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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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.github/workflows/issue-on-pr-rollback.yml
uses: actions/github-script@d556feaca394842dc55e4734bf3bb9f685482fa0 # v6.3.3 with: github-token: ${{secrets.GITHUB_TOKEN}} script: | const script = require('./.github/workflows/create_issue.js')
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.github/workflows/osv-scanner-scheduled.yml
# limitations under the License. # ============================================================================== name: OSV-Scanner Scheduled Scan on: schedule: - cron: 0 4 * * 1 permissions: # Require writing security events to upload SARIF file to security tab security-events: write # Only need to read contents contents: read jobs: scan-scheduled: if: github.repository == 'tensorflow/tensorflow'
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ci/official/envs/public_cache_push
# limitations under the License. # ============================================================================== # Sourcing this enables Bazel remote cache (read and write) # Note that "_push" cache configs write to GCS buckets and require # authentication. If you are not a Googler, source "public_cache" to enable the # public read-only cache. # The cache configs are different for MacOS and Linux if [[ $(uname -s) == "Darwin" ]]; then
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.github/workflows/trusted-partners.yml
uses: actions/github-script@d556feaca394842dc55e4734bf3bb9f685482fa0 # v6.3.3 with: github-token: ${{ secrets.GITHUB_TOKEN }} script: | const script = require('./.github/workflows/trusted_partners.js'); const username = context.payload.pull_request.user.login; const domain = await script.get_email_domain({github, username}); switch(domain) {
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ci/official/requirements_updater/README.md
`release_updater.sh` 5) Run the `updater.sh` shell script. \ If the base requirements file hasn't yet been updated to account for the new Python version, which will require different versions for at least some dependencies, it will need to be updated now, for the script to run successfully. 6) A new `requirements_lock_3_11.txt` file should appear under the root of the
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ci/official/utilities/setup_macos.sh
# scripts. By setting "expand_aliases", we enable alias expansion in # non-interactive shells as well. shopt -s expand_aliases else echo '==TFCI==: Error: Cannot find path to grealpath or gstat' echo 'TF CI scripts require GNU core utilties to be installed. Please make' echo 'sure they are present on your system and try again.' exit 1 fi # "TFCI_MACOS_BAZEL_TEST_DIR_PATH" specifies the directory that Bazel should use
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ci/official/containers/linux_arm64/builder.devtoolset/build_devtoolset.sh
# Download glibc's shared and development libraries based on the value of the # `VERSION` parameter. # Note: 'Templatizing' this and the other conditional branches would require # defining several variables (version, os, path) making it difficult to maintain # and extend for future modifications. mkdir -p glibc-src mkdir -p glibc-build cd glibc-src
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tensorflow/c/experimental/filesystem/plugins/posix/BUILD
"//tensorflow/c:tf_file_statistics", "//tensorflow/c:tf_status", "//tensorflow/c/experimental/filesystem:filesystem_interface", ], ) # Since building pip package and API tests require a filesystem, we provide a # static registration target that they should link against. cc_library( name = "posix_filesystem_static", srcs = ["posix_filesystem_static.cc"], visibility = ["//visibility:public"],
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SECURITY.md
are skipped, and any checks implemented inside the shape inference code are not executed. The security impact of skipping those checks should be low, since the attack scenario would require a malicious user to be able to control the model which as stated above is already equivalent to code execution. In any case, the recommendation is not to serve models using Eager mode since it also has performance limitations.
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