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ci/official/utilities/code_check_full.bats
setup_file() { bazel version # Start the bazel server } # Do a bazel query specifically for the licenses checker. It searches for # targets matching the provided query, which start with // or @ but not # //tensorflow (so it looks for //third_party, //external, etc.), and then # gathers the list of all packages (i.e. directories) which contain those # targets. license_query() {
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ci/official/utilities/repack_libtensorflow.sh
# under the root of srcjars jars created by bazel, rather than under # the maven-style src/main/java subdirectory. # # Bazel manages annotation generated source as follows: First, it # calls javac with options that create generated files under a # bazel-out directory. Next, it archives the generated source files # into a srcjar directly under the root. There doesn't appear to be a # simple way to parameterize this from bazel, hence this helper to
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ci/devinfra/README.md
# DevInfra CI Directory > **Warning** This folder is still under construction. It is part of an ongoing > effort to improve the structure of CI and build related files within the > 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
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.github/workflows/update-rbe.yml
function map() { # The "digest" that allows us to pull an image is not the digest as # returned by the API, but a sha256sum of the entire chunk of image # metadata. gcr.io helpfully includes it in the header of the response # as docker-content-digest: sha256:[digest]. Note we use egrep to # match exactly sha256:<hash> because curl may include a ^M symbol at # the end of the line.
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ci/official/wheel_test/test_import_api_packages.py
# ============================================================================== """Import API packages test. This is a Python test that verifies whether API v2 packages can be imported from the current build or not. It uses the `_api/v2/api_packages.txt` file from the local wheel file. The `_api/v2/api_packages.txt` file is created during the process of generating TensorFlow API v2 init files and is stored in the wheel file after the build.
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tensorflow/c/eager/BUILD
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ci/devinfra/docker_windows/Dockerfile
gcloud components install docker-credential-gcr kubectl gsutil; # Install cygwin and packages # Running a seperate ps1 file since when running inside a Dockerfile, it does # not work. COPY install/install_cygwin.ps1 c:/ RUN c:/install_cygwin.ps1; \ $old_path = [Environment]::GetEnvironmentVariable(\"PATH\", \"Machine\"); \
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ci/official/containers/linux_arm64/builder.devtoolset/stringop_trunc.patch
-# endif - -/* GCC < 3.0 optimizes memset(s, 0, n) but not bzero(s, n). - The optimization is broken before EGCS 1.1. - GCC 3.0+ has __builtin_bzero as well, but at least till GCC 3.4 - if it decides to call the library function, it calls memset - and not bzero. */ -# if __GNUC_PREREQ (2, 91) -# define __bzero(s, n) __builtin_memset (s, '\0', n) -# endif - +# define __bzero(s, n) __builtin_memset (s, '\0', n) #endif
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tensorflow/c/experimental/filesystem/plugins/posix/posix_filesystem.cc
} PosixFile; static void Cleanup(TF_RandomAccessFile* file) { auto posix_file = static_cast<PosixFile*>(file->plugin_file); close(posix_file->fd); // This would be safe to free using `free` directly as it is only opaque. // However, it is better to be consistent everywhere. plugin_memory_free(const_cast<char*>(posix_file->filename)); delete posix_file; } static int64_t Read(const TF_RandomAccessFile* file, uint64_t offset, size_t n,
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ci/official/utilities/setup.sh
# # Common setup for all TF scripts. # # Make as FEW changes to this file as possible. It should not contain utility # functions (except for tfrun); use dedicated scripts instead and reference them # 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."
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