# Questions for Time Series LSTM

**URL:** <https://community.konduit.ai/t/questions-for-time-series-lstm/171>\
**Category:** DL4J\
**Created:** [February 25, 2020, 6:59pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171 "2020-02-25T18:59:55Z")\
**Posts on this page:** 20\
**Page:** 1

<div class="post-metadata">

**Author:** ![Inqus](https://avatars.discourse-cdn.com/v4/letter/i/ee7513/32.png) [@Inqus](https://community.konduit.ai/u/Inqus)\
**Post date:** [February 25, 2020, 6:59pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/1 "2020-02-25T18:59:55Z")

</div>

#### Question

Hello, I wanted to ask a couple of questions. I retrieve my data from the database. And I did not find in the examples the correct way to convert Java arrays to DataSetIterators. Below is an example of a code with toy data (my data is also an integer format, so the example is correct).

1. How do I normalize my data? Below in the code there is a commented-out code, it converts only the input data, but the labels remain not converted.
2. I added a listener to the model but it does not work, tell me what could be the problem.
3. why can’t I evaluate test data without an iterator?
4. How can I set the batch size if I do not use a DataSeIterator?
5. Did I set the array shape for a recurrent neural network correctly? (split\_sequence() method)

thanks.

```
public class Forecast {

    public final static int BATCH_SIZE = 2; 
    public final static int RNG_SEED = 123; 
    public final static int TIME_STEPS = 3;
    public final static int nEpoch = 10;

    public static void main(String[] args) throws IOException, InterruptedException {

        int[] train = {10, 20, 30, 40, 50, 60, 70, 80, 90};
        int[] test = {70, 80, 90};

        DataSet dataSet = split_sequence(train, TIME_STEPS);
        DataSetIterator train_iterator = new ListDataSetIterator(Collections.singletonList(dataSet), BATCH_SIZE);

// NormalizerMinMaxScaler normalizer = new NormalizerMinMaxScaler(0, 1);
// normalizer.fit(dataSet);
// normalizer.transform(dataSet);

        MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
                .seed(RNG_SEED)
                .weightInit(WeightInit.XAVIER)
                .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT)
                .updater(new Adam())
                .l2(1e-4)
                .list()
                .layer(0,new LSTM.Builder()
                        .nIn(TIME_STEPS)
                        .nOut(10)
                        .activation(Activation.SOFTSIGN)
                        .gradientNormalization(GradientNormalization.ClipElementWiseAbsoluteValue)
                        .gradientNormalizationThreshold(10)
                        .build())
                .layer(1, new RnnOutputLayer.Builder(LossFunctions.LossFunction.MSE)
                        .activation(Activation.IDENTITY)
                        .nIn(10)
                        .nOut(1)
                        .gradientNormalization(GradientNormalization.ClipElementWiseAbsoluteValue)
                        .gradientNormalizationThreshold(10)
                        .build())
                .build();

        MultiLayerNetwork model = new MultiLayerNetwork(conf);
        model.init();

        System.out.println("Train model...");
        long startTime = System.currentTimeMillis();
        model.setListeners(new ScoreIterationListener(1)); // doesn't work

        for (int i=0; i < nEpoch; i++)
            model.fit(train_iterator);

        long endTime = System.currentTimeMillis();
        System.out.println("=============run time===================== " + (endTime - startTime));

        var eval = model.evaluateRegression(); // how i can evaluate model without iterator?
        System.out.println(eval.stats());

    }

//split a given univariate sequence into multiple samples where each sample has a specified number of time steps and the output is a single time step
    public static DataSet split_sequence(int[] sequence, int n_steps) {

        int arr_size = sequence.length - n_steps;
        var input = new double[arr_size][n_steps];
        var label = new double[arr_size];

        for (int i = 0; i < sequence.length; i++){
            int seq_end = i + n_steps;
            if (seq_end > sequence.length-1) break;
            input[i] = copyFromIntArray(Arrays.copyOfRange(sequence, i, seq_end)); // copyFromIntArray method converting int[] -> double[]
            label[i] = sequence[seq_end];
        }
        INDArray x = Nd4j.create(input).reshape(new int[]{arr_size, n_steps, 1});
        INDArray y = Nd4j.create(label).reshape(new int[]{arr_size, 1, 1});

        return new DataSet(x,y);
    }

```

#### Version Information

- DL4J 1.0.0-beta6
- Mac OS

---

<div class="post-metadata">

**Author:** ![treo](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/treo/32/47_2.png) [@treo](https://community.konduit.ai/u/treo)\
**Post date:** [February 26, 2020, 11:46am UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/2 "2020-02-26T11:46:17Z")

</div>

> [@Inqus](#):
>
> I retrieve my data from the database

You might be interested in using `JDBCRecordReader` instead of manually turning your data into arrays.

> [@Inqus](#):
>
> How do I normalize my data? Below in the code there is a commented-out code, it converts only the input data, but the labels remain not converted.

If you want to also normalize your labels, you just call `normalizer.fitLabel(true)`. It will then learn about both features and labels and normalize both of them when it transforms a dataset.

In order for your `Normalizer` to learn about your data set you pass in a `DataSetIterator` to its `.fit` method.

Afterwards, you would usually set the normalizer as a dataset preprocessor on the `DataSetIterator`. That way it will always be used when a `DataSet` is requested from the `DataSetIterator`.

> [@Inqus](#):
>
> I added a listener to the model but it does not work, tell me what could be the problem.

You likely haven’t configured logging properly. The ScoreIterationListener uses a logger to output the scores.

Check out [https://github.com/eclipse/deeplearning4j-examples/tree/master/standalone-sample-project](https://github.com/eclipse/deeplearning4j-examples/tree/master/standalone-sample-project) for an example project where it is configured sanely. The two files of most interest for logging in this case are:  
[https://github.com/eclipse/deeplearning4j-examples/blob/master/standalone-sample-project/pom.xml#L76-L80](https://github.com/eclipse/deeplearning4j-examples/blob/master/standalone-sample-project/pom.xml#L76-L80) which adds an actual logger to the project and  
[https://github.com/eclipse/deeplearning4j-examples/blob/master/standalone-sample-project/src/main/resources/logback.xml](https://github.com/eclipse/deeplearning4j-examples/blob/master/standalone-sample-project/src/main/resources/logback.xml) which contains the actual configuration

> [@Inqus](#):
>
> why can’t I evaluate test data without an iterator?

