You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2018/09/20 15:27:56 UTC
[GitHub] nswamy closed pull request #12570: review require() usages to add
meaningful messages.
nswamy closed pull request #12570: review require() usages to add meaningful messages.
URL: https://github.com/apache/incubator-mxnet/pull/12570
This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the sake of provenance:
As this is a foreign pull request (from a fork), the diff is supplied
below (as it won't show otherwise due to GitHub magic):
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/EvalMetric.scala b/scala-package/core/src/main/scala/org/apache/mxnet/EvalMetric.scala
index de2881a221c..aedf7c8327c 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/EvalMetric.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/EvalMetric.scala
@@ -133,17 +133,20 @@ class TopKAccuracy(topK: Int) extends EvalMetric("top_k_accuracy") {
override def update(labels: IndexedSeq[NDArray], preds: IndexedSeq[NDArray]): Unit = {
require(labels.length == preds.length,
- "labels and predictions should have the same length.")
+ s"labels and predictions should have the same length " +
+ s"(got ${labels.length} and ${preds.length}).")
for ((pred, label) <- preds zip labels) {
val predShape = pred.shape
val dims = predShape.length
- require(dims <= 2, "Predictions should be no more than 2 dims.")
+ require(dims <= 2, s"Predictions should be no more than 2 dims (got $predShape).")
val labelArray = label.toArray
val numSamples = predShape(0)
if (dims == 1) {
val predArray = pred.toArray.zipWithIndex.sortBy(_._1).reverse.map(_._2)
- require(predArray.length == labelArray.length)
+ require(predArray.length == labelArray.length,
+ s"Each label and prediction array should have the same length " +
+ s"(got ${labelArray.length} and ${predArray.length}).")
this.sumMetric +=
labelArray.zip(predArray).map { case (l, p) => if (l == p) 1 else 0 }.sum
} else if (dims == 2) {
@@ -151,7 +154,9 @@ class TopKAccuracy(topK: Int) extends EvalMetric("top_k_accuracy") {
val predArray = pred.toArray.grouped(numclasses).map { a =>
a.zipWithIndex.sortBy(_._1).reverse.map(_._2)
}.toArray
- require(predArray.length == labelArray.length)
+ require(predArray.length == labelArray.length,
+ s"Each label and prediction array should have the same length " +
+ s"(got ${labelArray.length} and ${predArray.length}).")
val topK = Math.max(this.topK, numclasses)
for (j <- 0 until topK) {
this.sumMetric +=
@@ -169,7 +174,8 @@ class TopKAccuracy(topK: Int) extends EvalMetric("top_k_accuracy") {
class F1 extends EvalMetric("f1") {
override def update(labels: IndexedSeq[NDArray], preds: IndexedSeq[NDArray]): Unit = {
require(labels.length == preds.length,
- "labels and predictions should have the same length.")
+ s"labels and predictions should have the same length " +
+ s"(got ${labels.length} and ${preds.length}).")
for ((pred, label) <- preds zip labels) {
val predLabel = NDArray.argmax_channel(pred)
@@ -223,7 +229,8 @@ class F1 extends EvalMetric("f1") {
class Perplexity(ignoreLabel: Option[Int] = None, axis: Int = -1) extends EvalMetric("Perplexity") {
override def update(labels: IndexedSeq[NDArray], preds: IndexedSeq[NDArray]): Unit = {
require(labels.length == preds.length,
- "labels and predictions should have the same length.")
+ s"labels and predictions should have the same length " +
+ s"(got ${labels.length} and ${preds.length}).")
var loss = 0d
var num = 0
val probs = ArrayBuffer[NDArray]()
@@ -261,12 +268,16 @@ class Perplexity(ignoreLabel: Option[Int] = None, axis: Int = -1) extends EvalMe
*/
class MAE extends EvalMetric("mae") {
override def update(labels: IndexedSeq[NDArray], preds: IndexedSeq[NDArray]): Unit = {
- require(labels.size == preds.size, "labels and predictions should have the same length.")
+ require(labels.size == preds.size,
+ s"labels and predictions should have the same length " +
+ s"(got ${labels.length} and ${preds.length}).")
for ((label, pred) <- labels zip preds) {
val labelArr = label.toArray
val predArr = pred.toArray
- require(labelArr.length == predArr.length)
+ require(labelArr.length == predArr.length,
+ s"Each label and prediction array should have the same length " +
+ s"(got ${labelArr.length} and ${predArr.length}).")
this.sumMetric +=
(labelArr zip predArr).map { case (l, p) => Math.abs(l - p) }.sum / labelArr.length
this.numInst += 1
@@ -277,12 +288,16 @@ class MAE extends EvalMetric("mae") {
// Calculate Mean Squared Error loss
class MSE extends EvalMetric("mse") {
override def update(labels: IndexedSeq[NDArray], preds: IndexedSeq[NDArray]): Unit = {
- require(labels.size == preds.size, "labels and predictions should have the same length.")
+ require(labels.size == preds.size,
+ s"labels and predictions should have the same length " +
+ s"(got ${labels.length} and ${preds.length}).")
for ((label, pred) <- labels zip preds) {
val labelArr = label.toArray
val predArr = pred.toArray
- require(labelArr.length == predArr.length)
+ require(labelArr.length == predArr.length,
+ s"Each label and prediction array should have the same length " +
+ s"(got ${labelArr.length} and ${predArr.length}).")
this.sumMetric +=
(labelArr zip predArr).map { case (l, p) => (l - p) * (l - p) }.sum / labelArr.length
this.numInst += 1
@@ -295,12 +310,16 @@ class MSE extends EvalMetric("mse") {
*/
class RMSE extends EvalMetric("rmse") {
override def update(labels: IndexedSeq[NDArray], preds: IndexedSeq[NDArray]): Unit = {
- require(labels.size == preds.size, "labels and predictions should have the same length.")
+ require(labels.size == preds.size,
+ s"labels and predictions should have the same length " +
+ s"(got ${labels.length} and ${preds.length}).")
for ((label, pred) <- labels zip preds) {
val labelArr = label.toArray
val predArr = pred.toArray
- require(labelArr.length == predArr.length)
+ require(labelArr.length == predArr.length,
+ s"Each label and prediction array should have the same length " +
+ s"(got ${labelArr.length} and ${predArr.length}).")
val metric: Double = Math.sqrt(
(labelArr zip predArr).map { case (l, p) => (l - p) * (l - p) }.sum / labelArr.length)
this.sumMetric += metric.toFloat
@@ -318,7 +337,9 @@ class RMSE extends EvalMetric("rmse") {
class CustomMetric(fEval: (NDArray, NDArray) => Float,
name: String) extends EvalMetric(name) {
override def update(labels: IndexedSeq[NDArray], preds: IndexedSeq[NDArray]): Unit = {
- require(labels.size == preds.size, "labels and predictions should have the same length.")
+ require(labels.size == preds.size,
+ s"labels and predictions should have the same length " +
+ s"(got ${labels.length} and ${preds.length}).")
for ((label, pred) <- labels zip preds) {
this.sumMetric += fEval(label, pred)
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/Executor.scala b/scala-package/core/src/main/scala/org/apache/mxnet/Executor.scala
index 181b2328ddc..fc791d5cd9a 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/Executor.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/Executor.scala
@@ -26,7 +26,7 @@ object Executor {
// Get the dictionary given name and ndarray pairs.
private[mxnet] def getDict(names: Seq[String],
ndarrays: Seq[NDArray]): Map[String, NDArray] = {
- require(names.toSet.size == names.length, "Duplicate names detected")
+ require(names.toSet.size == names.length, s"Duplicate names detected in ($names)")
(names zip ndarrays).toMap
}
}
@@ -86,7 +86,10 @@ class Executor private[mxnet](private[mxnet] val handle: ExecutorHandle,
def reshape(partialShaping: Boolean = false, allowUpSizing: Boolean = false,
kwargs: Map[String, Shape]): Executor = {
val (argShapes, _, auxShapes) = this.symbol.inferShape(kwargs)
- require(argShapes != null, "Insufficient argument shapes provided.")
+ // TODO: more precise error message should be provided by backend
+ require(argShapes != null, "Shape inference failed." +
+ s"Known shapes are $kwargs for symbol arguments ${symbol.listArguments()} " +
+ s"and aux states ${symbol.listAuxiliaryStates()}")
var newArgDict = Map[String, NDArray]()
var newGradDict = Map[String, NDArray]()
@@ -194,13 +197,13 @@ class Executor private[mxnet](private[mxnet] val handle: ExecutorHandle,
* on outputs that are not a loss function.
*/
def backward(outGrads: Array[NDArray]): Unit = {
- require(outGrads != null)
+ require(outGrads != null, "outGrads must not be null")
val ndArrayPtrs = outGrads.map(_.handle)
checkCall(_LIB.mxExecutorBackward(handle, ndArrayPtrs))
}
def backward(outGrad: NDArray): Unit = {
- require(outGrad != null)
+ require(outGrad != null, "outGrads must not be null")
backward(Array(outGrad))
}
@@ -271,7 +274,7 @@ class Executor private[mxnet](private[mxnet] val handle: ExecutorHandle,
if (argDict.contains(name)) {
array.copyTo(argDict(name))
} else {
- require(allowExtraParams, s"Find name $name that is not in the arguments")
+ require(allowExtraParams, s"Provided name $name is not in the arguments")
}
}
if (auxParams != null) {
@@ -279,7 +282,7 @@ class Executor private[mxnet](private[mxnet] val handle: ExecutorHandle,
if (auxDict.contains(name)) {
array.copyTo(auxDict(name))
} else {
- require(allowExtraParams, s"Find name $name that is not in the auxiliary states")
+ require(allowExtraParams, s"Provided name $name is not in the auxiliary states")
}
}
}
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/ExecutorManager.scala b/scala-package/core/src/main/scala/org/apache/mxnet/ExecutorManager.scala
index 22914a558b4..b13741bdd3b 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/ExecutorManager.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/ExecutorManager.scala
@@ -54,7 +54,8 @@ private[mxnet] class DataParallelExecutorManager(private val symbol: Symbol,
if (workLoadList == null) {
workLoadList = Seq.fill(numDevice)(1f)
}
- require(workLoadList.size == numDevice, "Invalid settings for work load.")
