Оболочка Spark Apache для Di git Recognizer вызывает исключение

Question

Я следовал инструкциям в этом руководстве (https://towardsdatascience.com/how-to-train-your-neural-networks-in-parallel-with-keras-and-apache-spark-ea8a3f48cae6), чтобы приступить к расширению моей модели глубокого обучения.

Однако, когда я попытался выполнить метод подгонки, это произошло исключение:

Traceback (most recent call last):
  File "/home/Projects/KLA/thong/Project/venv_py2/lib/python2.7/site-packages/systemml/mllearn/estimators.py", line 176, in _fit_numpy
    self.model = self.estimator.fit(convertToMatrixBlock(self.sc, self.X), y_mb)
  File "/home/Projects/KLA/thong/Project/venv_py2/lib/python2.7/site-packages/py4j/java_gateway.py", line 1257, in __call__
    answer, self.gateway_client, self.target_id, self.name)
  File "/home/Projects/KLA/thong/Project/venv_py2/lib/python2.7/site-packages/pyspark/sql/utils.py", line 63, in deco
    return f(*a, **kw)
  File "/home/Projects/KLA/thong/Project/venv_py2/lib/python2.7/site-packages/py4j/protocol.py", line 328, in get_return_value
    format(target_id, ".", name), value)
Py4JJavaError: An error occurred while calling o103.fit.
: org.apache.sysml.parser.LanguageException: Layer with name label not found
    at org.apache.sysml.api.dl.CaffeNetwork.throwException(CaffeNetwork.scala:208)
    at org.apache.sysml.api.dl.CaffeNetwork.getCaffeLayer(CaffeNetwork.scala:215)
    at org.apache.sysml.api.dl.SoftmaxWithLoss$$anonfun$12.apply(CaffeLayer.scala:574)
    at org.apache.sysml.api.dl.SoftmaxWithLoss$$anonfun$12.apply(CaffeLayer.scala:574)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.immutable.Set$Set2.foreach(Set.scala:128)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
    at scala.collection.AbstractSet.scala$collection$SetLike$$super$map(Set.scala:47)
    at scala.collection.SetLike$class.map(SetLike.scala:92)
    at scala.collection.AbstractSet.map(Set.scala:47)
    at org.apache.sysml.api.dl.SoftmaxWithLoss.bottomLayerOutputShape(CaffeLayer.scala:574)
    at org.apache.sysml.api.dl.CaffeLayer$class.outputShape(CaffeLayer.scala:42)
    at org.apache.sysml.api.dl.SoftmaxWithLoss.outputShape(CaffeLayer.scala:534)
    at org.apache.sysml.api.dl.IsLossLayer$class.isSegmentationProblem(CaffeLayer.scala:167)
    at org.apache.sysml.api.dl.SoftmaxWithLoss.isSegmentationProblem(CaffeLayer.scala:534)
    at org.apache.sysml.api.dl.SoftmaxWithLoss.sourceFileName(CaffeLayer.scala:536)
    at org.apache.sysml.api.dl.SourceDMLGenerator$$anonfun$source$2.apply(DMLGenerator.scala:168)
    at org.apache.sysml.api.dl.SourceDMLGenerator$$anonfun$source$2.apply(DMLGenerator.scala:168)
    at scala.collection.immutable.List.map(List.scala:288)
    at org.apache.sysml.api.dl.SourceDMLGenerator$class.source(DMLGenerator.scala:168)
    at org.apache.sysml.api.dl.Caffe2DML.source(Caffe2DML.scala:164)
    at org.apache.sysml.api.dl.DMLGenerator$class.source(DMLGenerator.scala:212)
    at org.apache.sysml.api.dl.Caffe2DML.source(Caffe2DML.scala:164)
    at org.apache.sysml.api.dl.DMLGenerator$class.appendHeaders(DMLGenerator.scala:280)
    at org.apache.sysml.api.dl.Caffe2DML.appendHeaders(Caffe2DML.scala:164)
    at org.apache.sysml.api.dl.Caffe2DML.getTrainingScript(Caffe2DML.scala:318)
    at org.apache.sysml.api.ml.BaseSystemMLClassifier$class.baseFit(BaseSystemMLClassifier.scala:238)
    at org.apache.sysml.api.dl.Caffe2DML.baseFit(Caffe2DML.scala:164)
    at org.apache.sysml.api.dl.Caffe2DML.fit(Caffe2DML.scala:215)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:282)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:238)
    at java.lang.Thread.run(Thread.java:748)

Моя среда Python 2.7. Я пытался найти решение, но, похоже, нет источника, поднимающего тот же вопрос, что и мой.

Для получения дополнительной информации, когда я переключился на Python 3.6, код обнаружил еще одно исключение:

Py4JJavaError: An error occurred while calling None.org.apache.sysml.api.dl.Caffe2DML.
: com.google.protobuf.TextFormat$ParseException: 14:10: Couldn't parse integer: For input string: "2.5"

Они все кажутся мне чепухой, я был бы чрезвычайно признателен за любые советы !