have the datatype of Double.
+ *
+ * @param model BigDL module to be optimized
+ * @param featureSize The size (Tensor dimensions) of the feature data.
+ */
+@deprecated("`DLClassifierModel` is deprecated." +
+  "com.intel.analytics.bigdl.dlframes is deprecated in BigDL 0.11, " +
+  "and will be removed in future releases", "0.10.0")
+class DLClassifierModel[T: ClassTag](
+    @transient override val model: Module[T],
+    featureSize : Array[Int],
+    override val uid: String = "DLClassifierModel"
+  )(implicit ev: TensorNumeric[T]) extends DLModel[T](model, featureSize) {
+
+  protected override def outputToPrediction(output: Tensor[T]): Any = {
+    if (output.size().deep == Array(1).deep) {
+      val raw = ev.toType[Double](output.toArray().head)
+      if (raw > 0.5) 1.0 else 0.0
+    } else {
+      ev.toType[Double](output.max(1)._2.valueAt(1))
+    }
+  }
+
+  override def transformSchema(schema : StructType): StructType = {
+    validateDataType(schema, $(featuresCol))
+    SchemaUtils.appendColumn(schema, $(predictionCol), DoubleType)
+  }
+}
+