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ci/official/wheel_test/README.md
file for testing, such as: * Ensuring the entire API is importable * Testing downstream projects against the wheel Ensure you have Bazel installed and accessible from your command line. These tests use hermetic Python. They also require a built TensorFlow wheel file and a requirements_lock file. The requirements_lock file is generated by the
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ci/devinfra/README.md
> TensorFlow repo. This warning will be removed when the contents of this > directory are stable and appropriate documentation around its usage is in > place. Maintainer: TensorFlow DevInfra Issue Reporting: File an issue against this repo and tag [@devinfra](https://github.com/orgs/tensorflow/teams/devinfra) ********************************************************************************
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README.md
conflicts. * Run TensorFlow tests and ensure they pass. * [Build](https://www.tensorflow.org/install/source) the TensorFlow pip package from source. ## Continuous build status You can find more community-supported platforms and configurations in the [TensorFlow SIG Build community builds table](https://github.com/tensorflow/build#community-supported-tensorflow-builds). ### Official Builds
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ci/official/README.md
# # To use RBE, you must first run `gcloud auth application-default login`, then: export TFCI=py311,linux_x86,rbe # Finally: Run your script of choice. # If you've clicked on a test result from our CI (via a dashboard or GitHub link), # click to "Invocation Details" and find BUILD_CONFIG, which will contain a # "build_file" item that indicates the script used.
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ci/official/requirements_updater/README.md
It takes in a file with a set of dependencies, and produces a more detailed requirements file for each version, with hashes specified for each dependency required, as well as their sub-dependencies. ### How to update/add requirements By default, the name of the base requirements file is `requirements.in`, but it can be set using the `REQUIREMENTS_FILE_NAME` variable. \ For example: ```
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tensorflow/c/experimental/ops/README.md
category names correspond to generated source file names, and should be consistent with the original source files registering each operator. For example since `REGISTER_OP("MatMul")` appears in ***core/math_ops.cc***, the "MatMul" operator in the script should be in the "math" category, and it will be generated in the output file `c/experimental/ops/math_ops.cc`.
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