nswamy commented on a change in pull request #9678: [MXNET-50] Scala Inference 
APIs
URL: https://github.com/apache/incubator-mxnet/pull/9678#discussion_r174247041
 
 

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 File path: 
scala-package/infer/src/main/scala/ml/dmlc/mxnet/infer/Classifier.scala
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 @@ -0,0 +1,167 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You 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 ml.dmlc.mxnet.infer
+
+import ml.dmlc.mxnet.{DataDesc, NDArray}
+import java.io.File
+
+import org.slf4j.LoggerFactory
+
+import scala.io
+import scala.collection.mutable.ListBuffer
+
+trait ClassifierBase {
+
+  /**
+    * Takes an Array of Floats and returns corresponding labels, score tuples.
+    * @param input: IndexedSequence one-dimensional array of Floats.
+    * @param topK: (Optional) How many top_k(sorting will be based on the last 
axis)
+    *             elements to return, if not passed returns unsorted output.
+    * @return IndexedSequence of (Label, Score) tuples.
+    */
+  def classify(input: IndexedSeq[Array[Float]],
+               topK: Option[Int] = None): List[(String, Float)]
+
+  /**
+    * Takes a Sequence of NDArrays and returns Label, Score tuples.
+    * @param input: Indexed Sequence of NDArrays
+    * @param topK: (Optional) How many top_k(sorting will be based on the last 
axis)
+    *             elements to return, if not passed returns unsorted output.
+    * @return Traversable Sequence of (Label, Score) tuple, Score will be in 
the form of NDArray
+    */
+  def classifyWithNDArray(input: IndexedSeq[NDArray],
+                          topK: Option[Int] = None): IndexedSeq[List[(String, 
Float)]]
+}
+
+/**
+  * A class for classifier tasks
+  * @param modelPathPrefix PathPrefix from where to load the symbol, 
parameters and synset.txt
+  *                        Example: file://model-dir/resnet-152(containing 
resnet-152-symbol.json
+  *                        file://model-dir/synset.txt
+  * @param inputDescriptors Descriptors defining the input node names, shape,
+  *                         layout and Type parameters
+  */
+class Classifier(modelPathPrefix: String, protected val inputDescriptors: 
IndexedSeq[DataDesc])
+  extends ClassifierBase {
+
+  private val logger = LoggerFactory.getLogger(classOf[Classifier])
+
+  val predictor: PredictBase = getPredictor(modelPathPrefix, inputDescriptors)
+
+  val synsetFilePath = getSynsetFilePath(modelPathPrefix)
+
+  val synset = readSynsetFile(synsetFilePath)
 
 Review comment:
   Classifier is just taking the predictor and using Synset to map the labels, 
this is the only difference between the predictor/classifier

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