[SPARKNLP-994] Solves ZeroShotNerClassification Issue

docs/_posts/maziyarpanahi/2023-02-08-zero_shot_ner_roberta_en.md

@@ -101,15 +101,15 @@ val ner_converter = new NerConverter()
     .setInputCols(Array("sentence", "token", "zero_shot_ner"))
     .setOutputCol("ner_chunk")
 
-val pipeline = new .setStages(Array(
+val pipeline = new Pipeline().setStages(Array(
     documentAssembler, 
     sentenceDetector, 
     tokenizer, 
     zero_shot_ner, 
     ner_converter))
 
-val data = Seq(Array("Hellen works in London, Paris and Berlin. My name is Clara, I live in New York and Hellen lives in Paris.",
-                                     "John is a man who works in London, London and London.")toDS().toDF("text")
+val data = Seq("Hellen works in London, Paris and Berlin. My name is Clara, I live in New York and Hellen lives in Paris.",
+      "John is a man who works in London, London and London.").toDS.toDF("text")
 
 val result = pipeline.fit(data).transform(data)
 ```

src/main/scala/com/johnsnowlabs/ml/ai/RoBertaClassification.scala

@@ -352,11 +352,11 @@ private[johnsnowlabs] class RoBertaClassification(
 
     val endDim = endLogits.length / batchLength
     val endScores: Array[Array[Float]] =
-      endLogits.grouped(endDim).toArray
+      endLogits.grouped(endDim).map(scores => calculateSoftmax(scores)).toArray
 
     val startDim = startLogits.length / batchLength
     val startScores: Array[Array[Float]] =
-      startLogits.grouped(startDim).toArray
+      startLogits.grouped(startDim).map(scores => calculateSoftmax(scores)).toArray
 
     (startScores, endScores)
   }

src/main/scala/com/johnsnowlabs/ml/ai/ZeroShotNerClassification.scala

@@ -88,7 +88,7 @@ private[johnsnowlabs] class ZeroShotNerClassification(
 
     val allTokenPieces =
       wordPieceTokenizedQuestion.head.tokens ++ wordPieceTokenizedContext.flatMap(x => x.tokens)
-    val decodedAnswer = allTokenPieces.slice(startIndex._2 - 2, endIndex._2 - 1)
+    val decodedAnswer = allTokenPieces.slice(startIndex._2 - 3, endIndex._2 - 2)
     // Check if the answer span starts at the CLS symbol 0 - if so return empty string
     val content =
       if (startIndex._2 > 0)
@@ -141,4 +141,5 @@ private[johnsnowlabs] class ZeroShotNerClassification(
     }
 
   }
+
 }

src/main/scala/com/johnsnowlabs/nlp/annotators/ner/dl/ZeroShotNerModel.scala

@@ -17,8 +17,10 @@
 package com.johnsnowlabs.nlp.annotators.ner.dl
 
 import com.johnsnowlabs.ml.ai.{RoBertaClassification, ZeroShotNerClassification}
-import com.johnsnowlabs.ml.onnx.OnnxWrapper
+import com.johnsnowlabs.ml.onnx.{OnnxWrapper, ReadOnnxModel}
 import com.johnsnowlabs.ml.tensorflow.{ReadTensorflowModel, TensorflowWrapper}
+import com.johnsnowlabs.ml.util.LoadExternalModel.notSupportedEngineError
+import com.johnsnowlabs.ml.util.{ONNX, TensorFlow}
 import com.johnsnowlabs.nlp.AnnotatorType.{DOCUMENT, NAMED_ENTITY, TOKEN}
 import com.johnsnowlabs.nlp.annotator.RoBertaForQuestionAnswering
 import com.johnsnowlabs.nlp.pretrained.ResourceDownloader
@@ -448,19 +450,34 @@ trait ReadablePretrainedZeroShotNer
   }
 }
 
-trait ReadZeroShotNerDLModel extends ReadTensorflowModel {
+trait ReadZeroShotNerDLModel extends ReadTensorflowModel with ReadOnnxModel {
   this: ParamsAndFeaturesReadable[ZeroShotNerModel] =>
 
   override val tfFile: String = "roberta_classification_tensorflow"
+  override val onnxFile: String = "roberta_classification_onnx"
 
-  def readTensorflow(instance: ZeroShotNerModel, path: String, spark: SparkSession): Unit = {
-
-    val tfWrapper =
-      readTensorflowModel(path, spark, "_roberta_classification_tf", initAllTables = false)
-    instance.setModelIfNotSet(spark, Some(tfWrapper), None)
+  def readModel(instance: ZeroShotNerModel, path: String, spark: SparkSession): Unit = {
+    instance.getEngine match {
+      case TensorFlow.name => {
+        val tfWrapper = readTensorflowModel(path, spark, "_roberta_classification_tf", initAllTables = false)
+        instance.setModelIfNotSet(spark, Some(tfWrapper), None)
+      }
+      case ONNX.name => {
+        val onnxWrapper = readOnnxModel(
+          path,
+          spark,
+          "_roberta_classification_onnx",
+          zipped = true,
+          useBundle = false,
+          None)
+        instance.setModelIfNotSet(spark, None, Some(onnxWrapper))
+      }
+      case _ =>
+        throw new Exception(notSupportedEngineError)
+    }
   }
 
-  addReader(readTensorflow)
+  addReader(readModel)
 }
 object ZeroShotNerModel extends ReadablePretrainedZeroShotNer with ReadZeroShotNerDLModel {
 
@@ -487,7 +504,12 @@ object ZeroShotNerModel extends ReadablePretrainedZeroShotNer with ReadZeroShotN
       newModel.setSignatures(
         model.signatures.get.getOrElse(throw new RuntimeException("Signatures not set")))
 
-    newModel.setModelIfNotSet(spark, model.getModelIfNotSet.tensorflowWrapper, None)
+    model.getEngine match {
+      case TensorFlow.name =>
+        newModel.setModelIfNotSet(spark, model.getModelIfNotSet.tensorflowWrapper, None)
+      case ONNX.name =>
+        newModel.setModelIfNotSet(spark, None, model.getModelIfNotSet.onnxWrapper)
+    }
 
     model
       .extractParamMap()