+ require(workLoadList.size == numDevice, "Invalid settings for work load. " +
+ s"Size (${workLoadList.size}) should match num devices ($numDevice)")
private val slices = ExecutorManager.splitInputSlice(trainData.batchSize, workLoadList)
@@ -212,13 +213,13 @@ private[mxnet] object ExecutorManager {
private[mxnet] def checkArguments(symbol: Symbol): Unit = {
val argNames = symbol.listArguments()
require(argNames.toSet.size == argNames.length,
- "Find duplicated argument name," +
+ "Found duplicated argument name," +
"please make the weight name non-duplicated(using name arguments)," +
s"arguments are $argNames")
val auxNames = symbol.listAuxiliaryStates()
require(auxNames.toSet.size == auxNames.length,
- "Find duplicated auxiliary param name," +
+ "Found duplicated auxiliary param name," +
"please make the weight name non-duplicated(using name arguments)," +
s"arguments are $auxNames")
}
@@ -272,7 +273,11 @@ private[mxnet] object ExecutorManager {
sharedDataArrays: mutable.Map[String, NDArray] = null,
inputTypes: ListMap[String, DType] = null) = {
val (argShape, _, auxShape) = sym.inferShape(inputShapes)
- require(argShape != null)
+ // TODO: more precise error message should be provided by backend
+ require(argShape != null, "Shape inference failed." +
+ s"Known shapes are $inputShapes for symbol arguments ${sym.listArguments()} " +
+ s"and aux states ${sym.listAuxiliaryStates()}")
+
val inputTypesUpdate =
if (inputTypes == null) {
inputShapes.map { case (key, _) => (key, Base.MX_REAL_TYPE) }
@@ -280,7 +285,9 @@ private[mxnet] object ExecutorManager {
inputTypes
}
val (argTypes, _, auxTypes) = sym.inferType(inputTypesUpdate)
- require(argTypes != null)
+ require(argTypes != null, "Type inference failed." +
+ s"Known types as $inputTypes for symbol arguments ${sym.listArguments()} " +
+ s"and aux states ${sym.listAuxiliaryStates()}")
val argArrays = ArrayBuffer.empty[NDArray]
val gradArrays: mutable.Map[String, NDArray] =
@@ -311,7 +318,8 @@ private[mxnet] object ExecutorManager {
val arr = sharedDataArrays(name)
if (arr.shape.product >= argShape(i).product) {
// good, we can share this memory
- require(argTypes(i) == arr.dtype)
+ require(argTypes(i) == arr.dtype,
+ s"Type ${arr.dtype} of argument $name does not match inferred type ${argTypes(i)}")
arr.reshape(argShape(i))
} else {
DataParallelExecutorManager.logger.warn(
@@ -345,8 +353,10 @@ private[mxnet] object ExecutorManager {
NDArray.zeros(argShape(i), ctx, dtype = argTypes(i))
} else {
val arr = baseExec.argDict(name)
- require(arr.shape == argShape(i))
- require(arr.dtype == argTypes(i))
+ require(arr.shape == argShape(i),
+ s"Shape ${arr.shape} of argument $name does not match inferred shape ${argShape(i)}")
+ require(arr.dtype == argTypes(i),
+ s"Type ${arr.dtype} of argument $name does not match inferred type ${argTypes(i)}")
if (gradSet.contains(name)) {
gradArrays.put(name, baseExec.gradDict(name))
}
@@ -356,6 +366,7 @@ private[mxnet] object ExecutorManager {
}
}
// create or borrow aux variables
+ val auxNames = sym.listAuxiliaryStates()
val auxArrays =
if (baseExec == null) {
(auxShape zip auxTypes) map { case (s, t) =>
@@ -363,8 +374,12 @@ private[mxnet] object ExecutorManager {
}
} else {
baseExec.auxArrays.zipWithIndex.map { case (a, i) =>
- require(auxShape(i) == a.shape)
- require(auxTypes(i) == a.dtype)
+ require(auxShape(i) == a.shape,
+ s"Shape ${a.shape} of aux variable ${auxNames(i)} does not match " +
+ s"inferred shape ${auxShape(i)}")
+ require(auxTypes(i) == a.dtype,
+ s"Type ${a.dtype} of aux variable ${auxNames(i)} does not match " +
+ s"inferred type ${auxTypes(i)}")
a
}.toSeq
}
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/FeedForward.scala b/scala-package/core/src/main/scala/org/apache/mxnet/FeedForward.scala
index 87c9bc72be0..00a1450089f 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/FeedForward.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/FeedForward.scala
@@ -99,7 +99,7 @@ class FeedForward private(
// verify the argument of the default symbol and user provided parameters
def checkArguments(): Unit = {
if (!argumentChecked) {
- require(symbol != null)
+ require(symbol != null, "Symbol must not be null")
// check if symbol contain duplicated names.
ExecutorManager.checkArguments(symbol)
// rematch parameters to delete useless ones
@@ -169,7 +169,9 @@ class FeedForward private(
private def initPredictor(inputShapes: Map[String, Shape]): Unit = {
if (this.predExec != null) {
val (argShapes, _, _) = symbol.inferShape(inputShapes)
- require(argShapes != null, "Incomplete input shapes")
+ require(argShapes != null, "Shape inference failed." +
+ s"Known shapes are $inputShapes for symbol arguments ${symbol.listArguments()} " +
+ s"and aux states ${symbol.listAuxiliaryStates()}")
val predShapes = this.predExec.argArrays.map(_.shape)
if (argShapes.sameElements(predShapes)) {
return
@@ -187,7 +189,8 @@ class FeedForward private(
require(y != null || !isTrain, "y must be specified")
val label = if (y == null) NDArray.zeros(X.shape(0)) else y
require(label.shape.length == 1, "Label must be 1D")
- require(X.shape(0) == label.shape(0), "The numbers of data points and labels not equal")
+ require(X.shape(0) == label.shape(0),
+ s"The numbers of data points (${X.shape(0)}) and labels (${label.shape(0)}) are not equal")
if (isTrain) {
new NDArrayIter(IndexedSeq(X), IndexedSeq(label), batchSize,
shuffle = isTrain, lastBatchHandle = "roll_over")
@@ -402,7 +405,7 @@ class FeedForward private(
* - ``prefix-epoch.params`` will be saved for parameters.
*/
def save(prefix: String, epoch: Int = this.numEpoch): Unit = {
- require(epoch >= 0)
+ require(epoch >= 0, s"epoch must be >=0 (got $epoch)")
Model.saveCheckpoint(prefix, epoch, this.symbol, getArgParams, getAuxParams)
}
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/IO.scala b/scala-package/core/src/main/scala/org/apache/mxnet/IO.scala
index a1095cf0483..e8351422c48 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/IO.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/IO.scala
@@ -114,8 +114,9 @@ object IO {
defaultName: String,
defaultDType: DType,
defaultLayout: String): IndexedSeq[(DataDesc, NDArray)] = {
- require(data != null)
- require(data != IndexedSeq.empty || allowEmpty)
+ require(data != null, "data is required.")
+ require(data != IndexedSeq.empty || allowEmpty,
+ s"data should not be empty when allowEmpty is false")
if (data == IndexedSeq.empty) {
IndexedSeq()
} else if (data.length == 1) {
@@ -372,9 +373,7 @@ abstract class DataPack() extends Iterable[DataBatch] {
case class DataDesc(name: String, shape: Shape,
dtype: DType = DType.Float32, layout: String = Layout.UNDEFINED) {
require(layout == Layout.UNDEFINED || shape.length == layout.length,
- ("number of dimensions in shape :%d with" +
- " shape: %s should match the length of the layout: %d with layout: %s").
- format(shape.length, shape.toString, layout.length, layout))
+ s"number of dimensions in $shape should match the layout $layout")
override def toString(): String = {
s"DataDesc[$name,$shape,$dtype,$layout]"
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/Initializer.scala b/scala-package/core/src/main/scala/org/apache/mxnet/Initializer.scala
index e26690c9192..8531285ba60 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/Initializer.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/Initializer.scala
@@ -98,7 +98,8 @@ abstract class Initializer {
*/
class Mixed(protected val patterns: List[String],
protected val initializers: List[Initializer]) extends Initializer {
- require(patterns.length == initializers.length)
+ require(patterns.length == initializers.length,
+ "Should provide a pattern for each initializer")
private val map = patterns.map(_.r).zip(initializers)
override def apply(name: String, arr: NDArray): Unit = {
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/Model.scala b/scala-package/core/src/main/scala/org/apache/mxnet/Model.scala
index ad6fae5765c..4bb9cdd331a 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/Model.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/Model.scala
@@ -160,7 +160,8 @@ object Model {
argParams: Map[String, NDArray],
paramNames: IndexedSeq[String],
updateOnKVStore: Boolean): Unit = {
- require(paramArrays.length == paramNames.length)
+ require(paramArrays.length == paramNames.length,
+ s"Provided parameter arrays does not match parameter names")
for (idx <- 0 until paramArrays.length) {
val paramOnDevs = paramArrays(idx)
val name = paramNames(idx)
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/NDArray.scala b/scala-package/core/src/main/scala/org/apache/mxnet/NDArray.scala
index 8b5e1e01095..9b6a7dc6654 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/NDArray.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/NDArray.scala
@@ -427,7 +427,7 @@ object NDArray extends NDArrayBase {
* @return An `NDArray` that lives on the same context as `arrays[0].context`.
