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ci/official/wheel_test/README.md
## Wheel Test This directory is dedicated to tests that require a built TensorFlow wheel 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/official/envs/rbe
# it enables a derived --config setting. If RBE is not available (i.e. there # is no --config setting), bazel would fail and quit. This script does a quick # check This script checks for such errors early if ! grep "rbe_$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX" .bazelrc; then cat <<EOF ERROR: RBE was enabled via the 'rbe' env in the 'TFCI' variable. TFCI: $TFCI
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ci/official/utilities/get_versions.sh
export TF_VER_PATCH=$(awk '/#define TF_PATCH_VERSION/ {print $3}' tensorflow/core/public/version.h) # Note: in awk, "print $N" prints the Nth "field", where fields are strings separated # by whitespace. The flag "-F<x>" changes the behavior such that fields are now strings # separated by the character <x>. Therefore, -F\' (escaped single quote) means that field # $2 in <Tensor'flow'> is <flow>. This is useful for reading string literals like below.
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ci/official/utilities/setup.sh
# specifically. Use your best judgment to keep the scripts in this directory # lean and easy to follow. When in doubt, remember that for CI scripts, "keep it # simple" is MUCH more important than "don't repeat yourself." # -e: abort script if one command fails # -u: error if undefined variable used # -x: log all commands # -o pipefail: entire command fails if pipe fails. watch out for yes | ...
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ci/official/README.md
# your builds. This usually saves a lot of time, especially when # re-running tests. However, note that: # # - New environments like new CUDA versions, changes to manylinux, # compilers, etc. can cause undefined behavior such as build failures # or tests passing incorrectly. # - Automatic LLVM updates are known to extend build time even with # the cache; this is unavoidable. export TFCI=py311,linux_x86,public_cache,disk_cache
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SECURITY.md
targets of those operations, which could result in arbitrary read/write/executions. ### Running a TensorFlow server TensorFlow is a platform for distributed computing, and as such there is a TensorFlow server (`tf.train.Server`). The TensorFlow server is intended for internal communication only. It is not built for use in untrusted environments or networks.
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