Running TimeSeries Demo, got the TranslateException: ai.djl.engine.EngineException #2641

mengzhizihu · 2023-06-08T02:34:50Z

Description

When I run the TimeSeries Demo, I got an exception called "Exception in thread "main" ai.djl.translate.TranslateException: ai.djl.engine.EngineException: Expected at most 7 argument(s) for operator 'forward', but received 8 argument(s). Declaration: forward(torch.gluonts.torch.model.deepar.module.DeepARModel self, Tensor feat_static_cat, Tensor feat_static_real, Tensor past_time_feat, Tensor past_target, Tensor past_observed_values, Tensor future_time_feat) -> Tensor"

Expected Behavior

(what's the expected behavior?)
Expected that I can get a successful running result

Error Message

(Paste the complete error message, including stack trace.)
Exception in thread "main" ai.djl.translate.TranslateException: ai.djl.engine.EngineException: Expected at most 7 argument(s) for operator 'forward', but received 8 argument(s). Declaration: forward(torch.gluonts.torch.model.deepar.module.DeepARModel self, Tensor feat_static_cat, Tensor feat_static_real, Tensor past_time_feat, Tensor past_target, Tensor past_observed_values, Tensor future_time_feat) -> Tensor
at ai.djl.inference.Predictor.batchPredict(Predictor.java:189)
at ai.djl.inference.Predictor.predict(Predictor.java:126)
at com.demo.djl.TimeSeriesTest.predict(TimeSeriesTest.java:68)
at com.demo.djl.TimeSeriesTest.main(TimeSeriesTest.java:34)
Caused by: ai.djl.engine.EngineException: Expected at most 7 argument(s) for operator 'forward', but received 8 argument(s). Declaration: forward(torch.gluonts.torch.model.deepar.module.DeepARModel self, Tensor feat_static_cat, Tensor feat_static_real, Tensor past_time_feat, Tensor past_target, Tensor past_observed_values, Tensor future_time_feat) -> Tensor
at ai.djl.pytorch.jni.PyTorchLibrary.moduleRunMethod(Native Method)
at ai.djl.pytorch.jni.IValueUtils.forward(IValueUtils.java:53)
at ai.djl.pytorch.engine.PtSymbolBlock.forwardInternal(PtSymbolBlock.java:145)
at ai.djl.nn.AbstractBaseBlock.forward(AbstractBaseBlock.java:79)
at ai.djl.nn.Block.forward(Block.java:127)
at ai.djl.inference.Predictor.predictInternal(Predictor.java:140)
at ai.djl.inference.Predictor.batchPredict(Predictor.java:180)
... 3 more

How to Reproduce?

(If you developed your own code, please provide a short script that reproduces the error. For existing examples, please provide link.)

package com.demo.djl;

import ai.djl.Application;
import ai.djl.ModelException;
import ai.djl.inference.Predictor;
import ai.djl.ndarray.NDArray;
import ai.djl.ndarray.NDManager;
import ai.djl.repository.zoo.Criteria;
import ai.djl.repository.zoo.ZooModel;
import ai.djl.timeseries.Forecast;
import ai.djl.timeseries.TimeSeriesData;
import ai.djl.timeseries.dataset.FieldName;
import ai.djl.timeseries.translator.DeepARTranslator;
import ai.djl.training.util.ProgressBar;
import ai.djl.translate.TranslateException;
import com.google.gson.GsonBuilder;

import java.io.IOException;
import java.io.InputStreamReader;
import java.io.Reader;
import java.net.URL;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.time.LocalDateTime;
import java.time.ZoneId;
import java.util.Date;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
import java.util.zip.GZIPInputStream;

public class TimeSeriesTest {

    public static void main(String[] args) throws TranslateException, ModelException, IOException {
        predict();
    }

    public static float[] predict() throws IOException, TranslateException, ModelException {
        Map<String, Object> arguments = new ConcurrentHashMap<>();
        // set parameter
        arguments.put("prediction_length", 12);
        arguments.put("freq", "M");
        arguments.put("use_" + FieldName.FEAT_DYNAMIC_REAL.name().toLowerCase(), false);
        arguments.put("use_" + FieldName.FEAT_STATIC_CAT.name().toLowerCase(), false);
        arguments.put("use_" + FieldName.FEAT_STATIC_REAL.name().toLowerCase(), false);