You can: [Eclipse Deeplearning4j · GitHub](https://deeplearning4j.org/api/latest/org/deeplearning4j/eval/Evaluation.html#eval-org.nd4j.linalg.api.ndarray.INDArray-org.nd4j.linalg.api.ndarray.INDArray-)

You just can’t use the convenience methods on the model directly.

> [@Inqus](#):
>
> How can I set the batch size if I do not use a DataSeIterator?

You will have to do it manually. Each `DataSet` object is a single batch.

> [@Inqus](#):
>
> Did I set the array shape for a recurrent neural network correctly?

The correct shape for a recurrent neural network is `[batchSize, featureSize, timeSteps]`.  
If I understand your code correctly, then no, you didn’t do it correctly.

---

<div class="post-metadata">

**Author:** ![Inqus](https://avatars.discourse-cdn.com/v4/letter/i/ee7513/32.png) [@Inqus](https://community.konduit.ai/u/Inqus)\
**Post date:** [February 26, 2020, 3:03pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/3 "2020-02-26T15:03:59Z")

</div>

@treo thanks for the reply. unfortunately I can’t use the _ **JDBCRecordReader** _, because I pre-process the data received from the database (interpolate, etc.), in the end I had to create files for iterators.  
I have one more question:  
I added classifier for nd4j but but the warning messages did not disappear (p.s cpu support avx2 - i7 6700hq)

```auto
       <dependency>
            <groupId>org.nd4j</groupId>
            <artifactId>nd4j-native-platform</artifactId>
            <version>1.0.0-beta6</version>
            <classifier>macosx-x86_64-avx2</classifier>
        </dependency>

```

```java
[main] INFO org.nd4j.linalg.factory.Nd4jBackend - Loaded [CpuBackend] backend
[main] INFO org.nd4j.nativeblas.NativeOpsHolder - Number of threads used for linear algebra: 1
[main] WARN org.nd4j.linalg.cpu.nativecpu.CpuNDArrayFactory - ***********************************CPU Feature Check Warning***********************************
[main] WARN org.nd4j.linalg.cpu.nativecpu.CpuNDArrayFactory - Warning: Initializing ND4J with Generic x86 binary on a CPU with AVX/AVX2 support
[main] WARN org.nd4j.linalg.cpu.nativecpu.CpuNDArrayFactory - Using ND4J with AVX/AVX2 will improve performance. See deeplearning4j.org/cpu for more details
[main] WARN org.nd4j.linalg.cpu.nativecpu.CpuNDArrayFactory - Or set environment variable ND4J_IGNORE_AVX=true to suppress this warning
[main] WARN org.nd4j.linalg.cpu.nativecpu.CpuNDArrayFactory - *************************************************************************************************
[main] INFO org.nd4j.nativeblas.Nd4jBlas - Number of threads used for OpenMP BLAS: 4
[main] INFO org.nd4j.linalg.api.ops.executioner.DefaultOpExecutioner - Backend used: [CPU]; OS: [Mac OS X]
[main] INFO org.nd4j.linalg.api.ops.executioner.DefaultOpExecutioner - Cores: [8]; Memory: [4,0GB];
[main] INFO org.nd4j.linalg.api.ops.executioner.DefaultOpExecutioner - Blas vendor: [OPENBLAS]

```

and  
for time series predictions (regression) i should use (early stopping)

> DataSetLossCalculator

or

> RegressionScoreCalculator

I found one more problem, ui server is not starting, or rather, I can’t access it

```java
 // ----- UI interface ----------------------
        //Initialize the user interface backend
        UIServer uiServer = UIServer.getInstance();

        //Configure where the network information (gradients, score vs. time etc) is to be stored. Here: store in memory.
        StatsStorage statsStorage = new InMemoryStatsStorage();

        //Attach the StatsStorage instance to the UI: this allows the contents of the StatsStorage to be visualized
        uiServer.attach(statsStorage);

        //Then add the StatsListener to collect this information from the network, as it trains
        model.setListeners(new StatsListener(statsStorage));
        //Finally: open your browser and go to http://localhost:9000/train
        // -----------------------------------------------

```

> [main] INFO org.deeplearning4j.ui.VertxUIServer - StatsStorage instance attached to UI: InMemoryStatsStorage(uid=90040e6b)

I tried to get the address, but got an exception

```auto
  System.out.println(uiServer.getAddress());
  System.out.println(uiServer.getPort());

```

```auto
Exception in thread "main" java.lang.NullPointerException
	at org.deeplearning4j.ui.VertxUIServer.getAddress(VertxUIServer.java:323)
	at ml.Trainer.main(Trainer.java:150)

```

```auto
        <dependency>
            <groupId>org.deeplearning4j</groupId>
            <artifactId>deeplearning4j-ui</artifactId>
            <version>1.0.0-beta6</version>
        </dependency>

```

thanks

---

<div class="post-metadata">

**Author:** ![treo](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/treo/32/47_2.png) [@treo](https://community.konduit.ai/u/treo)\
**Post date:** [February 26, 2020, 6:04pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/4 "2020-02-26T18:04:52Z")

</div>

> [@Inqus](#):
>
> unfortunately I can’t use the _ **JDBCRecordReader** _ , because I pre-process the data received from the database (interpolate, etc.), in the end I had to create files for iterators.

You can also create a RecordReader of your own. Many of the methods on the interface are actually optional and using a RecordReaderDataSetIterator will save you some headaches later on.

> [@Inqus](#):
>
> I added classifier for nd4j but but the warning messages did not disappear

In beta6 the avx2 message doesn’t go away even if you use the proper dependency. It is a known bug, and will go away in beta7.

> [@Inqus](#):
>
> for time series predictions (regression) i should use (early stopping) `DataSetLossCalculator` or `RegressionScoreCalculator`

It depends what you are optimizing for. If you want the lowest loss, then you go for `DataSetLossCalculator`, if you have a specific Regression Metric that you want to optimize for (which is different from the loss function that you are directly training on), then you go with `RegressionScoreCalculator`.