*/
def concatenate(arrays: Seq[NDArray], axis: Int = 0, alwaysCopy: Boolean = true): NDArray = {
- require(arrays.size > 0)
+ require(arrays.size > 0, "Provide at least one array")
val array0 = arrays(0)
if (!alwaysCopy && arrays.size == 1) {
@@ -439,9 +439,12 @@ object NDArray extends NDArrayBase {
val shapeAxis =
arrays.map(arr => {
- require(shapeRest1 == arr.shape.slice(0, axis))
- require(shapeRest2 == arr.shape.slice(axis + 1, arr.shape.length))
- require(dtype == arr.dtype)
+ require(shapeRest1 == arr.shape.slice(0, axis),
+ s"Mismatch between shape $shapeRest1 and ${arr.shape}")
+ require(shapeRest2 == arr.shape.slice(axis + 1, arr.shape.length),
+ s"Mismatch between shape $shapeRest2 and ${arr.shape}")
+ require(dtype == arr.dtype,
+ s"All arrays must have the same type (got ${dtype} and ${arr.dtype})")
arr.shape(axis)
}).sum
val retShape = shapeRest1 ++ Shape(shapeAxis) ++ shapeRest2
@@ -484,7 +487,7 @@ object NDArray extends NDArrayBase {
* - `s3://my-bucket/path/my-s3-ndarray`
* - `hdfs://my-bucket/path/my-hdfs-ndarray`
* - `/path-to/my-local-ndarray`
- * @return dict of str->NDArray to be saved
+ * @return dict of str->NDArray
*/
def load(fname: String): (Array[String], Array[NDArray]) = {
val outSize = new MXUintRef
@@ -492,7 +495,8 @@ object NDArray extends NDArrayBase {
val handles = ArrayBuffer.empty[NDArrayHandle]
val names = ArrayBuffer.empty[String]
checkCall(_LIB.mxNDArrayLoad(fname, outSize, handles, outNameSize, names))
- require(outNameSize.value == 0 || outNameSize.value == outSize.value)
+ require(outNameSize.value == 0 || outNameSize.value == outSize.value,
+ s"Mismatch between names and arrays in file $fname")
(names.toArray, handles.map(new NDArray(_)).toArray)
}
@@ -1003,7 +1007,7 @@ class NDArray private[mxnet](private[mxnet] val handle: NDArrayHandle,
val ndim = new MXUintRef
val data = ArrayBuffer[Int]()
checkCall(_LIB.mxNDArrayGetShape(handle, ndim, data))
- require(ndim.value == data.length, s"ndim=$ndim, while len(pdata)=${data.length}")
+ require(ndim.value == data.length, s"ndim=$ndim, while len(data)=${data.length}")
Shape(data)
}
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/Operator.scala b/scala-package/core/src/main/scala/org/apache/mxnet/Operator.scala
index f2abe5e4515..a521702967e 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/Operator.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/Operator.scala
@@ -134,7 +134,8 @@ abstract class CustomOpProp(needTopGrad: Boolean = false) {
protected var kwargs: Map[String, String] = Map[String, String]()
private[mxnet] def init(keys: Array[String], vals: Array[String]): Unit = {
- require(keys.length == vals.length)
+ require(keys.length == vals.length,
+ s"Number of keys (${keys.length}) does not match arrays (${vals.length})")
kwargs = keys.zip(vals).toMap
}
@@ -166,11 +167,13 @@ abstract class CustomOpProp(needTopGrad: Boolean = false) {
val tmp = this.listAuxiliaryStates()
if (tmp == null) 0 else tmp.length
}
- require(numTensor == (nIn + nOut + nAux))
+ require(numTensor == (nIn + nOut + nAux),
+ s"Shape inference failed. $numTensor tensors expected, but got " +
+ s"$nIn args, $nOut ouputs and $nAux aux states")
val (inShapes, outShapes, auxShapes) =
inferShape(intputShapes.map(Shape(_)))
- require(inShapes != null && inShapes.length != 0)
- require(outShapes != null && outShapes.length != 0)
+ require(inShapes != null && inShapes.length != 0, "InputShape is undefined or empty")
+ require(outShapes != null && outShapes.length != 0, "OutputShape is undefined or empty")
if (auxShapes != null && auxShapes.length != 0) {
inShapes.map(_.toArray) ++ outShapes.map(_.toArray) ++ auxShapes.map(_.toArray)
} else inShapes.map(_.toArray) ++ outShapes.map(_.toArray)
@@ -206,11 +209,13 @@ abstract class CustomOpProp(needTopGrad: Boolean = false) {
val tmp = this.listAuxiliaryStates()
if (tmp == null) 0 else tmp.length
}
- require(numTensor == (nIn + nOut + nAux))
+ require(numTensor == (nIn + nOut + nAux),
+ s"Type inference failed. $numTensor tensors expected, but got " +
+ s"$nIn args, $nOut ouputs and $nAux aux states")
val (inTypes, outTypes, auxTypes) =
inferType(intputTypes.map(DType(_)))
- require(inTypes != null && inTypes.length != 0)
- require(outTypes != null && outTypes.length != 0)
+ require(inTypes != null && inTypes.length != 0, "InputType is undefined or empty")
+ require(outTypes != null && outTypes.length != 0, "OutputType is undefined or empty")
if (auxTypes != null && auxTypes.length != 0) {
inTypes.map(_.id) ++ outTypes.map(_.id) ++ auxTypes.map(_.id)
} else inTypes.map(_.id) ++ outTypes.map(_.id)
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/Profiler.scala b/scala-package/core/src/main/scala/org/apache/mxnet/Profiler.scala
index df10b34f127..a917377f096 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/Profiler.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/Profiler.scala
@@ -44,7 +44,7 @@ object Profiler {
* be "stop" or "run". Default is "stop".
*/
def profilerSetState(state: String = "stop"): Unit = {
- require(state2Int.contains(state))
+ require(state2Int.contains(state), s"Invalid state $state")
checkCall(_LIB.mxSetProfilerState(state2Int(state)))
}
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/Symbol.scala b/scala-package/core/src/main/scala/org/apache/mxnet/Symbol.scala
index e3e1a320358..b1a3e392f41 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/Symbol.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/Symbol.scala
@@ -423,7 +423,13 @@ class Symbol private(private[mxnet] val handle: SymbolHandle) extends WarnIfNotD
}
val (argShapes, _, auxShapes) = inferShape(shapeDict)
val (argTypes, _, auxTypes) = inferType(types)
- require(argShapes != null && argTypes != null, "Input node is not complete")
+ require(argShapes != null, "Shape inference failed." +
+ s"Known shapes are $shapeDict for symbol arguments ${listArguments()} " +
+ s"and aux states ${listAuxiliaryStates()}")
+ require(argTypes != null, "Type inference failed." +
+ s"Known types as $typeDict for symbol arguments ${listArguments()} " +
+ s"and aux states ${listAuxiliaryStates()}")
+
// alloc space
val argNDArrays = (argShapes zip argTypes) map { case (shape, t) =>
NDArray.zeros(shape, ctx, dtype = t)
@@ -715,10 +721,14 @@ class Symbol private(private[mxnet] val handle: SymbolHandle) extends WarnIfNotD
args: Iterable[_], argsGrad: Iterable[_],
gradsReq: Iterable[_], auxStates: Iterable[_],
group2ctx: Map[String, Context], sharedExec: Executor): Executor = {
- require(args != null && !args.isInstanceOf[Set[_]])
- require(argsGrad == null || !argsGrad.isInstanceOf[Set[_]])
- require(auxStates == null || !auxStates.isInstanceOf[Set[_]])
- require(gradsReq != null && !gradsReq.isInstanceOf[Set[_]])
+ require(args != null && !args.isInstanceOf[Set[_]],
+ s"args must be provided (Set is not supported)")
+ require(argsGrad == null || !argsGrad.isInstanceOf[Set[_]],
+ s"argsGrad must be provided (Set is not supported)")
+ require(auxStates == null || !auxStates.isInstanceOf[Set[_]],
+ s"auxStates must be provided (Set is not supported)")
+ require(gradsReq != null && !gradsReq.isInstanceOf[Set[_]],
+ s"gradsReq must be provided (Set is not supported)")
val (argsHandle, argsNDArray) =
if (args.isInstanceOf[Seq[_]]) {
@@ -756,14 +766,16 @@ class Symbol private(private[mxnet] val handle: SymbolHandle) extends WarnIfNotD
val reqsArray =
if (gradsReq.isInstanceOf[Seq[_]]) {
gradsReq.asInstanceOf[Seq[String]].map { req =>
- require(Symbol.bindReqMap.contains(req), s"grad_req must be in ${Symbol.bindReqMap}")
+ require(Symbol.bindReqMap.contains(req),
+ s"grad_req $req must be in ${Symbol.bindReqMap}")
Symbol.bindReqMap(req)
}.toArray
} else {
val gradsReqMap = gradsReq.asInstanceOf[Map[String, String]]
symbolArguments.map { req =>
val value = gradsReqMap.getOrElse(req, "null")
- require(Symbol.bindReqMap.contains(value), s"grad_req must be in ${Symbol.bindReqMap}")
+ require(Symbol.bindReqMap.contains(value),
+ s"grad_req $req must be in ${Symbol.bindReqMap}")
Symbol.bindReqMap(value)
}.toArray
}
@@ -1083,9 +1095,9 @@ object Symbol extends SymbolBase {
(key, value.toString)
}
}
- require(symbols.isEmpty || symbolKwargs.isEmpty, String.format(
- "%s can only accept input Symbols either as positional or keyword arguments, not both",
- operator))