        // build translator
        DeepARTranslator translator = DeepARTranslator.builder(arguments).build();

        // create criteria
        Criteria<TimeSeriesData, Forecast> criteria =
                Criteria.builder()
                        .optApplication(Application.TimeSeries.FORECASTING)
                        .setTypes(TimeSeriesData.class, Forecast.class)
//                        .optModelPath(Paths.get(modelUrl))
                        .optTranslator(translator)
                        .optProgress(new ProgressBar())
                        .build();

        // load model
        try (ZooModel<TimeSeriesData, Forecast> model = criteria.loadModel();
             Predictor<TimeSeriesData, Forecast> predictor = model.newPredictor()) {
            NDManager manager = model.getNDManager();

            AirPassengers ap = new AirPassengers(Paths.get("Not implemented"));
            TimeSeriesData data = ap.get(manager);

            // prediction
            Forecast forecast = predictor.predict(data);

            return forecast.mean().toFloatArray();
        }
    }

    public static class AirPassengers {

        private Path path;
        private AirPassengerData data;

        public AirPassengers(Path path) {
            this.path = path;
            prepare();
        }

        public TimeSeriesData get(NDManager manager) {
            LocalDateTime start =
                    data.start.toInstant().atZone(ZoneId.systemDefault()).toLocalDateTime();
            NDArray target = manager.create(data.target);
            TimeSeriesData ret = new TimeSeriesData(10);
            // A TimeSeriesData must contain start time and target value.
            ret.setStartTime(start);
            ret.setField(FieldName.TARGET, target);
            return ret;
        }


        private void prepare(){
            String airPassangers = "{\"start\":\"1949-01\",\"target\":[112.0,118.0,132.0,129.0,121.0,135.0,148.0,148.0,136.0,119.0,104.0,118.0,115.0,126.0,141.0,135.0,125.0,149.0,170.0,170.0,158.0,133.0,114.0,140.0,145.0,150.0,178.0,163.0,172.0,178.0,199.0,199.0,184.0,162.0,146.0,166.0,171.0,180.0,193.0,181.0,183.0,218.0,230.0,242.0,209.0,191.0,172.0,194.0,196.0,196.0,236.0,235.0,229.0,243.0,264.0,272.0,237.0,211.0,180.0,201.0,204.0,188.0,235.0,227.0,234.0,264.0,302.0,293.0,259.0,229.0,203.0,229.0,242.0,233.0,267.0,269.0,270.0,315.0,364.0,347.0,312.0,274.0,237.0,278.0,284.0,277.0,317.0,313.0,318.0,374.0,413.0,405.0,355.0,306.0,271.0,306.0,315.0,301.0,356.0,348.0,355.0,422.0,465.0,467.0,404.0,347.0,305.0,336.0,340.0,318.0,362.0,348.0,363.0,435.0,491.0,505.0,404.0,359.0,310.0,337.0,360.0,342.0,406.0,396.0,420.0,472.0,548.0,559.0,463.0,407.0,362.0,405.0,417.0,391.0,419.0,461.0,472.0,535.0,622.0,606.0,508.0,461.0,390.0,432.0]}";
            data =
                    new GsonBuilder()
                            .setDateFormat("yyyy-MM")
                            .create()
                            .fromJson(airPassangers, AirPassengerData.class);

        }

        private static class AirPassengerData {
            Date start;
            float[] target;
        }
    }

}

Steps to reproduce

(Paste the commands you ran that produced the error.)

1.run TimeSeriesTest.main()

What have you tried to solve it?