> [@Inqus](#):
>
> I tried to get the address, but got an exception

That happens because the server is started asynchronously. You should be able to access the server at [http://localhost:9000/train/overview](http://localhost:9000/train/overview) after a few seconds

---

<div class="post-metadata">

**Author:** ![Inqus](https://avatars.discourse-cdn.com/v4/letter/i/ee7513/32.png) [@Inqus](https://community.konduit.ai/u/Inqus)\
**Post date:** [February 26, 2020, 6:19pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/5 "2020-02-26T18:19:56Z")

</div>

> [@treo](#):
>
> That happens because the server is started asynchronously. You should be able to access the server at [http://localhost:9000/train/overview](http://localhost:9000/train/overview) after a few seconds

I tried now but could not log into the server. maybe it’s because of an early stopping?

---

<div class="post-metadata">

**Author:** ![treo](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/treo/32/47_2.png) [@treo](https://community.konduit.ai/u/treo)\
**Post date:** [February 26, 2020, 6:21pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/6 "2020-02-26T18:21:07Z")

</div>

> [@Inqus](#):
>
> could not log into the server.

What do you see? There is no login page there.

---

<div class="post-metadata">

**Author:** ![Inqus](https://avatars.discourse-cdn.com/v4/letter/i/ee7513/32.png) [@Inqus](https://community.konduit.ai/u/Inqus)\
**Post date:** [February 26, 2020, 6:25pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/7 "2020-02-26T18:25:11Z")

</div>

there is no interface. I can not access the server [screenshot](https://imgur.com/a/Dv104wf)

---

<div class="post-metadata">

**Author:** ![treo](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/treo/32/47_2.png) [@treo](https://community.konduit.ai/u/treo)\
**Post date:** [February 26, 2020, 6:40pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/8 "2020-02-26T18:40:55Z")

</div>

Can you step through `VertxUIServer.start`? Something appears to hinder it from actually starting up, but I can’t reproduce it on any of my machines.

---

<div class="post-metadata">

**Author:** ![Inqus](https://avatars.discourse-cdn.com/v4/letter/i/ee7513/32.png) [@Inqus](https://community.konduit.ai/u/Inqus)\
**Post date:** [February 26, 2020, 7:19pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/9 "2020-02-26T19:19:03Z")

</div>

> [@treo](#):
>
> VertxUIServer.start

i tried and got that:

```auto
Exception in thread "main" java.lang.IllegalArgumentException: The FreeMarker version requested by "incompatibleImprovements" was 2.3.29, but the installed FreeMarker version is only 2.3.23. You may need to upgrade FreeMarker in your project.
	at freemarker.template._TemplateAPI.checkVersionNotNullAndSupported(_TemplateAPI.java:49)
	at freemarker.core.Configurable.<init>(Configurable.java:309)
	at freemarker.template.Configuration.<init>(Configuration.java:634)
	at org.deeplearning4j.ui.module.train.TrainModule.<init>(TrainModule.java:140)
	at org.deeplearning4j.ui.VertxUIServer.start(VertxUIServer.java:197)
	at ml.Trainer.main(Trainer.java:120)

```

should I add a new version of Freemaker to pom.xml manually?

---

<div class="post-metadata">

**Author:** ![treo](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/treo/32/47_2.png) [@treo](https://community.konduit.ai/u/treo)\
**Post date:** [February 26, 2020, 7:26pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/10 "2020-02-26T19:26:58Z")

</div>

Interesting.  
Before doing the suggestions below, can you please run `mvn dependency:tree` and post the results here.

And afterwards can you add the following to your pom.xml and try again (without explicity calling `VertxUIServer.start`):

```xml
    <dependencyManagement>
        <dependencies>
            <dependency>
                <groupId>org.freemarker</groupId>
                <artifactId>freemarker</artifactId>
                <version>2.3.29</version>
            </dependency>
        </dependencies>
    </dependencyManagement>

```

---

<div class="post-metadata">

**Author:** ![Inqus](https://avatars.discourse-cdn.com/v4/letter/i/ee7513/32.png) [@Inqus](https://community.konduit.ai/u/Inqus)\
**Post date:** [February 26, 2020, 7:31pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/11 "2020-02-26T19:31:40Z")

</div>

> [@treo](#):
>
> Before doing the suggestions below, can you please run `mvn dependency:tree` and post the results here.

a few lines of package downloading and below

```auto
[INFO] BUILD FAILURE
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 46.751 s
[INFO] Finished at: 2020-02-27T01:30:20+06:00
[INFO] ------------------------------------------------------------------------
[ERROR] Failed to execute goal on project Forecast: Could not resolve dependencies for project groudId:Forecast:jar:1.0-SNAPSHOT: Could not find artifact org.nd4j:nd4j-native-platform:jar:macosx-x86_64-avx2:1.0.0-beta6 in central (https://repo.maven.apache.org/maven2) -> [Help 1]
[ERROR]
[ERROR] To see the full stack trace of the errors, re-run Maven with the -e switch.
[ERROR] Re-run Maven using the -X switch to enable full debug logging.
[ERROR]
[ERROR] For more information about the errors and possible solutions, please read the following articles:
[ERROR] [Help 1] http://cwiki.apache.org/confluence/display/MAVEN/DependencyResolutionException

```

---

<div class="post-metadata">

**Author:** ![treo](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/treo/32/47_2.png) [@treo](https://community.konduit.ai/u/treo)\
**Post date:** [February 26, 2020, 7:37pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/12 "2020-02-26T19:37:39Z")

</div>

> [@Inqus](#):
>
> Could not find artifact org.nd4j:nd4j-native-platform:jar:macosx-x86\_64-avx2

Oh, I overlooked that earlier. Too many questions at once 😅

For that you should be using just ndj4-native for the artifactId. But that is unrelated to the UI not starting. But maybe the AVX2 message will go away now 🙂

---

<div class="post-metadata">

**Author:** ![Inqus](https://avatars.discourse-cdn.com/v4/letter/i/ee7513/32.png) [@Inqus](https://community.konduit.ai/u/Inqus)\
**Post date:** [February 26, 2020, 7:39pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/13 "2020-02-26T19:39:12Z")

</div>

I should delete classifier right?

```auto
<dependency>
            <groupId>org.nd4j</groupId>
            <artifactId>nd4j-native-platform</artifactId>
            <version>1.0.0-beta6</version>
            <classifier>macosx-x86_64-avx2</classifier>
        </dependency>

```

---

<div class="post-metadata">

**Author:** ![Inqus](https://avatars.discourse-cdn.com/v4/letter/i/ee7513/32.png) [@Inqus](https://community.konduit.ai/u/Inqus)\
**Post date:** [February 26, 2020, 7:40pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/14 "2020-02-26T19:40:42Z")

