nswamy closed pull request #11250: [MXNET-531] MNIST Examples for Scala new API
URL: https://github.com/apache/incubator-mxnet/pull/11250
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diff --git
a/scala-package/examples/src/main/scala/org/apache/mxnetexamples/imclassification/ModelTrain.scala
b/scala-package/examples/src/main/scala/org/apache/mxnetexamples/imclassification/ModelTrain.scala
index ab86314a42a..1a77775b985 100644
---
a/scala-package/examples/src/main/scala/org/apache/mxnetexamples/imclassification/ModelTrain.scala
+++
b/scala-package/examples/src/main/scala/org/apache/mxnetexamples/imclassification/ModelTrain.scala
@@ -30,7 +30,7 @@ object ModelTrain {
network: Symbol, dataLoader: (String, Int, KVStore) => (DataIter,
DataIter),
kvStore: String, numEpochs: Int, modelPrefix: String = null,
loadEpoch: Int = -1,
lr: Float = 0.1f, lrFactor: Float = 1f, lrFactorEpoch: Float = 1f,
- clipGradient: Float = 0f, monitorSize: Int = -1): Unit = {
+ clipGradient: Float = 0f, monitorSize: Int = -1): Accuracy = {
// kvstore
var kv = KVStore.create(kvStore)
@@ -96,15 +96,17 @@ object ModelTrain {
if (monitorSize > 0) {
model.setMonitor(new Monitor(monitorSize))
}
+ val acc = new Accuracy()
model.fit(trainData = train,
evalData = validation,
- evalMetric = new Accuracy(),
+ evalMetric = acc,
kvStore = kv,
batchEndCallback = new Speedometer(batchSize, 50),
epochEndCallback = checkpoint)
if (kv != null) {
kv.dispose()
}
+ acc
}
// scalastyle:on parameterNum
}
diff --git
a/scala-package/examples/src/main/scala/org/apache/mxnetexamples/imclassification/README.md
b/scala-package/examples/src/main/scala/org/apache/mxnetexamples/imclassification/README.md
new file mode 100644
index 00000000000..5141f441b1e
--- /dev/null
+++
b/scala-package/examples/src/main/scala/org/apache/mxnetexamples/imclassification/README.md
@@ -0,0 +1,17 @@
+# MNIST Example for Scala
+This is the MNIST Training Example implemented for Scala type-safe api
+## Setup
+### Download the source File
+```$xslt
+https://s3.us-east-2.amazonaws.com/mxnet-scala/scala-example-ci/mnist/mnist.zip
+```
+### Unzip the file
+```$xslt
+unzip mnist.zip
+```
+### Arguement Configuration
+Then you need to define the arguments that you would like to pass in the model:
+```$xslt
+--data-dir <location of your downloaded file>
+```
+You can find more information
[here](https://github.com/apache/incubator-mxnet/blob/scala-package/examples/src/main/scala/org/apache/mxnet/examples/imclassification/TrainMnist.scala#L169-L207)
\ No newline at end of file
diff --git
a/scala-package/examples/src/main/scala/org/apache/mxnetexamples/imclassification/TrainMnist.scala
b/scala-package/examples/src/main/scala/org/apache/mxnetexamples/imclassification/TrainMnist.scala
index e9171bd47c2..b0ecc7d29cc 100644
---
a/scala-package/examples/src/main/scala/org/apache/mxnetexamples/imclassification/TrainMnist.scala
+++
b/scala-package/examples/src/main/scala/org/apache/mxnetexamples/imclassification/TrainMnist.scala
@@ -21,8 +21,8 @@ import org.apache.mxnet._
import org.kohsuke.args4j.{CmdLineParser, Option}
import org.slf4j.LoggerFactory
-import scala.collection.mutable
import scala.collection.JavaConverters._
+import scala.collection.mutable
object TrainMnist {
private val logger = LoggerFactory.getLogger(classOf[TrainMnist])
@@ -31,6 +31,7 @@ object TrainMnist {
def getMlp: Symbol = {
val data = Symbol.Variable("data")
+ // val fc1 = Symbol.FullyConnected(name = "relu")()(Map("data" -> data,
"act_type" -> "relu"))
val fc1 = Symbol.api.FullyConnected(data = Some(data), num_hidden = 128,
name = "fc1")
val act1 = Symbol.api.Activation (data = Some(fc1), "relu", name = "relu")
val fc2 = Symbol.api.FullyConnected(Some(act1), None, None, 64, name =
"fc2")
@@ -40,10 +41,6 @@ object TrainMnist {
mlp
}
- // LeCun, Yann, Leon Bottou, Yoshua Bengio, and Patrick
- // Haffner. "Gradient-based learning applied to document recognition."
- // Proceedings of the IEEE (1998)
-
def getLenet: Symbol = {
val data = Symbol.Variable("data")
// first conv
@@ -95,6 +92,19 @@ object TrainMnist {
(train, eval)
}
+ def test(dataPath : String) : Float = {
+ val (dataShape, net) = (Shape(784), getMlp)
+ val devs = Array(Context.cpu(0))
+ val envs: mutable.Map[String, String] = mutable.HashMap.empty[String,
String]
+ val Acc = ModelTrain.fit(dataDir = dataPath,
+ batchSize = 128, numExamples = 60000, devs = devs,
+ network = net, dataLoader = getIterator(dataShape),
+ kvStore = "local", numEpochs = 10)
+ logger.info("Finish test fit ...")