1.upgrade the pytorch version to 1.12.1

Environment Info

Please run the command ./gradlew debugEnv from the root directory of DJL (if necessary, clone DJL first). It will output information about your system, environment, and installation that can help us debug your issue. Paste the output of the command below:

    <properties>
        <maven.compiler.source>8</maven.compiler.source>
        <maven.compiler.target>8</maven.compiler.target>
        <djl.version>0.21.0</djl.version>
    </properties>

    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <configuration>
                    <source>11</source>
                    <target>11</target>
                </configuration>
            </plugin>
        </plugins>
    </build>

    <dependencyManagement>
        <dependencies>
            <dependency>
                <groupId>ai.djl</groupId>
                <artifactId>bom</artifactId>
                <version>${djl.version}</version>
                <type>pom</type>
                <scope>import</scope>
            </dependency>
        </dependencies>
    </dependencyManagement>

    <dependencies>
        <dependency>
            <groupId>ai.djl</groupId>
            <artifactId>api</artifactId>
            <version>${djl.version}</version>
        </dependency>
        <dependency>
            <groupId>ai.djl.pytorch</groupId>
            <artifactId>pytorch-model-zoo</artifactId>
            <version>${djl.version}</version>
        </dependency>
        <dependency>
            <groupId>ai.djl.pytorch</groupId>
            <artifactId>pytorch-engine</artifactId>
            <version>${djl.version}</version>
            <scope>runtime</scope>
        </dependency>
<!--        <dependency>
            <groupId>ai.djl.pytorch</groupId>
            <artifactId>pytorch-native-auto</artifactId>
            <version>1.9.1</version>
        </dependency>-->
        <dependency>
            <groupId>ai.djl.timeseries</groupId>
            <artifactId>timeseries</artifactId>
            <version>0.22.1</version>
        </dependency>

        <dependency>
            <groupId>ch.qos.logback</groupId>
            <artifactId>logback-classic</artifactId>
            <version>1.2.6</version>
        </dependency>

        <dependency>
            <groupId>ch.qos.logback</groupId>
            <artifactId>logback-core</artifactId>
            <version>1.2.6</version>
        </dependency>

        <dependency>
            <groupId>ai.djl</groupId>
            <artifactId>basicdataset</artifactId>
        </dependency>
        <dependency>
            <groupId>ai.djl</groupId>
            <artifactId>model-zoo</artifactId>
        </dependency>

        <dependency>
            <groupId>commons-cli</groupId>
            <artifactId>commons-cli</artifactId>
            <version>1.5.0</version>
        </dependency>

    </dependencies>

The text was updated successfully, but these errors were encountered:

KexinFeng · 2023-06-09T17:08:56Z

Is it exactly the same as the demo code?
https://github.com/deepjavalibrary/djl/blob/master/examples/src/test/java/ai/djl/examples/inference/TimeSeriesTest.java
https://github.com/deepjavalibrary/djl/blob/master/examples/src/main/java/ai/djl/examples/inference/timeseries/M5ForecastingDeepAR.java
https://github.com/deepjavalibrary/djl/blob/master/examples/src/main/java/ai/djl/examples/inference/timeseries/AirPassengersDeepAR.java
The demo code runs well. So you can check your code against the demo.

mengzhizihu · 2023-06-12T08:27:06Z

I just replace the json resolving code because I don't have the "data.json.gz" file.

origin:

 /** prepare the file data */
//        private void prepare() {
//            Path filePath = path.resolve("test").resolve("data.json.gz");
//            try {
//                URL url = filePath.toUri().toURL();
//                try (GZIPInputStream is = new GZIPInputStream(url.openStream())) {
//                    Reader reader = new InputStreamReader(is);
//                    data =
//                            new GsonBuilder()
//                                    .setDateFormat("yyyy-MM")
//                                    .create()
//                                    .fromJson(reader, AirPassengerData.class);
//                }
//            } catch (IOException e) {
//                throw new IllegalArgumentException("Invalid url: " + filePath, e);
//            }
//        }

replace:

