How to do deep learning for java on the Valohai platform? -blog | Valohai

valohai.yaml

---

- step:
    name: Build-dl4j-mnist-single-layer-java-app
    image: neomatrix369/dl4j-mnist-single-layer:v0.5
    command:
      - cd ${VH_REPOSITORY_DIR}
      - ./buildUberJar.sh
      - echo "~~~ Copying the build jar file into ${VH_OUTPUTS_DIR}"
      - cp target/MLPMnist-1.0.0-bin.jar ${VH_OUTPUTS_DIR}/MLPMnist-1.0.0.jar
      - ls -lash ${VH_OUTPUTS_DIR}
    environment: aws-eu-west-1-g2-2xlarge
- step:
    name: Run-dl4j-mnist-single-layer-train-model
    image: neomatrix369/dl4j-mnist-single-layer:v0.5
    command:
      - echo "~~~ Unpack the MNist dataset into ${HOME} folder"
      - tar xvzf ${VH_INPUTS_DIR}/dataset/mlp-mnist-dataset.tgz -C ${HOME}
      - cd ${VH_REPOSITORY_DIR}
      - echo "~~~ Copying the build jar file from ${VH_INPUTS_DIR} to current location"
      - cp ${VH_INPUTS_DIR}/dl4j-java-app/MLPMnist-1.0.0.jar .
      - echo "~~~ Run the DL4J app to train model based on the the MNist dataset"
      - ./runMLPMnist.sh {parameters}
    inputs:
      - name: dl4j-java-app
        description: DL4J Java app file (jar) generated in the previous step 'Build-dl4j-mnist-single-layer-java-app'
      - name: dataset
        default: https://github.com/neomatrix369/awesome-ai-ml-dl/releases/download/mnist-dataset-v0.1/mlp-mnist-dataset.tgz
        description: MNist dataset needed to train the model
    parameters:
      - name: --action
        pass-as: '--action {v}'
        type: string
        default: train
        description: Action to perform i.e. train or evaluate
      - name: --output-dir
        pass-as: '--output-dir {v}'
        type: string
        default: /valohai/outputs/
        description: Output directory where the model will be created, best to pick the Valohai output directory
    environment: aws-eu-west-1-g2-2xlarge

- step:
    name: Run-dl4j-mnist-single-layer-evaluate-model
    image: neomatrix369/dl4j-mnist-single-layer:v0.5
    command:
      - cd ${VH_REPOSITORY_DIR}
      - echo "~~~ Copying the build jar file from ${VH_INPUTS_DIR} to current location"
      - cp ${VH_INPUTS_DIR}/dl4j-java-app/MLPMnist-1.0.0.jar .
      - echo "~~~ Run the DL4J app to evaluate the trained MNist model"
      - ./runMLPMnist.sh {parameters}
    inputs:
      - name: dl4j-java-app
        description: DL4J Java app file (jar) generated in the previous step 'Build-dl4j-mnist-single-layer-java-app'    
      - name: model
        description: Model file generated in the previous step 'Run-dl4j-mnist-single-layer-train-model'
    parameters:
      - name: --action
        pass-as: '--action {v}'
        type: string
        default: evaluate
        description: Action to perform i.e. train or evaluate
      - name: --input-dir
        pass-as: '--input-dir {v}'
        type: string
        default: /valohai/inputs/model
        description: Input directory where the model created by the previous step can be found created
    environment: aws-eu-west-1-g2-2xlarge