+ require(symbols.isEmpty || symbolKwargs.isEmpty,
+ s"$operator can only accept input Symbols either as positional or keyword arguments, " +
+ s"not both")
if (symbols.isEmpty) {
createFromNamedSymbols(operator, name, attr)(symbolKwargs, strKwargs)
} else {
@@ -1217,7 +1229,8 @@ object Symbol extends SymbolBase {
*/
private def getNDArrayInputs(argKey: String, args: Seq[NDArray], argNames: Seq[String],
allowMissing: Boolean): (Array[NDArrayHandle], Array[NDArray]) = {
- require(args.length == argNames.length, s"Length of $argKey do not match number of arguments")
+ require(args.length == argNames.length,
+ s"Length of $argKey do not match number of arguments")
val argHandles = args.map(_.handle)
(argHandles.toArray, args.toArray)
}
@@ -1232,7 +1245,8 @@ object Symbol extends SymbolBase {
argArrays += narr.get
argHandles += narr.get.handle
case None =>
- require(allowMissing, s"Must specify all the arguments in $argKey")
+ require(allowMissing,
+ s"Must specify all the arguments in $argKey. $name is unknown")
argArrays += null
argHandles += 0L
}
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/Visualization.scala b/scala-package/core/src/main/scala/org/apache/mxnet/Visualization.scala
index 6ecc3cadbc2..2a7b7a8b31b 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/Visualization.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/Visualization.scala
@@ -198,9 +198,9 @@ object Visualization {
case None => null
case Some(map) => map.asInstanceOf[Map[String, Any]]
}
- require(conf != null)
+ require(conf != null, "Invalid json")
- require(conf.contains("nodes"))
+ require(conf.contains("nodes"), "Invalid json")
val nodes = conf("nodes").asInstanceOf[List[Any]]
// default attributes of node
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/module/BaseModule.scala b/scala-package/core/src/main/scala/org/apache/mxnet/module/BaseModule.scala
index 60b80f25285..30e57c57fbe 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/module/BaseModule.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/module/BaseModule.scala
@@ -171,8 +171,8 @@ abstract class BaseModule {
batchEndCallback: Option[BatchEndCallback] = None,
scoreEndCallback: Option[BatchEndCallback] = None,
reset: Boolean = true, epoch: Int = 0): EvalMetric = {
- require(evalData != null && evalMetric != null)
- require(binded && paramsInitialized)
+ require(evalData != null && evalMetric != null, "evalData and evalMetric must be defined")
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
if (reset) {
evalData.reset()
@@ -216,7 +216,7 @@ abstract class BaseModule {
*/
def predictEveryBatch(evalData: DataIter, numBatch: Int = -1, reset: Boolean = true)
: IndexedSeq[IndexedSeq[NDArray]] = {
- require(binded && paramsInitialized)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
if (reset) {
evalData.reset()
}
@@ -234,7 +234,7 @@ abstract class BaseModule {
}
def predict(batch: DataBatch): IndexedSeq[NDArray] = {
- require(binded && paramsInitialized)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
forward(batch, isTrain = Option(false))
val pad = batch.pad
getOutputsMerged().map(out => {
@@ -260,7 +260,8 @@ abstract class BaseModule {
val numOutputs = outputBatches.head.size
outputBatches.foreach(out =>
require(out.size == numOutputs,
- "Cannot merge batches, as num of outputs is not the same in mini-batches." +
+ s"Cannot merge batches, as num of outputs $numOutputs is not the same " +
+ s"in mini-batches (${out.size})." +
"Maybe bucketing is used?")
)
val concatenatedOutput = outputBatches.map(out => NDArray.concatenate(out))
@@ -395,8 +396,8 @@ abstract class BaseModule {
*/
def fit(trainData: DataIter, evalData: Option[DataIter] = None, numEpoch: Int = 1,
fitParams: FitParams = new FitParams): Unit = {
- require(fitParams != null)
- require(numEpoch > 0, "please specify number of epochs")
+ require(fitParams != null, "Undefined fitParams")
+ require(numEpoch > 0, s"Invalid number of epochs $numEpoch")
import org.apache.mxnet.DataDesc._
bind(dataShapes = trainData.provideData, labelShapes = Option(trainData.provideLabel),
forTraining = true, forceRebind = fitParams.forceRebind)
@@ -604,7 +605,7 @@ class FitParams {
// The performance measure used to display during training.
def setEvalMetric(evalMetric: EvalMetric): FitParams = {
- require(evalMetric != null)
+ require(evalMetric != null, "Undefined evalMetric")
this.evalMetric = evalMetric
this
}
@@ -623,13 +624,13 @@ class FitParams {
}
def setKVStore(kvStore: String): FitParams = {
- require(kvStore != null)
+ require(kvStore != null, "Undefined kvStore")
this.kvstore = kvstore
this
}
def setOptimizer(optimizer: Optimizer): FitParams = {
- require(optimizer != null)
+ require(optimizer != null, "Undefined optimizer")
this.optimizer = optimizer
this
}
@@ -649,7 +650,7 @@ class FitParams {
// Will be called to initialize the module parameters if not already initialized.
def setInitializer(initializer: Initializer): FitParams = {
- require(initializer != null)
+ require(initializer != null, "Undefined Initializer")
this.initializer = initializer
this
}
@@ -697,7 +698,7 @@ class FitParams {
// checkpoint saved at a previous training phase at epoch N,
// then we should specify this value as N+1.
def setBeginEpoch(beginEpoch: Int): FitParams = {
- require(beginEpoch >= 0)
+ require(beginEpoch >= 0, s"Invalid epoch $beginEpoch")
this.beginEpoch = beginEpoch
this
}
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/module/BucketingModule.scala b/scala-package/core/src/main/scala/org/apache/mxnet/module/BucketingModule.scala
index 28238188549..2262f5c6aa3 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/module/BucketingModule.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/module/BucketingModule.scala
@@ -52,7 +52,8 @@ class BucketingModule(symGen: AnyRef => (Symbol, IndexedSeq[String], IndexedSeq[
}
private val workLoads = workLoadList.getOrElse(contexts.map(_ => 1f).toIndexedSeq)
- require(workLoads.size == contexts.length)
+ require(workLoads.size == contexts.length,
+ s"workloads size (${workLoads.size}) do not match number of contexts ${contexts.length}")
private val _buckets = scala.collection.mutable.Map[AnyRef, Module]()
private var _currModule: Module = null
@@ -84,7 +85,7 @@ class BucketingModule(symGen: AnyRef => (Symbol, IndexedSeq[String], IndexedSeq[
// Input/Output information
// A list of (name, shape) pairs specifying the data inputs to this module.
override def dataShapes: IndexedSeq[DataDesc] = {
- require(this.binded)
+ require(this.binded, "bind() must be called first.")
this._currModule.dataShapes
}
@@ -95,13 +96,13 @@ class BucketingModule(symGen: AnyRef => (Symbol, IndexedSeq[String], IndexedSeq[
* list `[]`.
*/
override def labelShapes: IndexedSeq[DataDesc] = {
- require(this.binded)
+ require(this.binded, "bind() must be called first.")
this._currModule.labelShapes
}
// A list of (name, shape) pairs specifying the outputs of this module.
override def outputShapes: IndexedSeq[(String, Shape)] = {
- require(this.binded)
+ require(this.binded, "bind() must be called first.")
this._currModule.outputShapes
}
@@ -111,7 +112,7 @@ class BucketingModule(symGen: AnyRef => (Symbol, IndexedSeq[String], IndexedSeq[
* `NDArray`) mapping.
*/
override def getParams: (Map[String, NDArray], Map[String, NDArray]) = {
- require(binded && paramsInitialized)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
this._currModule.paramsDirty = this.paramsDirty
val params = this._currModule.getParams
this.paramsDirty = false
@@ -220,8 +221,8 @@ class BucketingModule(symGen: AnyRef => (Symbol, IndexedSeq[String], IndexedSeq[
return
}
- require(sharedModule == None,
- "shared_module for BucketingModule is not supported")
+ require(sharedModule.isEmpty,
+ "sharedModule for BucketingModule is not supported")
this.forTraining = forTraining
this.inputsNeedGrad = inputsNeedGrad
@@ -276,7 +277,7 @@ class BucketingModule(symGen: AnyRef => (Symbol, IndexedSeq[String], IndexedSeq[
*/
override def initOptimizer(kvstore: String = "local", optimizer: Optimizer = new SGD(),
resetOptimizer: Boolean = true, forceInit: Boolean = false): Unit = {
- require(binded && paramsInitialized)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
if (optimizerInitialized && !forceInit) {
logger.warn("optimizer already initialized, ignoring ...")
