lanking520 commented on a change in pull request #13330: [MXNET-1222] Scala
Inference enable different shapes input
URL: https://github.com/apache/incubator-mxnet/pull/13330#discussion_r237649512
##########
File path:
scala-package/infer/src/main/scala/org/apache/mxnet/infer/Predictor.scala
##########
@@ -172,18 +189,20 @@ class Predictor(modelPathPrefix: String,
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),
- s"Input Data Shape: ${i.shape} should match the inputDescriptor " +
- s"shape: ${d.shape} except batchSize")
+ if (!shapeCheckDisabled) {
+ require(i.shape.drop(batchIndex + 1) == d.shape.drop(batchIndex + 1),
+ s"Input Data Shape: ${i.shape} should match the inputDescriptor " +
+ s"shape: ${d.shape} except batchSize")
+ }
}
val inputBatchSize = inputBatch(0).shape(batchIndex)
// rebind with the new batchSize
if (batchSize != inputBatchSize) {
Review comment:
@nswamy After some tests, I found that the batch size cannot be changed:
```
- Test Predictor With Different Batch size *** FAILED ***
java.lang.AssertionError: Shape of unspecified array arg:softmax_label
changed.This can cause the new executor to not share parameters with the old
one. Please check for error in network.If this is intended, set partialShaping
= true to suppress this warning.
at org.apache.mxnet.Executor$$anonfun$reshape$2.apply(Executor.scala:120)
at org.apache.mxnet.Executor$$anonfun$reshape$2.apply(Executor.scala:98)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.mxnet.Executor.reshape(Executor.scala:98)
at
org.apache.mxnet.module.DataParallelExecutorGroup$$anonfun$bindExec$1.apply$mcVI$sp(DataParallelExecutorGroup.scala:376)
at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:160)
at
org.apache.mxnet.module.DataParallelExecutorGroup.bindExec(DataParallelExecutorGroup.scala:371)
at
org.apache.mxnet.module.DataParallelExecutorGroup.reshape(DataParallelExecutorGroup.scala:440)
at org.apache.mxnet.module.Module.reshape(Module.scala:348)
at org.apache.mxnet.module.Module.forward(Module.scala:453)
at org.apache.mxnet.module.BaseModule.predict(BaseModule.scala:238)
at
org.apache.mxnet.module.BaseModule.predictEveryBatch(BaseModule.scala:228)
at org.apache.mxnet.module.BaseModule.predict(BaseModule.scala:259)
at org.apache.mxnet.infer.Predictor$$anonfun$11.apply(Predictor.scala:213)
at org.apache.mxnet.infer.Predictor$$anonfun$11.apply(Predictor.scala:213)
at
org.apache.mxnet.infer.MXNetThreadPoolHandler$$anon$4.call(MXNetHandler.scala:73)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
```
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