Fix compilation error and formatting

Author: maziyarpanahi

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

@@ -22,11 +22,11 @@ import com.johnsnowlabs.ml.onnx.{OnnxSession, OnnxWrapper}
 import com.johnsnowlabs.ml.openvino.OpenvinoWrapper
 import com.johnsnowlabs.ml.tensorflow.sign.{ModelSignatureConstants, ModelSignatureManager}
 import com.johnsnowlabs.ml.tensorflow.{TensorResources, TensorflowWrapper}
-import com.johnsnowlabs.ml.util.{ModelArch, ONNX, Openvino, TensorFlow}
+import com.johnsnowlabs.ml.util._
 import com.johnsnowlabs.nlp.annotators.common._
 import com.johnsnowlabs.nlp.{Annotation, AnnotatorType}
-import org.slf4j.{Logger, LoggerFactory}
 import org.intel.openvino.Tensor
+import org.slf4j.{Logger, LoggerFactory}
 
 import scala.collection.JavaConverters._
 
@@ -233,9 +233,7 @@ private[johnsnowlabs] class Bert(
           .map(sentence => sentence.map(x => if (x == 0) 0L else 1L))
           .toArray
         val maskTensors =
-          OnnxTensor.createTensor(
-            env,
-            attentionMask)
+          OnnxTensor.createTensor(env, attentionMask)
 
         val segmentTensors =
           OnnxTensor.createTensor(env, batch.map(x => Array.fill(maxSentenceLength)(0L)).toArray)

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

@@ -23,7 +23,7 @@ import com.johnsnowlabs.ml.openvino.OpenvinoWrapper
 import com.johnsnowlabs.ml.tensorflow.sentencepiece.{SentencePieceWrapper, SentencepieceEncoder}
 import com.johnsnowlabs.ml.tensorflow.sign.{ModelSignatureConstants, ModelSignatureManager}
 import com.johnsnowlabs.ml.tensorflow.{TensorResources, TensorflowWrapper}
-import com.johnsnowlabs.ml.util.{ModelArch, ONNX, Openvino, TensorFlow}
+import com.johnsnowlabs.ml.util._
 import com.johnsnowlabs.nlp.annotators.common._
 import com.johnsnowlabs.nlp.{Annotation, AnnotatorType}
 import org.slf4j.{Logger, LoggerFactory}
@@ -243,10 +243,7 @@ private[johnsnowlabs] class XlmRoberta(
         val tokenTensors =
           OnnxTensor.createTensor(env, batch.map(x => x.map(x => x.toLong)).toArray)
         val maskTensors =
-          OnnxTensor.createTensor(
-            env,
-            attentionMask
-            )
+          OnnxTensor.createTensor(env, attentionMask)
 
         val inputs =
           Map("input_ids" -> tokenTensors, "attention_mask" -> maskTensors).asJava

src/main/scala/com/johnsnowlabs/nlp/annotators/classifier/dl/MPNetForTokenClassification.scala

@@ -373,7 +373,8 @@ trait ReadMPNetForTokenDLModel extends ReadOnnxModel {
       case TensorFlow.name =>
         throw new NotImplementedError("Tensorflow models are not supported.")
       case ONNX.name =>
-        val onnxWrapper = OnnxWrapper.read(spark, localModelPath, zipped = false, useBundle = true)
+        val onnxWrapper =
+          OnnxWrapper.read(spark, localModelPath, zipped = false, useBundle = true)
         annotatorModel
           .setModelIfNotSet(spark, Some(onnxWrapper))
       case _ =>

src/test/scala/com/johnsnowlabs/nlp/annotators/classifier/dl/MPNetForTokenClassificationTestSpec.scala

@@ -14,7 +14,6 @@
  * limitations under the License.
  */
 
-
 package com.johnsnowlabs.nlp.annotators.classifier.dl
 
 import com.johnsnowlabs.nlp.annotators.Tokenizer

src/test/scala/com/johnsnowlabs/nlp/annotators/classifier/dl/XlmRoBertaForQuestionAnsweringTestSpec.scala

@@ -116,7 +116,6 @@ class XlmRoBertaForQuestionAnsweringTestSpec extends AnyFlatSpec {
     val loadedPipelineModel = PipelineModel.load("./tmp_xlmrobertaforquestion_pipeline")
     loadedPipelineModel.transform(ddd).select("label.result").show(false)
 
-
   }
 
   "XlmRoBertaForQuestionAnswering" should "benchmark test" taggedAs SlowTest in {

src/test/scala/com/johnsnowlabs/nlp/annotators/classifier/dl/XlmRoBertaForTokenClassificationTestSpec.scala

@@ -75,7 +75,6 @@ class XlmRoBertaForTokenClassificationTestSpec extends AnyFlatSpec {
 
   }
 
-
   "XlmRoBertaForTokenClassification" should "be saved and loaded correctly" taggedAs SlowTest in {
 
     import ResourceHelper.spark.implicits._