</div>

i delete classifier (mac os)  
and this `mvn dependency:tree` results  
(p.s here it seems a few unnecessary imports (apparently in vain I turned on auto import in intellij)

```auto
[INFO] groudId:Forecast:jar:1.0-SNAPSHOT
[INFO] +- org.nd4j:nd4j-native-platform:jar:1.0.0-beta6:compile
[INFO] | +- org.bytedeco:openblas-platform:jar:0.3.7-1.5.2:compile
[INFO] | | +- org.bytedeco:openblas:jar:0.3.7-1.5.2:compile
[INFO] | | +- org.bytedeco:openblas:jar:android-arm:0.3.7-1.5.2:compile
[INFO] | | +- org.bytedeco:openblas:jar:android-arm64:0.3.7-1.5.2:compile
[INFO] | | +- org.bytedeco:openblas:jar:android-x86:0.3.7-1.5.2:compile
[INFO] | | +- org.bytedeco:openblas:jar:android-x86_64:0.3.7-1.5.2:compile
[INFO] | | +- org.bytedeco:openblas:jar:ios-arm64:0.3.7-1.5.2:compile
[INFO] | | +- org.bytedeco:openblas:jar:ios-x86_64:0.3.7-1.5.2:compile
[INFO] | | +- org.bytedeco:openblas:jar:linux-x86:0.3.7-1.5.2:compile
[INFO] | | +- org.bytedeco:openblas:jar:linux-x86_64:0.3.7-1.5.2:compile
[INFO] | | +- org.bytedeco:openblas:jar:linux-armhf:0.3.7-1.5.2:compile
[INFO] | | +- org.bytedeco:openblas:jar:linux-arm64:0.3.7-1.5.2:compile
[INFO] | | +- org.bytedeco:openblas:jar:linux-ppc64le:0.3.7-1.5.2:compile
[INFO] | | +- org.bytedeco:openblas:jar:macosx-x86_64:0.3.7-1.5.2:compile
[INFO] | | +- org.bytedeco:openblas:jar:windows-x86:0.3.7-1.5.2:compile
[INFO] | | \- org.bytedeco:openblas:jar:windows-x86_64:0.3.7-1.5.2:compile
[INFO] | +- org.bytedeco:mkl-platform:jar:2019.5-1.5.2:compile
[INFO] | | +- org.bytedeco:mkl:jar:2019.5-1.5.2:compile
[INFO] | | +- org.bytedeco:mkl:jar:linux-x86:2019.5-1.5.2:compile
[INFO] | | +- org.bytedeco:mkl:jar:linux-x86_64:2019.5-1.5.2:compile
[INFO] | | +- org.bytedeco:mkl:jar:macosx-x86_64:2019.5-1.5.2:compile
[INFO] | | +- org.bytedeco:mkl:jar:windows-x86:2019.5-1.5.2:compile
[INFO] | | \- org.bytedeco:mkl:jar:windows-x86_64:2019.5-1.5.2:compile
[INFO] | +- org.nd4j:nd4j-native:jar:1.0.0-beta6:compile
[INFO] | | +- org.bytedeco:javacpp:jar:1.5.2:compile
[INFO] | | \- org.nd4j:nd4j-native-api:jar:1.0.0-beta6:compile
[INFO] | +- org.nd4j:nd4j-native:jar:android-arm:1.0.0-beta6:compile
[INFO] | +- org.nd4j:nd4j-native:jar:android-arm64:1.0.0-beta6:compile
[INFO] | +- org.nd4j:nd4j-native:jar:android-x86:1.0.0-beta6:compile
[INFO] | +- org.nd4j:nd4j-native:jar:android-x86_64:1.0.0-beta6:compile
[INFO] | +- org.nd4j:nd4j-native:jar:ios-arm64:1.0.0-beta6:compile
[INFO] | +- org.nd4j:nd4j-native:jar:ios-x86_64:1.0.0-beta6:compile
[INFO] | +- org.nd4j:nd4j-native:jar:linux-x86_64:1.0.0-beta6:compile
[INFO] | +- org.nd4j:nd4j-native:jar:macosx-x86_64:1.0.0-beta6:compile
[INFO] | +- org.nd4j:nd4j-native:jar:windows-x86_64:1.0.0-beta6:compile
[INFO] | +- org.nd4j:nd4j-native:jar:linux-ppc64le:1.0.0-beta6:compile
[INFO] | \- org.nd4j:nd4j-native:jar:linux-armhf:1.0.0-beta6:compile
[INFO] +- org.deeplearning4j:deeplearning4j-core:jar:1.0.0-beta6:compile
[INFO] | +- org.deeplearning4j:deeplearning4j-tsne:jar:1.0.0-beta6:compile
[INFO] | | \- org.deeplearning4j:nearestneighbor-core:jar:1.0.0-beta6:compile
[INFO] | +- org.deeplearning4j:deeplearning4j-datasets:jar:1.0.0-beta6:compile
[INFO] | | \- org.deeplearning4j:deeplearning4j-common:jar:1.0.0-beta6:compile
[INFO] | +- org.deeplearning4j:deeplearning4j-datavec-iterators:jar:1.0.0-beta6:compile
[INFO] | +- org.deeplearning4j:deeplearning4j-modelimport:jar:1.0.0-beta6:compile
[INFO] | | \- org.bytedeco:hdf5-platform:jar:1.10.5-1.5.2:compile
[INFO] | | +- org.bytedeco:hdf5:jar:1.10.5-1.5.2:compile
[INFO] | | +- org.bytedeco:hdf5:jar:linux-x86:1.10.5-1.5.2:compile
[INFO] | | +- org.bytedeco:hdf5:jar:linux-x86_64:1.10.5-1.5.2:compile
[INFO] | | +- org.bytedeco:hdf5:jar:linux-armhf:1.10.5-1.5.2:compile
[INFO] | | +- org.bytedeco:hdf5:jar:linux-arm64:1.10.5-1.5.2:compile
[INFO] | | +- org.bytedeco:hdf5:jar:linux-ppc64le:1.10.5-1.5.2:compile
[INFO] | | +- org.bytedeco:hdf5:jar:macosx-x86_64:1.10.5-1.5.2:compile
[INFO] | | +- org.bytedeco:hdf5:jar:windows-x86:1.10.5-1.5.2:compile
[INFO] | | \- org.bytedeco:hdf5:jar:windows-x86_64:1.10.5-1.5.2:compile
[INFO] | +- org.slf4j:slf4j-api:jar:1.7.21:compile
[INFO] | +- org.deeplearning4j:deeplearning4j-nn:jar:1.0.0-beta6:compile
[INFO] | | +- org.deeplearning4j:deeplearning4j-utility-iterators:jar:1.0.0-beta6:compile
[INFO] | | | \- org.deeplearning4j:deeplearning4j-util:jar:1.0.0-beta6:compile
[INFO] | | +- org.lucee:oswego-concurrent:jar:1.3.4:compile
[INFO] | | +- org.nd4j:nd4j-common:jar:1.0.0-beta6:compile