+ val (_, num) = Acc.get
+ num(0)
+ }
+
def main(args: Array[String]): Unit = {
val inst = new TrainMnist
diff --git
a/scala-package/examples/src/test/scala/org/apache/mxnetexamples/imclassification/MNISTExampleSuite.scala
b/scala-package/examples/src/test/scala/org/apache/mxnetexamples/imclassification/MNISTExampleSuite.scala
new file mode 100644
index 00000000000..0e3b7ec8f34
--- /dev/null
+++
b/scala-package/examples/src/test/scala/org/apache/mxnetexamples/imclassification/MNISTExampleSuite.scala
@@ -0,0 +1,66 @@
+/*
+ * 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 org.apache.mxnetexamples.imclassification
+
+import java.io.File
+import java.net.URL
+
+import org.apache.commons.io.FileUtils
+import org.apache.mxnet.Context
+import org.scalatest.{BeforeAndAfterAll, FunSuite}
+import org.slf4j.LoggerFactory
+
+import scala.sys.process.Process
+
+/**
+ * Integration test for imageClassifier example.
+ * This will run as a part of "make scalatest"
+ */
+class MNISTExampleSuite extends FunSuite with BeforeAndAfterAll {
+ private val logger = LoggerFactory.getLogger(classOf[MNISTExampleSuite])
+
+ test("Example CI: Test MNIST Training") {
+ // This test is CPU only
+ if (System.getenv().containsKey("SCALA_TEST_ON_GPU") &&
+ System.getenv("SCALA_TEST_ON_GPU").toInt == 1) {
+ logger.info("CPU test only, skipped...")
+ } else {
+ logger.info("Downloading mnist model")
+ val baseUrl =
"https://s3.us-east-2.amazonaws.com/mxnet-scala/scala-example-ci";
+ val tempDirPath = System.getProperty("java.io.tmpdir")
+ val modelDirPath = tempDirPath + File.separator + "mnist/"
+ logger.info("tempDirPath: %s".format(tempDirPath))
+ val tmpFile = new File(tempDirPath + "/mnist/mnist.zip")
+ if (!tmpFile.exists()) {
+ FileUtils.copyURLToFile(new URL(baseUrl + "/mnist/mnist.zip"),
+ tmpFile)
+ }
+ // TODO: Need to confirm with Windows
+ Process("unzip " + tempDirPath + "/mnist/mnist.zip -d "
+ + tempDirPath + "/mnist/") !
+
+ var context = Context.cpu()
+
+ val output = TrainMnist.test(modelDirPath)
+ Process("rm -rf " + modelDirPath) !
+
+ assert(output >= 0.95f)
+ }
+
+ }
+}
diff --git
a/scala-package/examples/src/test/scala/org/apache/mxnetexamples/infer/imageclassifier/ImageClassifierExampleSuite.scala
b/scala-package/examples/src/test/scala/org/apache/mxnetexamples/infer/imageclassifier/ImageClassifierExampleSuite.scala
index 63196ed8172..a08e1576ff3 100644
---
a/scala-package/examples/src/test/scala/org/apache/mxnetexamples/infer/imageclassifier/ImageClassifierExampleSuite.scala
+++
b/scala-package/examples/src/test/scala/org/apache/mxnetexamples/infer/imageclassifier/ImageClassifierExampleSuite.scala
@@ -65,14 +65,13 @@ class ImageClassifierExampleSuite extends FunSuite with
BeforeAndAfterAll {
val output = ImageClassifierExample.runInferenceOnSingleImage(modelDirPath
+ "resnet-18",
inputImagePath, context)
- assert(output(0).toList.head._1 === "n02110958 pug, pug-dog")
-
val outputList =
ImageClassifierExample.runInferenceOnBatchOfImage(modelDirPath + "resnet-18",
inputImageDir, context)
- assert(outputList(0).toList.head._1 === "n02110958 pug, pug-dog")
-
Process("rm -rf " + modelDirPath + " " + inputImageDir) !
+ assert(output(0).toList.head._1 === "n02110958 pug, pug-dog")
+ assert(outputList(0).toList.head._1 === "n02110958 pug, pug-dog")
+
}
}
diff --git
a/scala-package/examples/src/test/scala/org/apache/mxnetexamples/infer/objectdetector/ObjectDetectorExampleSuite.scala
b/scala-package/examples/src/test/scala/org/apache/mxnetexamples/infer/objectdetector/ObjectDetectorExampleSuite.scala
index 9725eebb645..ed63116e7cf 100644
---
a/scala-package/examples/src/test/scala/org/apache/mxnetexamples/infer/objectdetector/ObjectDetectorExampleSuite.scala
+++
b/scala-package/examples/src/test/scala/org/apache/mxnetexamples/infer/objectdetector/ObjectDetectorExampleSuite.scala
@@ -68,14 +68,14 @@ class ObjectDetectorExampleSuite extends FunSuite with
BeforeAndAfterAll {
val output = SSDClassifierExample.runObjectDetectionSingle(modelDirPath +
"resnet50_ssd_model",
inputImagePath, context)
- assert(output(0)(0)._1 === "car")
-
val outputList = SSDClassifierExample.runObjectDetectionBatch(
modelDirPath + "resnet50_ssd_model",
inputImageDir, context)
+ Process("rm -rf " + modelDirPath + " " + inputImageDir) !
+
+ assert(output(0)(0)._1 === "car")
assert(output(0)(0)._1 === "car")
- Process("rm -rf " + modelDirPath + " " + inputImageDir) !
}
}
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