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Kubeflow 0.7 Document
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Reference

 来源:谷歌 浏览 587 扫码 分享 2020-04-19 10:02:36
  • Reference
    • Kubeflow Fairing SDK Reference

    Reference

    Reference docs for Kubeflow Fairing

    Kubeflow Fairing SDK Reference

    Reference documentation for the Kubeflow Fairing SDK

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    • About
      • Kubeflow
      • Contributing to Kubeflow
      • Community
      • Events Calendar
      • Docs
      • Style Guide for the Kubeflow Docs
    • Getting Started
      • Kubeflow Overview
      • Installing Kubeflow
      • Cloud Installation
        • AWS for Kubeflow
        • Azure for Kubeflow
        • Google Cloud for Kubeflow
        • IBM Cloud Private for Kubeflow
      • Kubernetes Installation
        • Overview of Deployment on Existing Clusters
        • Kubeflow Deployment with kfctl_k8s_istio
        • Multi-user, auth-enabled Kubeflow with kfctl_existing_arrikto
      • Workstation Installation
        • Kubeflow on Linux
        • Kubeflow on Windows
        • Kubeflow on macOS
        • Deploy using MiniKF on GCP
    • Jupyter Notebooks
      • Overview of Jupyter Notebooks in Kubeflow
      • Set Up Your Notebooks
      • Create a Custom Jupyter Image
      • Submit Kubernetes Resources
      • Build a Docker Image on GCP
      • Troubleshooting Guide
    • Pipelines
      • Pipelines Quickstart
      • Installing Pipelines
        • Installation Options for Kubeflow Pipelines
        • Pipelines Standalone Deployment
      • Understanding Pipelines
        • Overview of Kubeflow Pipelines
        • Introduction to the Pipelines Interfaces
        • Concepts
          • Pipeline
          • Component
          • Graph
          • Experiment
          • Run and Recurring Run
          • 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
      • Deployment
      • Install Kubeflow
        • Uninstall Kubeflow
        • Customizing Kubeflow on AWS
        • Logging
        • Private Access
        • Authentication and TLS Support
        • Storage Options
        • Troubleshooting Deployments on Amazon EKS
        • Kubeflow on AWS Features
    • Kubeflow on Azure
      • Deployment
      • Install Kubeflow
        • Initial cluster setup for existing cluster
        • Uninstall Kubeflow
        • End-to-End Pipeline Example on Azure
        • Access Control for Azure Deployment
        • Troubleshooting Deployments on Azure AKS
    • Kubeflow on GCP
      • Deploying Kubeflow
      • Set up a GCP Project
        • Set up OAuth for Cloud IAP
        • Deploy using UI
        • Deploy using CLI
        • Monitor Cloud IAP Setup
        • Delete using CLI
        • Delete using GCP Console
        • Features of Kubeflow on GCP
      • Pipelines on GCP
      • Authenticating Pipelines to GCP
        • Upgrading and Reinstalling
        • Enabling GPU and TPU
        • Using Preemptible VMs and GPUs on GCP
        • Pipelines End-to-end on GCP
        • Customizing Kubeflow on GKE
        • Using Your Own Domain
        • Authenticating Kubeflow to GCP
        • Using Cloud Filestore
        • Securing Your Clusters
        • Troubleshooting Deployments on GKE
        • End-to-end Kubeflow on GCP
        • Logging and monitoring
    • Components of Kubeflow
      • Jupyter Notebooks
      • Central Dashboard
        • Central Dashboard
        • Registration Flow
      • Hyperparameter Tuning
        • Introduction to Katib
        • Getting started with Katib
        • Running an experiment
      • Pipelines
        • Pipelines
      • Serving
        • Overview
        • KFServing
        • Seldon Serving
        • NVIDIA TensorRT Inference Server
        • TensorFlow Serving
        • TensorFlow Batch Predict
        • PyTorch Serving
      • Training
        • Chainer Training
        • MPI Training
        • MXNet Training
        • PyTorch Training
        • TensorFlow Training (TFJob)
      • 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
        • Multi-user Isolation
        • Job Scheduling
        • Troubleshooting
    • 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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