[INFO] | | | \- org.nd4j:guava:jar:1.0.0-beta6:compile
[INFO] | | +- com.github.oshi:oshi-core:jar:3.4.2:compile
[INFO] | | | +- net.java.dev.jna:jna-platform:jar:4.3.0:compile
[INFO] | | | | \- net.java.dev.jna:jna:jar:4.3.0:compile
[INFO] | | | \- org.threeten:threetenbp:jar:1.3.3:compile
[INFO] | | \- it.unimi.dsi:fastutil:jar:6.5.7:compile
[INFO] | +- org.apache.commons:commons-math3:jar:3.5:compile
[INFO] | +- commons-io:commons-io:jar:2.5:compile
[INFO] | +- org.apache.commons:commons-compress:jar:1.18:compile
[INFO] | +- org.nd4j:nd4j-api:jar:1.0.0-beta6:compile
[INFO] | | +- com.jakewharton.byteunits:byteunits:jar:0.9.1:compile
[INFO] | | +- com.google.flatbuffers:flatbuffers-java:jar:1.10.0:compile
[INFO] | | +- org.nd4j:protobuf:jar:1.0.0-beta6:compile
[INFO] | | +- commons-net:commons-net:jar:3.1:compile
[INFO] | | +- org.nd4j:nd4j-buffer:jar:1.0.0-beta6:compile
[INFO] | | +- org.nd4j:nd4j-context:jar:1.0.0-beta6:compile
[INFO] | | \- net.ericaro:neoitertools:jar:1.0.0:compile
[INFO] | +- org.apache.commons:commons-lang3:jar:3.6:compile
[INFO] | +- org.nd4j:jackson:jar:1.0.0-beta6:compile
[INFO] | +- org.datavec:datavec-api:jar:1.0.0-beta6:compile
[INFO] | | +- commons-codec:commons-codec:jar:1.10:compile
[INFO] | | +- joda-time:joda-time:jar:2.2:compile
[INFO] | | +- org.freemarker:freemarker:jar:2.3.23:compile
[INFO] | | +- com.clearspring.analytics:stream:jar:2.7.0:compile
[INFO] | | +- net.sf.opencsv:opencsv:jar:2.3:compile
[INFO] | | \- com.tdunning:t-digest:jar:3.2:compile
[INFO] | +- org.datavec:datavec-data-image:jar:1.0.0-beta6:compile
[INFO] | | +- com.github.jai-imageio:jai-imageio-core:jar:1.3.0:compile
[INFO] | | +- com.twelvemonkeys.imageio:imageio-jpeg:jar:3.1.1:compile
[INFO] | | | +- com.twelvemonkeys.imageio:imageio-core:jar:3.1.1:compile
[INFO] | | | +- com.twelvemonkeys.imageio:imageio-metadata:jar:3.1.1:compile
[INFO] | | | +- com.twelvemonkeys.common:common-lang:jar:3.1.1:compile
[INFO] | | | +- com.twelvemonkeys.common:common-io:jar:3.1.1:compile
[INFO] | | | \- com.twelvemonkeys.common:common-image:jar:3.1.1:compile
[INFO] | | +- com.twelvemonkeys.imageio:imageio-tiff:jar:3.1.1:compile
[INFO] | | +- com.twelvemonkeys.imageio:imageio-psd:jar:3.1.1:compile
[INFO] | | +- com.twelvemonkeys.imageio:imageio-bmp:jar:3.1.1:compile
[INFO] | | +- org.bytedeco:javacv:jar:1.5.2:compile
[INFO] | | | +- org.bytedeco:opencv:jar:4.1.2-1.5.2:compile
[INFO] | | | +- org.bytedeco:ffmpeg:jar:4.2.1-1.5.2:compile
[INFO] | | | +- org.bytedeco:flycapture:jar:2.13.3.31-1.5.2:compile
[INFO] | | | +- org.bytedeco:libdc1394:jar:2.2.6-1.5.2:compile
[INFO] | | | +- org.bytedeco:libfreenect:jar:0.5.7-1.5.2:compile
[INFO] | | | +- org.bytedeco:libfreenect2:jar:0.2.0-1.5.2:compile
[INFO] | | | +- org.bytedeco:librealsense:jar:1.12.4-1.5.2:compile
[INFO] | | | +- org.bytedeco:librealsense2:jar:2.29.0-1.5.2:compile
[INFO] | | | +- org.bytedeco:videoinput:jar:0.200-1.5.2:compile
[INFO] | | | +- org.bytedeco:artoolkitplus:jar:2.3.1-1.5.2:compile
[INFO] | | | +- org.bytedeco:flandmark:jar:1.07-1.5.2:compile
[INFO] | | | +- org.bytedeco:leptonica:jar:1.78.0-1.5.2:compile
[INFO] | | | +- org.bytedeco:tesseract:jar:4.1.0-1.5.2:compile
[INFO] | | | \- org.openjfx:javafx-graphics:jar:11:compile
[INFO] | | | +- org.openjfx:javafx-graphics:jar:mac:11:compile
[INFO] | | | \- org.openjfx:javafx-base:jar:11:compile
[INFO] | | | \- org.openjfx:javafx-base:jar:mac:11:compile
[INFO] | | +- org.bytedeco:opencv-platform:jar:4.1.2-1.5.2:compile
[INFO] | | | +- org.bytedeco:opencv:jar:android-arm:4.1.2-1.5.2:compile
[INFO] | | | +- org.bytedeco:opencv:jar:android-arm64:4.1.2-1.5.2:compile
[INFO] | | | +- org.bytedeco:opencv:jar:android-x86:4.1.2-1.5.2:compile
[INFO] | | | +- org.bytedeco:opencv:jar:android-x86_64:4.1.2-1.5.2:compile
[INFO] | | | +- org.bytedeco:opencv:jar:ios-arm64:4.1.2-1.5.2:compile
[INFO] | | | +- org.bytedeco:opencv:jar:ios-x86_64:4.1.2-1.5.2:compile
[INFO] | | | +- org.bytedeco:opencv:jar:linux-x86:4.1.2-1.5.2:compile
[INFO] | | | +- org.bytedeco:opencv:jar:linux-x86_64:4.1.2-1.5.2:compile
[INFO] | | | +- org.bytedeco:opencv:jar:linux-armhf:4.1.2-1.5.2:compile
[INFO] | | | +- org.bytedeco:opencv:jar:linux-arm64:4.1.2-1.5.2:compile
[INFO] | | | +- org.bytedeco:opencv:jar:linux-ppc64le:4.1.2-1.5.2:compile
[INFO] | | | +- org.bytedeco:opencv:jar:macosx-x86_64:4.1.2-1.5.2:compile
[INFO] | | | +- org.bytedeco:opencv:jar:windows-x86:4.1.2-1.5.2:compile
[INFO] | | | \- org.bytedeco:opencv:jar:windows-x86_64:4.1.2-1.5.2:compile
