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---
- 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
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