} else {
@@ -294,7 +295,7 @@ class BucketingModule(symGen: AnyRef => (Symbol, IndexedSeq[String], IndexedSeq[
*/
def prepare(dataBatch: DataBatch): Unit = {
// perform bind if haven't done so
- require(this.binded && this.paramsInitialized)
+ require(this.binded && this.paramsInitialized, "bind() and initParams() must be called first.")
val bucketKey = dataBatch.bucketKey
val originalBucketKey = this._currBucketKey
this.switchBucket(bucketKey, dataBatch.provideData, Option(dataBatch.provideLabel))
@@ -308,7 +309,7 @@ class BucketingModule(symGen: AnyRef => (Symbol, IndexedSeq[String], IndexedSeq[
* @param isTrain Default is `None`, which means `is_train` takes the value of `for_training`.
*/
override def forward(dataBatch: DataBatch, isTrain: Option[Boolean] = None): Unit = {
- require(binded && paramsInitialized)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
this.switchBucket(dataBatch.bucketKey, dataBatch.provideData,
Option(dataBatch.provideLabel))
this._currModule.forward(dataBatch, isTrain)
@@ -321,14 +322,15 @@ class BucketingModule(symGen: AnyRef => (Symbol, IndexedSeq[String], IndexedSeq[
* on outputs that are not a loss function.
*/
override def backward(outGrads: Array[NDArray] = null): Unit = {
- require(binded && paramsInitialized)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
this._currModule.backward(outGrads)
}
// Update parameters according to the installed optimizer and the gradients computed
// in the previous forward-backward cycle.
override def update(): Unit = {
- require(binded && paramsInitialized && optimizerInitialized)
+ require(binded && paramsInitialized && optimizerInitialized,
+ "bind(), initParams() and initOptimizer() must be called first.")
this.paramsDirty = true
this._currModule.update()
}
@@ -341,7 +343,7 @@ class BucketingModule(symGen: AnyRef => (Symbol, IndexedSeq[String], IndexedSeq[
* those `NDArray` might live on different devices.
*/
override def getOutputs(): IndexedSeq[IndexedSeq[NDArray]] = {
- require(binded && paramsInitialized)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
this._currModule.getOutputs()
}
@@ -353,7 +355,7 @@ class BucketingModule(symGen: AnyRef => (Symbol, IndexedSeq[String], IndexedSeq[
* The results will look like `[out1, out2]`
*/
override def getOutputsMerged(): IndexedSeq[NDArray] = {
- require(binded && paramsInitialized)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
this._currModule.getOutputsMerged()
}
@@ -365,7 +367,8 @@ class BucketingModule(symGen: AnyRef => (Symbol, IndexedSeq[String], IndexedSeq[
* those `NDArray` might live on different devices.
*/
override def getInputGrads(): IndexedSeq[IndexedSeq[NDArray]] = {
- require(binded && paramsInitialized && inputsNeedGrad)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
+ require(inputsNeedGrad, "Call to getInputGrads() but inputsNeedGrad is false")
this._currModule.getInputGrads()
}
@@ -377,7 +380,8 @@ class BucketingModule(symGen: AnyRef => (Symbol, IndexedSeq[String], IndexedSeq[
* The results will look like `[grad1, grad2]`
*/
override def getInputGradsMerged(): IndexedSeq[NDArray] = {
- require(binded && paramsInitialized && inputsNeedGrad)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
+ require(inputsNeedGrad, "Call to getInputGradsMerged() but inputsNeedGrad is false")
this._currModule.getInputGradsMerged()
}
@@ -387,18 +391,18 @@ class BucketingModule(symGen: AnyRef => (Symbol, IndexedSeq[String], IndexedSeq[
* @param labels
*/
override def updateMetric(evalMetric: EvalMetric, labels: IndexedSeq[NDArray]): Unit = {
- require(binded && paramsInitialized)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
this._currModule.updateMetric(evalMetric, labels)
}
override def getSymbol: Symbol = {
- require(binded)
+ require(binded, "bind() must be called first.")
this._currModule.symbol
}
// Install monitor on all executors
override def installMonitor(monitor: Monitor): Unit = {
- require(binded)
+ require(binded, "bind() must be called first.")
for (mod <- this._buckets.values) mod.installMonitor(monitor)
}
}
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/module/DataParallelExecutorGroup.scala b/scala-package/core/src/main/scala/org/apache/mxnet/module/DataParallelExecutorGroup.scala
index 1494dc84035..5c567fe5d53 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/module/DataParallelExecutorGroup.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/module/DataParallelExecutorGroup.scala
@@ -101,10 +101,10 @@ private object DataParallelExecutorGroup {
gradReq: String, argNames: IndexedSeq[String], paramNames: IndexedSeq[String],
fixedParamNames: Set[String], dataNames: Seq[String], inputsNeedGrad: Boolean)
: Map[String, String] = {
- require(argNames != null)
- require(paramNames != null)
- require(fixedParamNames != null)
- require(dataNames != null)
+ require(argNames != null, "Invalid argNames")
+ require(paramNames != null, "Invalid paramNames")
+ require(fixedParamNames != null, "Invalid fixedParamNames")
+ require(dataNames != null, "Invalid dataNames")
argNames.map(k => {
if (paramNames.contains(k)) {
(k, if (fixedParamNames.contains(k)) "null" else gradReq)
@@ -139,13 +139,13 @@ private object DataParallelExecutorGroup {
}
def setDataShapes(shapes: IndexedSeq[DataDesc]): Builder = {
- require(shapes != null)
+ require(shapes != null, "Invalid shapes")
this.dataShapes = shapes
this
}
def setDataShapesByName(shapes: IndexedSeq[(String, Shape)]): Builder = {
- require(shapes != null)
+ require(shapes != null, "Invalid shapes")
this.dataShapes = shapes.map { case (k, s) => new DataDesc(k, s) }
this
}
@@ -188,7 +188,7 @@ private object DataParallelExecutorGroup {
}
def setGradReq(gradReq: Map[String, String]): Builder = {
- require(dataShapes != null)
+ require(dataShapes != null, "dataShapes must be set first")
val gradReqTmp = mutable.HashMap.empty[String, String]
val dataNames = dataShapes.map(_.name)
for (k <- argNames) {
@@ -206,7 +206,7 @@ private object DataParallelExecutorGroup {
}
def setGradReq(gradReq: String): Builder = {
- require(dataShapes != null)
+ require(dataShapes != null, "dataShapes must be set first")
val dataNames = dataShapes.map(_.name)
this.gradReqs = Builder.convertGradReq(
gradReq, argNames, paramNames, fixedParamNames, dataNames, inputsNeedGrad)
@@ -214,7 +214,9 @@ private object DataParallelExecutorGroup {
}
def setGradReq(gradReq: Seq[(String, String)]): Builder = {
- require(gradReq.size == argNames.size)
+ require(gradReq.size == argNames.size,
+ s"provided number of gradReq (${gradReq.size}) do not match number of args " +
+ s"(${argNames.size})")
this.gradReqs = gradReq.toMap
this
}
@@ -276,8 +278,8 @@ class DataParallelExecutorGroup private[module](
fixedParamNames: Set[String] = Set.empty[String],
gradReq: Map[String, String] = null) {
- require(symbol != null)
- require(contexts != null)
+ require(symbol != null, "Undefined symbol")
+ require(contexts != null, "Undefined context")
private val argNames = symbol.listArguments()
private val auxNames = symbol.listAuxiliaryStates()
@@ -329,7 +331,7 @@ class DataParallelExecutorGroup private[module](
* the shapes for the input data or label.
*/
private def decideSlices(dataShapes: Seq[DataDesc]): Seq[Int] = {
- require(dataShapes.size > 0)
+ require(dataShapes.size > 0, "dataShapes must be non empty")
val majorAxis = dataShapes.map(data => DataDesc.getBatchAxis(Option(data.layout)))
for ((dataDesc, axis) <- dataShapes.zip(majorAxis)) {
@@ -341,7 +343,7 @@ class DataParallelExecutorGroup private[module](
s"but ${dataDesc.name} has shape ${dataDesc.shape}")
} else {
this.batchSize = batchSize
- require(this.workLoadList != null)
+ require(this.workLoadList != null, "Undefined workLoadList")
this.slices = ExecutorManager.splitInputSlice(this.batchSize, this.workLoadList)
}
}
@@ -489,9 +491,9 @@ class DataParallelExecutorGroup private[module](
DataParallelExecutorGroup.loadData(dataBatch, dataArrays, dataLayouts)
val isTrainOpt = isTrain.getOrElse(this.forTraining)
labelArrays.foreach(labels => {
- require(!isTrainOpt || dataBatch.label != null)
+ require(!isTrainOpt || dataBatch.label != null, "label must be defined if in training phase")
if (dataBatch.label != null) {
- require(labelLayouts != null)
+ require(labelLayouts != null, "label layouts are undefined")
DataParallelExecutorGroup.loadLabel(dataBatch, labels, labelLayouts)
}
})
@@ -541,7 +543,7 @@ class DataParallelExecutorGroup private[module](
* those `NDArray` might live on different devices.
