[bug fix]max support one-element tensor indices

[qiuxin2012]

What changes were proposed in this pull request?

max support one-element tensor indices

or Max may throw exception:

java.lang.IllegalArgumentException: requirement failed: reduction indices should be a scalar
	at scala.Predef$.require(Predef.scala:224)
	at com.intel.analytics.bigdl.nn.ops.Max.updateOutput(Max.scala:46)
	at com.intel.analytics.bigdl.nn.ops.Max.updateOutput(Max.scala:32)
	at com.intel.analytics.bigdl.nn.abstractnn.AbstractModule.forward(AbstractModule.scala:257)
	at com.intel.analytics.bigdl.nn.DynamicGraph.updateOutput(DynamicGraph.scala:51)
	at com.intel.analytics.bigdl.nn.abstractnn.AbstractModule.forward(AbstractModule.scala:257)
	at com.intel.analytics.bigdl.optim.Predictor$$anonfun$predict$1$$anonfun$apply$3.apply(Predictor.scala:168)
	at com.intel.analytics.bigdl.optim.Predictor$$anonfun$predict$1$$anonfun$apply$3.apply(Predictor.scala:167)
	at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
	at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
	at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
	at org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.hasNext(SerDeUtil.scala:117)
	at scala.collection.Iterator$class.foreach(Iterator.scala:893)
	at org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.foreach(SerDeUtil.scala:112)
	at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:504)
	at org.apache.spark.api.python.PythonRunner$WriterThread$$anonfun$run$3.apply(PythonRDD.scala:328)
	at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1951)
	at org.apache.spark.api.python.PythonRunner$WriterThread.run(PythonRDD.scala:269)

	at com.intel.analytics.bigdl.nn.abstractnn.AbstractModule.forward(AbstractModule.scala:263)
	at com.intel.analytics.bigdl.nn.DynamicGraph.updateOutput(DynamicGraph.scala:51)
	at com.intel.analytics.bigdl.nn.abstractnn.AbstractModule.forward(AbstractModule.scala:257)
	at com.intel.analytics.bigdl.optim.Predictor$$anonfun$predict$1$$anonfun$apply$3.apply(Predictor.scala:168)
	at com.intel.analytics.bigdl.optim.Predictor$$anonfun$predict$1$$anonfun$apply$3.apply(Predictor.scala:167)
	at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
	at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
	at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
	at org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.hasNext(SerDeUtil.scala:117)
	at scala.collection.Iterator$class.foreach(Iterator.scala:893)
	at org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.foreach(SerDeUtil.scala:112)
	at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:504)
	at org.apache.spark.api.python.PythonRunner$WriterThread$$anonfun$run$3.apply(PythonRDD.scala:328)
	at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1951)
	at org.apache.spark.api.python.PythonRunner$WriterThread.run(PythonRDD.scala:269)

How was this patch tested?

(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If it is possible, please attach a screenshot; otherwise, remove this)

Related links or issues (optional)

fixed https://github.com/intel-analytics/BigDL/issues/XXX

[yiheng]

LGTM

[qiuxin2012]

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