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## Cloud Build will build and publish a custom image for running the training job the Vertex Pipeline Component (Finetuning with Dreambooth) 1. ** Enable Necessary APIs ** : Make sure that the required APIs are enabled for your project gcloud services enable artifactregistry.googleapis.com container.googleapis.com aiplatform.googleapis.com 2. ** Create a repo for your container artifacts ** BUILD_REGIST='your-repo-name' 3. ** Update the service account key path in the Dockerfile ** ENV GOOGLE_APPLICATION_CREDENTIALS="YOUR_SERVICE_ACCOUNT_KEY_PATH" 4. ** Replace the values in the cloud-build-config.yaml file with your values (YOUR_IMAGE and YOUR_TAG can be newly added. You should already have the values for the other components - YOUR_HOSTNAME, YOUR_PROJECT_ID and YOUR_REPOSITORY) # Build the custom container image - name: 'gcr.io/cloud-builders/docker' args: ['build', '-t', 'YOUR_HOSTNAME/YOUR_PROJECT_ID/YOUR_CREREPOSITORY/YOUR_IMAGE:YOUR_TAG', '.'] # Push the image to Artifact Registry - name: 'gcr.io/cloud-builders/docker' args: ['push', 'YOUR_HOSTNAME/YOUR_PROJECT_ID/YOUR_REPOSITORY/YOUR_IMAGE:YOUR_TAG'] options: machineType: 'N1_HIGHCPU_8' diskSizeGb: '200' 5. ** Build your component image by running the Cloud build command ** gcloud builds submit --config cloud-build-config.yaml .