        private void prepare(){
            String airPassangers = "{\"start\":\"1949-01\",\"target\":[112.0,118.0,132.0,129.0,121.0,135.0,148.0,148.0,136.0,119.0,104.0,118.0,115.0,126.0,141.0,135.0,125.0,149.0,170.0,170.0,158.0,133.0,114.0,140.0,145.0,150.0,178.0,163.0,172.0,178.0,199.0,199.0,184.0,162.0,146.0,166.0,171.0,180.0,193.0,181.0,183.0,218.0,230.0,242.0,209.0,191.0,172.0,194.0,196.0,196.0,236.0,235.0,229.0,243.0,264.0,272.0,237.0,211.0,180.0,201.0,204.0,188.0,235.0,227.0,234.0,264.0,302.0,293.0,259.0,229.0,203.0,229.0,242.0,233.0,267.0,269.0,270.0,315.0,364.0,347.0,312.0,274.0,237.0,278.0,284.0,277.0,317.0,313.0,318.0,374.0,413.0,405.0,355.0,306.0,271.0,306.0,315.0,301.0,356.0,348.0,355.0,422.0,465.0,467.0,404.0,347.0,305.0,336.0,340.0,318.0,362.0,348.0,363.0,435.0,491.0,505.0,404.0,359.0,310.0,337.0,360.0,342.0,406.0,396.0,420.0,472.0,548.0,559.0,463.0,407.0,362.0,405.0,417.0,391.0,419.0,461.0,472.0,535.0,622.0,606.0,508.0,461.0,390.0,432.0]}";
            data =
                    new GsonBuilder()
                            .setDateFormat("yyyy-MM")
                            .create()
                            .fromJson(airPassangers, AirPassengerData.class);

        }

KexinFeng · 2023-06-13T17:56:10Z

I notice that your demo is from the readme.md. Sorry that may be outdated. The reliable demo is that in the unit test as I sent above.
https://github.com/deepjavalibrary/djl/blob/master/examples/src/test/java/ai/djl/examples/inference/TimeSeriesTest.java
https://github.com/deepjavalibrary/djl/blob/master/examples/src/main/java/ai/djl/examples/inference/timeseries/M5ForecastingDeepAR.java
https://github.com/deepjavalibrary/djl/blob/master/examples/src/main/java/ai/djl/examples/inference/timeseries/AirPassengersDeepAR.java
The url of the air_passengers.json is also shown therein.

mengzhizihu · 2023-06-20T01:10:33Z

That works. Thxs a lot. It would be great if you could update the official demos on your website because it really confused me a bit time.

Fixes: deepjavalibrary#2641

Fixes: #2641

mengzhizihu added the bug Something isn't working label Jun 8, 2023

frankfliu mentioned this issue Jun 20, 2023

[timeseries] Updates timeseries README #2667

Merged

frankfliu added a commit to frankfliu/djl that referenced this issue Jun 20, 2023

[timeseries] Updates timeseries README

f978dbe

Fixes: deepjavalibrary#2641

frankfliu closed this as completed in #2667 Jun 20, 2023

frankfliu added a commit that referenced this issue Jun 20, 2023

[timeseries] Updates timeseries README (#2667)

892d8a5

Fixes: #2641

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Running TimeSeries Demo, got the TranslateException: ai.djl.engine.EngineException #2641

Running TimeSeries Demo, got the TranslateException: ai.djl.engine.EngineException #2641

mengzhizihu commented Jun 8, 2023 •

edited by KexinFeng

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KexinFeng commented Jun 9, 2023

mengzhizihu commented Jun 12, 2023 •

edited

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KexinFeng commented Jun 13, 2023

mengzhizihu commented Jun 20, 2023

Running TimeSeries Demo, got the TranslateException: ai.djl.engine.EngineException #2641

Running TimeSeries Demo, got the TranslateException: ai.djl.engine.EngineException #2641

Comments

mengzhizihu commented Jun 8, 2023 • edited by KexinFeng Loading

Description

Expected Behavior

Error Message

How to Reproduce?

Steps to reproduce

What have you tried to solve it?

Environment Info

KexinFeng commented Jun 9, 2023

mengzhizihu commented Jun 12, 2023 • edited Loading

KexinFeng commented Jun 13, 2023

mengzhizihu commented Jun 20, 2023

mengzhizihu commented Jun 8, 2023 •

edited by KexinFeng

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mengzhizihu commented Jun 12, 2023 •

edited

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