[INFO] | | \- org.bytedeco:leptonica-platform:jar:1.78.0-1.5.2:compile
[INFO] | | +- org.bytedeco:leptonica:jar:android-arm:1.78.0-1.5.2:compile
[INFO] | | +- org.bytedeco:leptonica:jar:android-arm64:1.78.0-1.5.2:compile
[INFO] | | +- org.bytedeco:leptonica:jar:android-x86:1.78.0-1.5.2:compile
[INFO] | | +- org.bytedeco:leptonica:jar:android-x86_64:1.78.0-1.5.2:compile
[INFO] | | +- org.bytedeco:leptonica:jar:linux-x86:1.78.0-1.5.2:compile
[INFO] | | +- org.bytedeco:leptonica:jar:linux-x86_64:1.78.0-1.5.2:compile
[INFO] | | +- org.bytedeco:leptonica:jar:linux-armhf:1.78.0-1.5.2:compile
[INFO] | | +- org.bytedeco:leptonica:jar:linux-arm64:1.78.0-1.5.2:compile
[INFO] | | +- org.bytedeco:leptonica:jar:linux-ppc64le:1.78.0-1.5.2:compile
[INFO] | | +- org.bytedeco:leptonica:jar:macosx-x86_64:1.78.0-1.5.2:compile
[INFO] | | +- org.bytedeco:leptonica:jar:windows-x86:1.78.0-1.5.2:compile
[INFO] | | \- org.bytedeco:leptonica:jar:windows-x86_64:1.78.0-1.5.2:compile
[INFO] | \- org.deeplearning4j:deeplearning4j-ui-components:jar:1.0.0-beta6:compile
[INFO] +- org.slf4j:slf4j-simple:jar:1.7.21:compile
[INFO] +- commons-cli:commons-cli:jar:1.2:compile
[INFO] +- org.deeplearning4j:arbiter-deeplearning4j:jar:1.0.0-beta6:compile
[INFO] | +- org.deeplearning4j:arbiter-core:jar:1.0.0-beta6:compile
[INFO] | \- com.google.code.gson:gson:jar:2.8.0:compile
[INFO] +- org.deeplearning4j:arbiter-ui:jar:1.0.0-beta6:compile
[INFO] +- org.deeplearning4j:deeplearning4j-ui:jar:1.0.0-beta6:compile
[INFO] | +- org.deeplearning4j:deeplearning4j-vertx:jar:1.0.0-beta6:compile
[INFO] | | +- io.vertx:vertx-core:jar:3.8.3:compile
[INFO] | | | +- io.netty:netty-common:jar:4.1.42.Final:compile
[INFO] | | | +- io.netty:netty-buffer:jar:4.1.42.Final:compile
[INFO] | | | +- io.netty:netty-transport:jar:4.1.42.Final:compile
[INFO] | | | +- io.netty:netty-handler:jar:4.1.42.Final:compile
[INFO] | | | | \- io.netty:netty-codec:jar:4.1.42.Final:compile
[INFO] | | | +- io.netty:netty-handler-proxy:jar:4.1.42.Final:compile
[INFO] | | | | \- io.netty:netty-codec-socks:jar:4.1.42.Final:compile
[INFO] | | | +- io.netty:netty-codec-http:jar:4.1.42.Final:compile
[INFO] | | | +- io.netty:netty-codec-http2:jar:4.1.42.Final:compile
[INFO] | | | +- io.netty:netty-resolver:jar:4.1.42.Final:compile
[INFO] | | | +- io.netty:netty-resolver-dns:jar:4.1.42.Final:compile
[INFO] | | | | \- io.netty:netty-codec-dns:jar:4.1.42.Final:compile
[INFO] | | | +- com.fasterxml.jackson.core:jackson-core:jar:2.9.9:compile
[INFO] | | | \- com.fasterxml.jackson.core:jackson-databind:jar:2.9.9.1:compile
[INFO] | | | \- com.fasterxml.jackson.core:jackson-annotations:jar:2.9.0:compile
[INFO] | | +- io.vertx:vertx-web:jar:3.8.3:compile
[INFO] | | | +- io.vertx:vertx-web-common:jar:3.8.3:compile
[INFO] | | | +- io.vertx:vertx-auth-common:jar:3.8.3:compile
[INFO] | | | \- io.vertx:vertx-bridge-common:jar:3.8.3:compile
[INFO] | | +- com.beust:jcommander:jar:1.27:compile
[INFO] | | +- jakarta.xml.bind:jakarta.xml.bind-api:jar:2.3.2:compile
[INFO] | | | \- jakarta.activation:jakarta.activation-api:jar:1.2.1:compile
[INFO] | | +- org.webjars.npm:babel__polyfill:jar:7.4.4:compile
[INFO] | | | +- org.webjars.npm:core-js:jar:3.0.0-beta.9:compile (version selected from constraint [2.6.5,3))
[INFO] | | | \- org.webjars.npm:regenerator-runtime:jar:0.13.4:compile (version selected from constraint [0.13.2,0.14))
[INFO] | | +- org.webjars.npm:coreui__coreui:jar:2.1.9:compile
[INFO] | | +- org.webjars.npm:coreui__icons:jar:0.3.0:compile
[INFO] | | +- org.webjars.npm:jquery:jar:3.4.1:compile
[INFO] | | +- org.webjars.bower:popper.js:jar:1.12.9:compile
[INFO] | | +- org.webjars.npm:bootstrap:jar:4.3.1:compile
[INFO] | | +- org.webjars:jquery:jar:2.2.0:compile
[INFO] | | +- org.webjars:jquery-migrate:jar:1.2.1:compile
[INFO] | | +- org.webjars:jquery-ui:jar:1.10.2:compile
[INFO] | | +- org.webjars:modernizr:jar:2.8.3-1:compile
[INFO] | | +- org.webjars:jquery-cookie:jar:1.4.1-1:compile
[INFO] | | +- org.webjars:fullcalendar:jar:1.6.4:compile
[INFO] | | +- org.webjars:excanvas:jar:3:compile
[INFO] | | +- org.webjars.npm:cytoscape:jar:3.3.3:compile
[INFO] | | | +- org.webjars.npm:heap:jar:0.2.6:compile (version selected from constraint [0.2.6,0.3))
[INFO] | | | \- org.webjars.npm:lodash.debounce:jar:4.0.8:compile (version selected from constraint [4.0.8,5))
[INFO] | | +- org.webjars.bower:cytoscape-dagre:jar:2.1.0:compile
[INFO] | | | +- org.webjars.bower:cytoscape:jar:3.2.5:compile (version selected from constraint [3.2.0,4))
