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Kubeflow Fairing SDK Reference

 来源:谷歌 浏览 377 扫码 分享 2020-04-19 10:02:37
  • Kubeflow Fairing SDK Reference

    Kubeflow Fairing SDK Reference

    Reference documentation for the Kubeflow Fairing SDK

    See the generated reference docs for the Kubeflow FairingSDK (hosted onRead the Docs).

    当前内容版权归 谷歌 或其关联方所有，如需对内容或内容相关联开源项目进行关注与资助，请访问 谷歌 .
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    • About
      • Kubeflow
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    • Getting Started
      • Kubeflow Overview
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      • Workstation Installation
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        • Deploy using MiniKF on GCP
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      • Set Up Your Notebooks
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        • Installation Options for Kubeflow Pipelines
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      • Understanding Pipelines
        • Overview of Kubeflow Pipelines
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        • Concepts
          • Pipeline
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          • Run Trigger
          • Step
          • Output Artifact
      • Building Pipelines with the SDK
        • Introduction to the Pipelines SDK
        • Install the Kubeflow Pipelines SDK
        • Build Components and Pipelines
        • Create Reusable Components
        • Build Lightweight Python Components
        • Best Practices for Designing Components
        • Pipeline Parameters
        • Python Based Visualizations
        • Visualize Results in the Pipelines UI
        • Pipeline Metrics
        • DSL Static Type Checking
        • DSL Recursion
        • GCP-specific Uses of the SDK
        • Manipulate Kubernetes Resources as Part of a Pipeline
        • Upgrading and Reinstalling
        • Samples and Tutorials
          • Experiment with the Pipelines Samples
          • Run a Cloud-specific Pipelines Tutorial
      • Reference
        • Component Specification
        • Pipelines API Reference
        • Pipelines SDK Reference
    • Fairing
      • Overview of Kubeflow Fairing
      • Install Kubeflow Fairing
      • Configure Kubeflow Fairing
        • Fairing on Azure
        • Fairing on GCP
        • Configure Kubeflow Fairing with Access to GCP
      • GCP Samples and Tutorials
      • Train and Deploy on GCP from a Local Notebook
      • Train and Deploy on GCP from a Kubeflow Notebook
        • Tutorials
        • Other Samples and Tutorials
        • Reference
        • Kubeflow Fairing SDK Reference
    • Kubeflow on AWS
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        • Upgrading and Reinstalling
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        • Using Preemptible VMs and GPUs on GCP
        • Pipelines End-to-end on GCP
        • Customizing Kubeflow on GKE
        • Using Your Own Domain
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        • Using Cloud Filestore
        • Securing Your Clusters
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        • End-to-end Kubeflow on GCP
        • Logging and monitoring
    • Components of Kubeflow
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      • Pipelines
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      • Training
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      • Miscellaneous
        • Metadata
        • Nuclio functions
    • Tutorials, Samples, and Shared Resources
      • Kubeflow Samples
      • Codelabs, Workshops, and Tutorials
      • Blog Posts
      • Videos
      • Shared Resources and Components
    • Further Setup and Troubleshooting
      • Accessing Kubeflow UIs
      • Virtual Developer Environments
      • Microk8s for Kubeflow
        • MiniKF
        • Minikube for Kubeflow
        • Configuring Kubeflow with kfctl and kustomize
        • Kubeflow On-prem in a Multi-node Kubernetes Cluster
        • Usage Reporting
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    • Upgrading Kubeflow
      • Upgrading a Kubeflow Deployment
    • Reference
      • Reference Overview
      • Dockerfile Locations
      • Katib Reference
        • Katib v1alpha3
        • Katib
      • Metadata Reference
        • Metadata API Reference
        • Kubeflow Metadata SDK Reference
      • PyTorchJob Reference
        • PyTorchJob v1
        • PyTorchJob
        • PyTorchJob v1beta2
        • PyTorchJob
      • TFJob Reference
      • TFJob v1
        • TFJob Common
        • TFJob TensorFlow
      • TFJob v1beta2
        • TFJob Common
        • TFJob TensorFlow
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