*/
def getInputGrads(): IndexedSeq[IndexedSeq[NDArray]] = {
- require(inputsNeedGrad)
+ require(inputsNeedGrad, "Cannot get InputGrads when inputNeedGrad is set to false")
inputGradArrays.map(_.toIndexedSeq)
}
@@ -632,13 +634,17 @@ class DataParallelExecutorGroup private[module](
= dataShapesSliced.toMap ++ labelShapesSliced.getOrElse(Map.empty[String, Shape])
val (argShapes, _, auxShapes) = symbol.inferShape(inputShapes)
- require(argShapes != null, "shape inference failed")
+ require(argShapes != null, "Shape inference failed." +
+ s"Known shapes are $inputShapes for symbol arguments ${symbol.listArguments()} " +
+ s"and aux states ${symbol.listAuxiliaryStates()}")
val inputTypesGot = inputTypes.getOrElse(inputShapes.map { case (k, v) =>
(k, Base.MX_REAL_TYPE)
})
val (argTypes, _, auxTypes) = symbol.inferType(inputTypesGot)
- require(argTypes != null, "type inference failed")
+ require(argTypes != null, "Type inference failed." +
+ s"Known types as $inputTypes for symbol arguments ${symbol.listArguments()} " +
+ s"and aux states ${symbol.listAuxiliaryStates()}")
val argArrays = ArrayBuffer.empty[NDArray]
val gradArrayMap = mutable.HashMap.empty[String, NDArray]
@@ -659,8 +665,12 @@ class DataParallelExecutorGroup private[module](
argArr
case Some(sharedExecInst) =>
val argArr = sharedExecInst.argDict(name)
- require(argArr.shape == argShapes(j))
- require(argArr.dtype == argTypes(j))
+ require(argArr.shape == argShapes(j),
+ s"Shape ${argArr.shape} of argument $name does not match " +
+ s"inferred shape ${argShapes(j)}")
+ require(argArr.dtype == argTypes(j),
+ s"Type ${argArr.dtype} of argument $name does not match " +
+ s"inferred type ${argTypes(j)}")
if (gradReqRun(name) != "null") {
gradArrayMap.put(name, sharedExecInst.gradDict(name))
}
@@ -687,8 +697,12 @@ class DataParallelExecutorGroup private[module](
}.toArray
case Some(sharedExecInst) =>
for ((arr, j) <- sharedExecInst.auxArrays.zipWithIndex) {
- require(auxShapes(j) == arr.shape)
- require(auxTypes(j) == arr.dtype)
+ require(auxShapes(j) == arr.shape,
+ s"Shape ${arr.shape} of aux variable ${auxNames(j)} does not match " +
+ s"inferred shape ${auxShapes(j)}")
+ require(auxTypes(j) == arr.dtype,
+ s"Type ${arr.dtype} of aux variable ${auxNames(j)} does not match " +
+ s"inferred type ${auxTypes(j)}")
}
sharedExecInst.auxArrays.map(identity)
}
@@ -729,7 +743,8 @@ class DataParallelExecutorGroup private[module](
val argArr = sharedDataArrays(name)
if (argArr.shape.product >= argShape.product) {
// nice, we can directly re-use this data blob
- require(argArr.dtype == argType)
+ require(argArr.dtype == argType,
+ s"Type ${argArr.dtype} of argument $name does not match infered type ${argType}")
argArr.reshape(argShape)
} else {
DataParallelExecutorGroup.logger.warn(s"bucketing: data $name has a shape $argShape," +
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/module/Module.scala b/scala-package/core/src/main/scala/org/apache/mxnet/module/Module.scala
index 9cf64b19a6a..fec1ba0dc35 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/module/Module.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/module/Module.scala
@@ -45,11 +45,12 @@ class Module(symbolVar: Symbol,
fixedParamNames: Option[Set[String]] = None) extends BaseModule {
private val logger = LoggerFactory.getLogger(classOf[Module])
- require(symbolVar != null)
+ require(symbolVar != null, "Undefined symbol")
this.symbol = symbolVar
private val workLoads = workLoadList.getOrElse(contexts.map(_ => 1f).toIndexedSeq)
- require(workLoads.size == contexts.length)
+ require(workLoads.size == contexts.length,
+ s"workloads size (${workLoads.size}) do not match number of contexts ${contexts.length}")
private val labelNameList = if (labelNames == null) IndexedSeq.empty[String] else labelNames
@@ -71,17 +72,17 @@ class Module(symbolVar: Symbol,
private var labelShapesVar: Option[IndexedSeq[DataDesc]] = None
override def dataShapes: IndexedSeq[DataDesc] = {
- require(binded)
+ require(binded, "bind() must be called first.")
dataShapesVar
}
override def labelShapes: IndexedSeq[DataDesc] = {
- require(binded)
+ require(binded, "bind() must be called first.")
labelShapesVar.orNull
}
override def outputShapes: IndexedSeq[(String, Shape)] = {
- require(binded)
+ require(binded, "bind() must be called first.")
execGroup.getOutputShapes
}
@@ -93,7 +94,7 @@ class Module(symbolVar: Symbol,
* `NDArray`) mapping.
*/
override def getParams: (Map[String, NDArray], Map[String, NDArray]) = {
- require(binded && paramsInitialized)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
if (paramsDirty) {
syncParamsFromDevices()
}
@@ -253,7 +254,7 @@ class Module(symbolVar: Symbol,
this.binded = true
if (!forTraining) {
- require(!inputsNeedGrad)
+ require(!inputsNeedGrad, "Invalid inputsNeedGrad (cannot be true if not forTraining)")
} else {
// this is not True, as some module might not contains a loss function
// that consumes the labels
@@ -265,7 +266,8 @@ class Module(symbolVar: Symbol,
val sharedGroup =
sharedModule.map(sharedModuleInst => {
- require(sharedModuleInst.binded && sharedModuleInst.paramsInitialized)
+ require(sharedModuleInst.binded && sharedModuleInst.paramsInitialized,
+ s"bind() and initParams() must be called first on shared module.")
sharedModuleInst.execGroup
})
@@ -338,7 +340,7 @@ class Module(symbolVar: Symbol,
*/
def reshape(dataShapes: IndexedSeq[DataDesc],
labelShapes: Option[IndexedSeq[DataDesc]] = None): Unit = {
- require(this.binded)
+ require(this.binded, "bind() must be called first.")
val (tdataShapes, tlabelShapes) = this._parseDataDesc(
this.dataNames, this.labelNames, dataShapes, labelShapes)
this.dataShapesVar = tdataShapes
@@ -357,7 +359,7 @@ class Module(symbolVar: Symbol,
*/
def initOptimizer(kvstore: String = "local", optimizer: Optimizer = new SGD(),
resetOptimizer: Boolean = true, forceInit: Boolean = false): Unit = {
- require(binded && paramsInitialized)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
if (optimizerInitialized && !forceInit) {
logger.warn("optimizer already initialized, ignoring ...")
} else {
@@ -414,7 +416,8 @@ class Module(symbolVar: Symbol,
* @param sharedModule
*/
def borrowOptimizer(sharedModule: Module): Unit = {
- require(sharedModule.optimizerInitialized)
+ require(sharedModule.optimizerInitialized,
+ "initOptimizer() must be called first for shared module")
optimizer = sharedModule.optimizer
kvstore = sharedModule.kvstore
updateOnKVStore = sharedModule.updateOnKVStore
@@ -428,7 +431,7 @@ class Module(symbolVar: Symbol,
* @param isTrain Default is `None`, which means `is_train` takes the value of `for_training`.
*/
def forward(dataBatch: DataBatch, isTrain: Option[Boolean] = None): Unit = {
- require(binded && paramsInitialized)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
val currDataShapes = this.dataShapes.map(_.shape)
val newDataShapes = dataBatch.data.map(_.shape)
if (currDataShapes != newDataShapes) {
@@ -459,20 +462,21 @@ class Module(symbolVar: Symbol,
* on outputs that are not a loss function.
*/
def backward(outGrads: Array[NDArray] = null): Unit = {
- require(binded && paramsInitialized)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
execGroup.backward(outGrads)
}
// Update parameters according to the installed optimizer and the gradients computed
// in the previous forward-backward batch.
def update(): Unit = {
- require(binded && paramsInitialized && optimizerInitialized)
+ require(binded && paramsInitialized && optimizerInitialized,
+ "bind(), initParams() and initOptimizer() must be called first.")
paramsDirty = true
if (updateOnKVStore) {
Model.updateParamsOnKVStore(execGroup.paramArrays,
execGroup.gradArrays, kvstore, execGroup.paramNames)
} else {
- require(updater != None)
+ require(updater.isDefined, "Undefined updater")
Model.updateParams(execGroup.paramArrays,
execGroup.gradArrays, updater.orNull, contexts.length, execGroup.paramNames, kvstore)
}
@@ -486,7 +490,7 @@ class Module(symbolVar: Symbol,
* those `NDArray` might live on different devices.
*/
def getOutputs(): IndexedSeq[IndexedSeq[NDArray]] = {
- require(binded && paramsInitialized)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
execGroup.getOutputs()
}
@@ -498,7 +502,7 @@ class Module(symbolVar: Symbol,
* The results will look like `[out1, out2]`
*/
def getOutputsMerged(): IndexedSeq[NDArray] = {
- require(binded && paramsInitialized)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
execGroup.getOutputsMerged()
}
@@ -510,7 +514,8 @@ class Module(symbolVar: Symbol,
* those `NDArray` might live on different devices.
