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  1. README.md

        period. The last release to remove non-`@Beta` APIs was Guava 21.0.) Even
        `@Deprecated` APIs will remain (again, unless they are `@Beta`). We have no
        plans to start removing things again, but officially, we're leaving our
        options open in case of surprises (like, say, a serious security problem).
    
    3.  Guava has one dependency that is needed for linkage at runtime:
        `com.google.guava:failureaccess:1.0.2`. It also has
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  2. manifests/charts/gateway/README.md

    If you install with `helm install istio-gateway istio/gateway`, resources will be named `istio-gateway` and the `selector` labels set to:
    
    ```yaml
    app: istio-gateway
    istio: gateway # the release name with leading istio- prefix stripped
    ```
    
    If your existing installation doesn't follow these names, you can override them. For example, if you have resources named `my-custom-gateway` with `selector` labels
    `foo=bar,istio=ingressgateway`:
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  3. README.md

    MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads.
    
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  4. docs/erasure/README.md

    and still the data remains safe. Further, MinIO's erasure code is at the object level and can heal one object at a time. For RAID, healing can be done only at the volume level which translates into high downtime. As MinIO encodes each object individually, it can heal objects incrementally. Storage servers once deployed should not require drive replacement or healing for the lifetime of the server. MinIO's erasure coded backend is designed for operational efficiency and takes full advantage of hardware...
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  5. README.md

    ------------------- |
    [![Documentation](https://img.shields.io/badge/api-reference-blue.svg)](https://www.tensorflow.org/api_docs/) |
    
    [TensorFlow](https://www.tensorflow.org/) is an end-to-end open source platform
    for machine learning. It has a comprehensive, flexible ecosystem of
    [tools](https://www.tensorflow.org/resources/tools),
    [libraries](https://www.tensorflow.org/resources/libraries-extensions), and
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