[INFO] | | | \- org.webjars.bower:dagre:jar:0.7.4:compile (version selected from constraint [0.7.4,0.8))
[INFO] | | | +- org.webjars.bower:graphlib:jar:1.0.7:compile (version selected from constraint [1.0.5,2))
[INFO] | | | \- org.webjars.bower:lodash:jar:3.10.1-amd:compile (version selected from constraint [3.10.0,4))
[INFO] | | +- org.webjars.npm:dagre:jar:0.8.4:compile
[INFO] | | | +- org.webjars.npm:graphlib:jar:2.1.8:compile (version selected from constraint [2.1.7,3))
[INFO] | | | \- org.webjars.npm:lodash:jar:4.17.15:compile (version selected from constraint [4.17.4,5))
[INFO] | | +- org.webjars.npm:cytoscape-cola:jar:2.3.0:compile
[INFO] | | | \- org.webjars.npm:webcola:jar:3.3.8:compile (version selected from constraint [3.3.6,4))
[INFO] | | | +- org.webjars.npm:d3-dispatch:jar:1.0.6:compile (version selected from constraint [1.0.3,2))
[INFO] | | | +- org.webjars.npm:d3-drag:jar:1.2.5:compile (version selected from constraint [1.0.4,2))
[INFO] | | | | \- org.webjars.npm:d3-selection:jar:2.0.0-rc.2:compile (version selected from constraint [1,2))
[INFO] | | | \- org.webjars.npm:d3-timer:jar:1.0.10:compile (version selected from constraint [1.0.5,2))
[INFO] | | +- org.webjars.npm:cytoscape-cose-bilkent:jar:4.0.0:compile
[INFO] | | +- org.webjars.npm:cytoscape-euler:jar:1.2.1:compile
[INFO] | | +- org.webjars.npm:cytoscape-klay:jar:3.1.2:compile
[INFO] | | +- org.webjars.npm:klayjs:jar:0.4.1:compile
[INFO] | | +- org.webjars.npm:cytoscape-spread:jar:3.0.0:compile
[INFO] | | +- org.webjars.npm:weaverjs:jar:1.2.0:compile
[INFO] | | +- org.webjars:retinajs:jar:0.0.2:compile
[INFO] | | +- org.webjars:flot:jar:0.8.3:compile
[INFO] | | | \- org.webjars:explorercanvas:jar:r3-1:compile
[INFO] | | +- org.webjars:chosen:jar:0.9.8:compile
[INFO] | | +- org.webjars:uniform:jar:2.1.2-1:compile
[INFO] | | +- org.webjars:noty:jar:2.2.2:compile
[INFO] | | +- org.webjars:jquery-raty:jar:2.5.2:compile
[INFO] | | +- org.webjars:imagesloaded:jar:2.1.1:compile
[INFO] | | +- org.webjars:masonry:jar:3.1.5:compile
[INFO] | | +- org.webjars:jquery.sparkline:jar:2.1.2:compile
[INFO] | | +- org.webjars:jquery-knob:jar:1.2.2:compile
[INFO] | | +- org.webjars:datatables:jar:1.9.4:compile
[INFO] | | +- org.webjars:jquery-ui-touch-punch:jar:0.2.2:compile
[INFO] | | +- org.webjars:d3js:jar:3.3.5:compile
[INFO] | | +- org.webjars:bootstrap-notify:jar:3.1.3-1:compile
[INFO] | | +- org.webjars.npm:github-com-jboesch-Gritter:jar:1.7.4:compile
[INFO] | | +- org.webjars.bowergithub.stenin-nikita:open-sans:jar:0.1.3:compile
[INFO] | | +- org.webjars:font-awesome:jar:3.0.2:compile
[INFO] | | | \- org.webjars:bootstrap:jar:2.2.2-1:compile
[INFO] | | +- org.webjars:bootstrap-glyphicons:jar:bdd2cbfba0:compile
[INFO] | | \- org.webjars.npm:flatbuffers:jar:1.9.0:compile
[INFO] | +- org.deeplearning4j:deeplearning4j-nlp:jar:1.0.0-beta6:compile
[INFO] | | +- commons-lang:commons-lang:jar:2.6:compile
[INFO] | | +- org.threadly:threadly:jar:4.10.0:compile
[INFO] | | \- com.github.vinhkhuc:jfasttext:jar:0.4:compile
[INFO] | +- org.nd4j:nd4j-jackson:jar:1.0.0-beta6:compile
[INFO] | \- org.deeplearning4j:deeplearning4j-ui-model:jar:1.0.0-beta6:compile
[INFO] | +- org.agrona:Agrona:jar:0.5.4:compile
[INFO] | +- org.mapdb:mapdb:jar:3.0.5:compile
[INFO] | | +- org.jetbrains.kotlin:kotlin-stdlib:jar:1.0.7:compile
[INFO] | | | \- org.jetbrains.kotlin:kotlin-runtime:jar:1.0.7:compile
[INFO] | | +- org.eclipse.collections:eclipse-collections-api:jar:7.1.2:compile (version selected from constraint [7.0.0,7.20.0))
[INFO] | | | \- net.jcip:jcip-annotations:jar:1.0:compile
[INFO] | | +- org.eclipse.collections:eclipse-collections:jar:7.1.2:compile (version selected from constraint [7.0.0,7.20.0))
[INFO] | | +- org.eclipse.collections:eclipse-collections-forkjoin:jar:7.1.2:compile (version selected from constraint [7.0.0,7.20.0))
[INFO] | | +- com.google.guava:guava:jar:19.0:compile (version selected from constraint [15.0,19.20))
[INFO] | | +- net.jpountz.lz4:lz4:jar:1.3.0:compile
[INFO] | | \- org.mapdb:elsa:jar:3.0.0-M5:compile
[INFO] | \- org.xerial:sqlite-jdbc:jar:3.15.1:compile
[INFO] +- org.apache.commons:commons-csv:jar:1.8:compile
[INFO] +- org.jfree:jfreechart:jar:1.0.19:compile
[INFO] | \- org.jfree:jcommon:jar:1.0.23:compile
[INFO] \- org.postgresql:postgresql:jar:42.2.10:compile
[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 10.764 s
[INFO] Finished at: 2020-02-27T01:39:52+06:00
[INFO] ------------------------------------------------------------------------