*/
def getInputGrads(): IndexedSeq[IndexedSeq[NDArray]] = {
- require(binded && paramsInitialized && inputsNeedGrad)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
+ require(inputsNeedGrad, "Call to getInputGrads() but inputsNeedGrad is false")
execGroup.getInputGrads()
}
@@ -522,7 +527,8 @@ class Module(symbolVar: Symbol,
* The results will look like `[grad1, grad2]`
*/
def getInputGradsMerged(): IndexedSeq[NDArray] = {
- require(binded && paramsInitialized && inputsNeedGrad)
+ require(binded && paramsInitialized, "bind() and initParams() must be called first.")
+ require(inputsNeedGrad, "Call to getInputGradsMerged() but inputsNeedGrad is false")
execGroup.getInputGradsMerged()
}
@@ -544,7 +550,7 @@ class Module(symbolVar: Symbol,
// Install monitor on all executors
def installMonitor(monitor: Monitor): Unit = {
- require(binded)
+ require(binded, "bind() must be called first.")
execGroup.installMonitor(monitor)
}
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/module/SequentialModule.scala b/scala-package/core/src/main/scala/org/apache/mxnet/module/SequentialModule.scala
index f376b54dc29..e75550a1d1f 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/module/SequentialModule.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/module/SequentialModule.scala
@@ -96,7 +96,7 @@ class SequentialModule extends BaseModule {
* @return The data shapes of the first module is the data shape of a SequentialModule.
*/
override def dataShapes: IndexedSeq[DataDesc] = {
- require(this.binded)
+ require(this.binded, "bind() must be called first.")
this.modules.head.dataShapes
}
@@ -107,7 +107,7 @@ class SequentialModule extends BaseModule {
* training (in this case, label information is not available).
*/
override def labelShapes: IndexedSeq[DataDesc] = {
- require(this.binded)
+ require(this.binded, "bind() must be called first.")
this.labelShapesVar.orNull
}
@@ -117,7 +117,7 @@ class SequentialModule extends BaseModule {
* module is the output shape of a SequentialModule.
*/
override def outputShapes: IndexedSeq[(String, Shape)] = {
- require(this.binded)
+ require(this.binded, "bind() must be called first.")
this.modules.reverse.head.outputShapes
}
@@ -127,7 +127,7 @@ class SequentialModule extends BaseModule {
* each a Map of name to parameters (in NDArray) mapping.
*/
override def getParams: (Map[String, NDArray], Map[String, NDArray]) = {
- require(this.binded && this.paramsInitialized)
+ require(this.binded && this.paramsInitialized, "bind() and initParams() must be called first.")
((Map[String, NDArray](), Map[String, NDArray]()) /: this.modules){ (result, module) =>
val (arg, aux) = module.getParams
(result._1 ++ arg, result._2 ++ aux)
@@ -220,7 +220,7 @@ class SequentialModule extends BaseModule {
}
if (inputsNeedGrad) {
- require(forTraining == true)
+ require(forTraining, "inputsNeedGrad can be set only for training")
}
require(sharedModule == None, "Shared module is not supported")
@@ -246,7 +246,8 @@ class SequentialModule extends BaseModule {
val myInputsNeedGrad = if (inputsNeedGrad || (forTraining && iLayer > 0)) true else false
if (meta.contains(META_AUTO_WIRING) && meta(META_AUTO_WIRING)) {
val dataNames = module.dataNames
- require(dataNames.length == myDataShapes.length)
+ require(dataNames.length == myDataShapes.length,
+ s"dataNmes $dataNames and dataShapes $myDataShapes do not match")
myDataShapes = dataNames.zip(myDataShapes).map { case (newName, dataDes) =>
DataDesc(newName, dataDes.shape)
}
@@ -276,7 +277,7 @@ class SequentialModule extends BaseModule {
*/
override def initOptimizer(kvstore: String = "local", optimizer: Optimizer = new SGD(),
resetOptimizer: Boolean = true, forceInit: Boolean = false): Unit = {
- require(this.binded && this.paramsInitialized)
+ require(this.binded && this.paramsInitialized, "bind() and initParams() must be called first.")
if (optimizerInitialized && !forceInit) {
logger.warn("optimizer already initialized, ignoring ...")
} else {
@@ -293,7 +294,7 @@ class SequentialModule extends BaseModule {
* @param isTrain Default is `None`, which means `isTrain` takes the value of `forTraining`.
*/
override def forward(dataBatch: DataBatch, isTrain: Option[Boolean] = None): Unit = {
- require(this.binded && this.paramsInitialized)
+ require(this.binded && this.paramsInitialized, "bind() and initParams() must be called first.")
var data = dataBatch
for ((module, iLayer) <- this.modules.zipWithIndex) {
@@ -304,7 +305,8 @@ class SequentialModule extends BaseModule {
// need to update this, in case the internal module is using bucketing
// or whatever
val dataNames = module.outputShapes.map(_._1)
- require(dataNames.length == data.data.length)
+ require(dataNames.length == data.data.length,
+ s"dataNames $dataNames do not match with number of arrays in batch")
var provideData = ListMap[String, Shape]()
for ((name, x) <- dataNames.zip(out.head)) {
provideData += name -> x.shape
@@ -322,7 +324,7 @@ class SequentialModule extends BaseModule {
* on outputs that are not a loss function.
*/
override def backward(outGrads: Array[NDArray] = null): Unit = {
- require(this.binded && this.paramsInitialized)
+ require(this.binded && this.paramsInitialized, "bind() and initParams() must be called first.")
var grad = outGrads
for ((module, iLayer) <- this.modules.zipWithIndex.reverse) {
module.backward(outGrads = grad)
@@ -335,7 +337,8 @@ class SequentialModule extends BaseModule {
// Update parameters according to the installed optimizer and the gradients computed
// in the previous forward-backward batch.
override def update(): Unit = {
- require(this.binded && this.paramsInitialized && this.optimizerInitialized)
+ require(this.binded && this.paramsInitialized && this.optimizerInitialized,
+ "bind(), initParams() and initOptimizer() must be called first.")
this.modules.foreach(_.update())
}
@@ -347,7 +350,7 @@ class SequentialModule extends BaseModule {
* those `NDArray` might live on different devices.
*/
def getOutputs(): IndexedSeq[IndexedSeq[NDArray]] = {
- require(this.binded && this.paramsInitialized)
+ require(this.binded && this.paramsInitialized, "bind() and initParams() must be called first.")
this.modules.reverse.head.getOutputs()
}
@@ -359,7 +362,7 @@ class SequentialModule extends BaseModule {
* The results will look like `[out1, out2]`
*/
def getOutputsMerged(): IndexedSeq[NDArray] = {
- require(this.binded && this.paramsInitialized)
+ require(this.binded && this.paramsInitialized, "bind() and initParams() must be called first.")
this.modules.reverse.head.getOutputsMerged()
}
@@ -371,7 +374,8 @@ class SequentialModule extends BaseModule {
* those `NDArray` might live on different devices.
*/
def getInputGrads(): IndexedSeq[IndexedSeq[NDArray]] = {
- require(this.binded && this.paramsInitialized && inputsNeedGrad)
+ require(this.binded && this.paramsInitialized, "bind() and initParams() must be called first.")
+ require(inputsNeedGrad, "Call to getInputGrads() but inputsNeedGrad is false")
this.modules.head.getInputGrads()
}
@@ -383,7 +387,8 @@ class SequentialModule extends BaseModule {
* The results will look like `[grad1, grad2]`
*/
def getInputGradsMerged(): IndexedSeq[NDArray] = {
- require(this.binded && this.paramsInitialized && inputsNeedGrad)
+ require(this.binded && this.paramsInitialized, "bind() and initParams() must be called first.")
+ require(inputsNeedGrad, "Call to getInputGradsMerged() but inputsNeedGrad is false")
this.modules.head.getInputGradsMerged()
}
@@ -393,7 +398,7 @@ class SequentialModule extends BaseModule {
* @param labels
*/
def updateMetric(evalMetric: EvalMetric, labels: IndexedSeq[NDArray]): Unit = {
- require(this.binded && this.paramsInitialized)
+ require(this.binded && this.paramsInitialized, "bind() and initParams() must be called first.")
for ((meta, module) <- this.metas.zip(this.modules)) {
if (meta.contains(META_TAKE_LABELS) && meta(META_TAKE_LABELS)) {
module.updateMetric(evalMetric, labels)
@@ -403,7 +408,7 @@ class SequentialModule extends BaseModule {
// Install monitor on all executors
def installMonitor(monitor: Monitor): Unit = {
- require(this.binded)
+ require(this.binded, "bind() must be called first.")
this.modules.foreach(_.installMonitor(monitor))
}
}
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/optimizer/DCASGD.scala b/scala-package/core/src/main/scala/org/apache/mxnet/optimizer/DCASGD.scala
index 6b5053b74a0..af804a58011 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/optimizer/DCASGD.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/optimizer/DCASGD.scala
@@ -71,7 +71,8 @@ class DCASGD(val learningRate: Float = 0.01f, momentum: Float = 0.0f,
mon *= this.momentum
mon += monUpdated
} else {
- require(this.momentum == 0)
+ require(this.momentum == 0f,
+ s"momentum should be zero when state is provided.")
mon = monUpdated
}
previousWeight.set(weight)
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/optimizer/NAG.scala b/scala-package/core/src/main/scala/org/apache/mxnet/optimizer/NAG.scala
index 47fe62d17f4..5ed89548ebd 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/optimizer/NAG.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/optimizer/NAG.scala
@@ -76,7 +76,8 @@ class NAG(val learningRate: Float = 0.01f, momentum: Float = 0.0f,
resdGrad += momentum * mom
weight += -lr * resdGrad
} else {
- require(momentum == 0f)
+ require(momentum == 0f,
+ s"momentum should be zero when state is provided.")
