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The provided RNNEmbedding Example does not work, on 1.0.0-M2.1 release #10022

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nishisan opened this issue Aug 15, 2023 · 0 comments
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Issue Description

The provided RNNEmbedding Example does not work, on 1.0.0-M2.1 release
The provided example in dl4j-examples/src/main/java/org/deeplearning4j/examples/quickstart/modeling/recurrent/RNNEmbedding.java does not compile

Please describe your issue, along with:

  • expected behavior
    The example to compile and run
  • encountered behavior
    An Exception:
    Exception in thread "main" java.lang.IllegalStateException: Sequence lengths do not match for RnnOutputLayer input and labels:Arrays should be rank 3 with shape [minibatch, size, sequenceLength] - mismatch on dimension 2 (sequence length) - input=[3, 7, 8] vs. label=[3, 4, 8]
    at org.nd4j.common.base.Preconditions.throwStateEx(Preconditions.java:639)
    at org.nd4j.common.base.Preconditions.checkState(Preconditions.java:337)
    at org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer.backpropGradient(RnnOutputLayer.java:59)
    at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.calcBackpropGradients(MultiLayerNetwork.java:1998)
    at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.computeGradientAndScore(MultiLayerNetwork.java:2813)
    at com.osstelecom.ai.deeplearning.ai.api.AiApi.main(AiApi.java:60)

Version Information

Please indicate relevant versions, including, if relevant:

  • Deeplearning4j version:1.0.0-M2.1
  • platform information (OS, etc) Linux Ubuntu 22,04
  • CUDA version: No Used
  • NVIDIA driver version: Not Used

Contributing

If you'd like to help us fix the issue by contributing some code, but would
like guidance or help in doing so, please mention it!

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