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docs/en/docs/features.md
### Short It has sensible **defaults** for everything, with optional configurations everywhere. All the parameters can be fine-tuned to do what you need and to define the API you need. But by default, it all **"just works"**. ### Validation * Validation for most (or all?) Python **data types**, including: * JSON objects (`dict`).
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architecture/ambient/ztunnel.md
This offered performance benefits that were too large to leave on the table, as well as opportunities to tune to our specific needs. ## Configuration protocol Ztunnel, of course, needs to be dynamically configured in order to make decisions on how it should handle traffic.
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docs/en/docs/deployment/docker.md
Here are some examples of when that could make sense: #### A Simple App You could want a process manager in the container if your application is **simple enough** that you don't need (at least not yet) to fine-tune the number of processes too much, and you can just use an automated default (with the official Docker image), and you are running it on a **single server**, not a cluster. #### Docker Compose
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.bazelrc
build:linux --copt="-Wswitch" build:linux --copt="-Werror=switch" # Required for building with clang build:linux --copt="-Wno-error=unused-but-set-variable" # Linux ARM64 specific options build:linux_arm64 --copt="-mtune=generic" --copt="-march=armv8-a" --copt="-O3" # On Windows, `__cplusplus` is wrongly defined without this switch # See https://devblogs.microsoft.com/cppblog/msvc-now-correctly-reports-__cplusplus/
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RELEASE.md
under `tf.keras.dtensor` in this release (refer to the `tf.keras` entry). The tutoral and guide for DTensor will be published on https://www.tensorflow.org/. Please stay tuned. * [oneDNN CPU performance optimizations](https://github.com/tensorflow/community/blob/master/rfcs/20210930-enable-onednn-ops.md) are available in Linux x86, Windows x86, and Linux aarch64 packages.
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doc/go_spec.html
and may explain why type inference fails in unusual code situations. But by and large these rules can be ignored when writing Go code: type inference is designed to mostly "work as expected", and the unification rules are fine-tuned accordingly. </p> <p> Type unification is controlled by a <i>matching mode</i>, which may be <i>exact</i> or <i>loose</i>. As unification recursively descends a composite type structure,
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