// adder = -lr * (resdGrad + this.wd * weight)
// we write in this way to get rid of memory leak
val adder = this.wd * weight
diff --git a/scala-package/core/src/main/scala/org/apache/mxnet/optimizer/SGD.scala b/scala-package/core/src/main/scala/org/apache/mxnet/optimizer/SGD.scala
index e228e7273d8..e20b433ed1e 100644
--- a/scala-package/core/src/main/scala/org/apache/mxnet/optimizer/SGD.scala
+++ b/scala-package/core/src/main/scala/org/apache/mxnet/optimizer/SGD.scala
@@ -73,7 +73,8 @@ class SGD(val learningRate: Float = 0.01f, momentum: Float = 0.0f,
weight += mom
adder.dispose()
} else {
- require(momentum == 0f)
+ require(momentum == 0f,
+ s"momentum should be zero when state is provided.")
// adder = -lr * (resdGrad + this.wd * weight)
// we write in this way to get rid of memory leak
val adder = this.wd * weight
diff --git a/scala-package/infer/src/main/scala/org/apache/mxnet/infer/Classifier.scala b/scala-package/infer/src/main/scala/org/apache/mxnet/infer/Classifier.scala
index aef44681ac6..adeb33d34a9 100644
--- a/scala-package/infer/src/main/scala/org/apache/mxnet/infer/Classifier.scala
+++ b/scala-package/infer/src/main/scala/org/apache/mxnet/infer/Classifier.scala
@@ -146,11 +146,11 @@ class Classifier(modelPathPrefix: String,
private[infer] def getSynsetFilePath(modelPathPrefix: String): String = {
val dirPath = modelPathPrefix.substring(0, 1 + modelPathPrefix.lastIndexOf(File.separator))
val d = new File(dirPath)
- require(d.exists && d.isDirectory, "directory: %s not found".format(dirPath))
+ require(d.exists && d.isDirectory, s"directory: $dirPath not found")
val s = new File(dirPath + "synset.txt")
- require(s.exists() && s.isFile, "File synset.txt should exist inside modelPath: %s".format
- (dirPath + "synset.txt"))
+ require(s.exists() && s.isFile,
+ s"File synset.txt should exist inside modelPath: ${dirPath + "synset.txt"}")
s.getCanonicalPath
}
diff --git a/scala-package/infer/src/main/scala/org/apache/mxnet/infer/MXNetHandler.scala b/scala-package/infer/src/main/scala/org/apache/mxnet/infer/MXNetHandler.scala
index 003804581c6..d2bed3aa9d8 100644
--- a/scala-package/infer/src/main/scala/org/apache/mxnet/infer/MXNetHandler.scala
+++ b/scala-package/infer/src/main/scala/org/apache/mxnet/infer/MXNetHandler.scala
@@ -39,8 +39,7 @@ private[infer] object MXNetHandlerType extends Enumeration {
private[infer] class MXNetThreadPoolHandler(numThreads: Int = 1)
extends MXNetHandler {
- require(numThreads > 0, "numThreads should be a positive number, you passed:%d".
- format(numThreads))
+ require(numThreads > 0, s"Invalid numThreads $numThreads")
private val logger = LoggerFactory.getLogger(classOf[MXNetThreadPoolHandler])
private var threadCount: Int = 0
diff --git a/scala-package/infer/src/main/scala/org/apache/mxnet/infer/Predictor.scala b/scala-package/infer/src/main/scala/org/apache/mxnet/infer/Predictor.scala
index 2a4f0305637..3987c648b2a 100644
--- a/scala-package/infer/src/main/scala/org/apache/mxnet/infer/Predictor.scala
+++ b/scala-package/infer/src/main/scala/org/apache/mxnet/infer/Predictor.scala
@@ -113,13 +113,14 @@ class Predictor(modelPathPrefix: String,
override def predict(input: IndexedSeq[Array[Float]])
: IndexedSeq[Array[Float]] = {
- require(input.length == inputDescriptors.length, "number of inputs provided: %d" +
- " does not match number of inputs in inputDescriptors: %d".format(input.length,
- inputDescriptors.length))
+ require(input.length == inputDescriptors.length,
+ s"number of inputs provided: ${input.length} does not match number of inputs " +
+ s"in inputDescriptors: ${inputDescriptors.length}")
for((i, d) <- input.zip(inputDescriptors)) {
- require (i.length == d.shape.product/batchSize, "number of elements:" +
- " %d in the input does not match the shape:%s".format( i.length, d.shape.toString()))
+ require(i.length == d.shape.product / batchSize,
+ s"number of elements:${i.length} in the input does not match the shape:" +
+ s"${d.shape.toString()}")
}
var inputND: ListBuffer[NDArray] = ListBuffer.empty[NDArray]
@@ -163,17 +164,17 @@ class Predictor(modelPathPrefix: String,
*/
override def predictWithNDArray(inputBatch: IndexedSeq[NDArray]): IndexedSeq[NDArray] = {
- require(inputBatch.length == inputDescriptors.length, "number of inputs provided: %d" +
- " do not match number of inputs in inputDescriptors: %d".format(inputBatch.length,
- inputDescriptors.length))
+ require(inputBatch.length == inputDescriptors.length,
+ s"number of inputs provided: ${inputBatch.length} do not match number " +
+ s"of inputs in inputDescriptors: ${inputDescriptors.length}")
// Shape validation, remove this when backend throws better error messages.
for((i, d) <- inputBatch.zip(iDescriptors)) {
require(inputBatch(0).shape(batchIndex) == i.shape(batchIndex),
"All inputs should be of same batch size")
require(i.shape.drop(batchIndex + 1) == d.shape.drop(batchIndex + 1),
- "Input Data Shape: %s should match the inputDescriptor shape: %s except batchSize".format(
- i.shape.toString, d.shape.toString))
+ s"Input Data Shape: ${i.shape} should match the inputDescriptor " +
+ s"shape: ${d.shape} except batchSize")
}
val inputBatchSize = inputBatch(0).shape(batchIndex)
diff --git a/scala-package/macros/src/main/scala/org/apache/mxnet/utils/CToScalaUtils.scala b/scala-package/macros/src/main/scala/org/apache/mxnet/utils/CToScalaUtils.scala
index b07e6f97eee..d0ebe5b1d2c 100644
--- a/scala-package/macros/src/main/scala/org/apache/mxnet/utils/CToScalaUtils.scala
+++ b/scala-package/macros/src/main/scala/org/apache/mxnet/utils/CToScalaUtils.scala
@@ -67,8 +67,10 @@ private[mxnet] object CToScalaUtils {
// Optional Field
if (commaRemoved.length >= 3) {
// arg: Type, optional, default = Null
- require(commaRemoved(1).equals("optional"))
- require(commaRemoved(2).startsWith("default="))
+ require(commaRemoved(1).equals("optional"),
+ s"""expected "optional" got ${commaRemoved(1)}""")
+ require(commaRemoved(2).startsWith("default="),
+ s"""expected "default=..." got ${commaRemoved(2)}""")
(typeConversion(commaRemoved(0), argType, argName, returnType), true)
} else if (commaRemoved.length == 2 || commaRemoved.length == 1) {
val tempType = typeConversion(commaRemoved(0), argType, argName, returnType)
diff --git a/scala-package/spark/src/main/scala/org/apache/mxnet/spark/MXNDArray.scala b/scala-package/spark/src/main/scala/org/apache/mxnet/spark/MXNDArray.scala
index da078fc4060..a18c47d7874 100644
--- a/scala-package/spark/src/main/scala/org/apache/mxnet/spark/MXNDArray.scala
+++ b/scala-package/spark/src/main/scala/org/apache/mxnet/spark/MXNDArray.scala
@@ -24,7 +24,7 @@ import org.apache.mxnet.NDArray
* @author Yizhi Liu
*/
class MXNDArray(@transient private var ndArray: NDArray) extends Serializable {
- require(ndArray != null)
+ require(ndArray != null, "Undefined ndArray")
private val arrayBytes: Array[Byte] = ndArray.serialize()
def get: NDArray = {
diff --git a/scala-package/spark/src/main/scala/org/apache/mxnet/spark/MXNetModel.scala b/scala-package/spark/src/main/scala/org/apache/mxnet/spark/MXNetModel.scala
index 2ecc2c88905..2c4c8fe4278 100644
--- a/scala-package/spark/src/main/scala/org/apache/mxnet/spark/MXNetModel.scala
+++ b/scala-package/spark/src/main/scala/org/apache/mxnet/spark/MXNetModel.scala
@@ -32,9 +32,9 @@ class MXNetModel private[mxnet](
private val batchSize: Int,
private val dataName: String = "data",
private val labelName: String = "label") extends Serializable {
- require(model != null, "try to serialize an empty FeedForward model")
- require(dimension != null, "unknown dimension")
- require(batchSize > 0, s"invalid batchSize: $batchSize")
+ require(model != null, "Undefined model")
+ require(dimension != null, "Undefined dimension")
+ require(batchSize > 0, s"Invalid batchSize: $batchSize")
val serializedModel = model.serialize()
/**
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services