```

---

<div class="post-metadata">

**Author:** ![treo](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/treo/32/47_2.png) [@treo](https://community.konduit.ai/u/treo)\
**Post date:** [February 26, 2020, 7:51pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/15 "2020-02-26T19:51:10Z")

</div>

> [@Inqus](#):
>
> I should delete classifier right?

No, this dependency should instead look like this:

```xml
<dependency>
  <groupId>org.nd4j</groupId>
  <artifactId>nd4j-native</artifactId>
  <version>1.0.0-beta6</version>
  <classifier>macosx-x86_64-avx2</classifier>
</dependency>

```

> [@Inqus](#):
>
> a few unnecessary imports

That is what the `-platform` artifacts will add so it runs on all the supported platforms.

Anyway, does it work now with the dependencyManagement section added?

---

<div class="post-metadata">

**Author:** ![Inqus](https://avatars.discourse-cdn.com/v4/letter/i/ee7513/32.png) [@Inqus](https://community.konduit.ai/u/Inqus)\
**Post date:** [February 26, 2020, 7:58pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/16 "2020-02-26T19:58:12Z")

</div>

What have I done wrong?)

```auto
Exception in thread "main" java.lang.ExceptionInInitializerError
	at org.deeplearning4j.nn.conf.MultiLayerConfiguration$Builder.build(MultiLayerConfiguration.java:719)
	at org.deeplearning4j.nn.conf.NeuralNetConfiguration$ListBuilder.build(NeuralNetConfiguration.java:258)
	at ml.Trainer.main(Trainer.java:97)
Caused by: java.lang.RuntimeException: org.nd4j.linalg.factory.Nd4jBackend$NoAvailableBackendException: Please ensure that you have an nd4j backend on your classpath. Please see: http://nd4j.org/getstarted.html
	at org.nd4j.linalg.factory.Nd4j.initContext(Nd4j.java:5131)
	at org.nd4j.linalg.factory.Nd4j.<clinit>(Nd4j.java:226)
	... 3 more
Caused by: org.nd4j.linalg.factory.Nd4jBackend$NoAvailableBackendException: Please ensure that you have an nd4j backend on your classpath. Please see: http://nd4j.org/getstarted.html
	at org.nd4j.linalg.factory.Nd4jBackend.load(Nd4jBackend.java:218)
	at org.nd4j.linalg.factory.Nd4j.initContext(Nd4j.java:5128)
	... 4 more

```

---

<div class="post-metadata">

**Author:** ![treo](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/treo/32/47_2.png) [@treo](https://community.konduit.ai/u/treo)\
**Post date:** [February 26, 2020, 8:01pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/17 "2020-02-26T20:01:36Z")

</div>

I think we are getting ahead of ourselves now. Let’s fix one problem at a time.

Let’s work on the AVX2 classifier thing after we solved your UI problem. So please leave your pom.xml just as it was when it worked and only add the `<dependencyManagement>` section as I’ve indicated in the previous post (at the same level as the `<dependencies>` section is).

---

<div class="post-metadata">

**Author:** ![Inqus](https://avatars.discourse-cdn.com/v4/letter/i/ee7513/32.png) [@Inqus](https://community.konduit.ai/u/Inqus)\
**Post date:** [February 26, 2020, 8:05pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/18 "2020-02-26T20:05:36Z")

</div>

I returned the previous dependency and now UI server is working

---

<div class="post-metadata">

**Author:** ![treo](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/treo/32/47_2.png) [@treo](https://community.konduit.ai/u/treo)\
**Post date:** [February 26, 2020, 8:08pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/19 "2020-02-26T20:08:42Z")

</div>

Great 👍. Now for your AVX2 problem:

If you want to deploy your application on a server and use AVX2 on your mac, you should have both of those dependencies:

```xml
<dependency>
  <groupId>org.nd4j</groupId>
  <artifactId>nd4j-native</artifactId>
  <version>1.0.0-beta6</version>
  <classifier>macosx-x86_64-avx2</classifier>
</dependency>
<dependency>
  <groupId>org.nd4j</groupId>
  <artifactId>nd4j-native-platform</artifactId>
  <version>1.0.0-beta6</version>
</dependency>

```

---

<div class="post-metadata">

**Author:** ![Inqus](https://avatars.discourse-cdn.com/v4/letter/i/ee7513/32.png) [@Inqus](https://community.konduit.ai/u/Inqus)\
**Post date:** [February 26, 2020, 8:13pm UTC](https://community.konduit.ai/t/questions-for-time-series-lstm/171/20 "2020-02-26T20:13:10Z")

</div>

thanks a lot. when I deploy the application to the server I can use native-platform dependency right

> [@treo](#):
>
> org.nd4j nd4j-native-platform 1.0.0-beta6

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