Working through Chapter 3 of the Book - DataPoints.syntheticData gives UnsupportedOperationException: Dimension mismatch or high dimensional dot operation is not supported.

[juliangamble]

Hi Everyone,

Thanks for this great library. I hope this can lead to something helpful.

I'm working through Chapter 3 of the book - I'll include code to reproduce my experience below.

I'm getting an error

Exception in thread "main" java.lang.UnsupportedOperationException: Dimension mismatch or high dimensional dot operation is not supported. Please use .matMul instead.
	at ai.djl.pytorch.engine.PtNDArray.dot(PtNDArray.java:1353)
	at ai.djl.pytorch.engine.PtNDArray.dot(PtNDArray.java:39)
	at org.example.DataPoints.syntheticData(Ch3DimensionMismatchDemoBug.java:41)
	at org.example.Ch3DimensionMismatchDemoBug.main(Ch3DimensionMismatchDemoBug.java:16)

It seems to me that the approach using dot product in the book is not valid for the latest version of Pytorch, and that matmul should be used instead. Can someone give me a pointer as to how to replace this code in DataPoints to use matmul?

Cheers
Julian

pom.xml

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>org.example</groupId>
    <artifactId>MinimalDemoForDotProductBug</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <maven.compiler.source>11</maven.compiler.source>
        <maven.compiler.target>11</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>
    <dependencies>
        <dependency>
            <groupId>ai.djl</groupId>
            <artifactId>api</artifactId>
            <version>0.22.1</version>
        </dependency>
        <dependency>
            <groupId>ai.djl.pytorch</groupId>
            <artifactId>pytorch-engine</artifactId>
            <version>0.22.1</version>
        </dependency>
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-api</artifactId>
            <version>2.0.7</version>
        </dependency>
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-simple</artifactId>
            <version>2.0.7</version>
        </dependency>
    </dependencies>

</project>

---

Ch3DimensionMismatchDemoBug.java

package org.example;


import ai.djl.ndarray.NDArray;
import ai.djl.ndarray.NDManager;
import ai.djl.ndarray.types.DataType;
import ai.djl.ndarray.types.Shape;

public class Ch3DimensionMismatchDemoBug {
    public static void main(String[] args) {
        NDManager manager = NDManager.newBaseManager();

        NDArray trueW = manager.create(new float[]{2, -3.4f});
        float trueB = 4.2f;

        DataPoints dp = DataPoints.syntheticData(manager, trueW, trueB, 1000);
    }
}

class DataPoints {

    private NDArray X;
    private NDArray y;

    public DataPoints(NDArray X, NDArray y) {
        this.X = X;
        this.y = y;
    }

    public NDArray getX() {
        return X;
    }

    public NDArray getY() {
        return y;
    }

    // Generate y = X w + b + noise
    public static DataPoints syntheticData(NDManager manager, NDArray w, float b, int numExamples) {
        NDArray X = manager.randomNormal(new Shape(numExamples, w.size()));
        NDArray y = X.dot(w).add(b);
        // Add noise
        y = y.add(manager.randomNormal(0, 0.01f, y.getShape(), DataType.FLOAT32));
        return new DataPoints(X, y);
    }
}