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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
test --test_summary=short # "nonpip" tests are regular py_test tests. # Pass --config=nonpip to run the same suite of tests. If you want to run just # one test for investigation, you don't need --config=nonpip; just run the # bazel test invocation as normal. test:nonpip_filters --test_tag_filters=-no_oss,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_aarch64,-no_oss_py38,-no_oss_py39,-no_oss_py310
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tensorflow/c/eager/parallel_device/BUILD
licenses = ["notice"], ) # Currently pybind extension shared objects must use only C API headers since # the C API has static initializers duplicated in the Python bindings. So we # need a second rule that omits .cc files, in # tensorflow/python:_pywrap_parallel_device. filegroup( name = "lib_headers", srcs = ["parallel_device_lib.h"], ) filegroup( name = "lib_sources",
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ci/official/debug_tfci.sh
# ============================================================================== # This script dumps some information about the environment. It's most useful # for verifying changes to the TFCI scripts system, and most users won't need # to interact with it at all. source "${BASH_SOURCE%/*}/utilities/setup.sh" echo "==TFCI== env outside of tfrun:" env echo "==TFCI== env inside of tfrun:"
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.github/workflows/osv-scanner-scheduled.yml
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' uses: "google/osv-scanner-action/.github/workflows/osv-scanner-reusable.yml@v1.6.2-beta1" with:
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
test --test_summary=short # "nonpip" tests are regular py_test tests. # Pass --config=nonpip to run the same suite of tests. If you want to run just # one test for investigation, you don't need --config=nonpip; just run the # bazel test invocation as normal. test:nonpip_filters --test_tag_filters=-no_oss,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_aarch64,-no_oss_py38,-no_oss_py39,-no_oss_py310
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ci/official/containers/linux_arm64/Dockerfile
RUN mkdir -p /tf/venv RUN chown -R buildslave:buildslave /tf RUN dpkg -i /patchelf/patchelf_0.14.3-1_arm64.deb # All lines past this point are reset when $CACHEBUSTER is set. We need this # for Python specifically because we install some nightly packages which are # likely to change daily. ARG CACHEBUSTER=0 RUN echo $CACHEBUSTER # Setup build and environment COPY devel.usertools /usertools
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ci/official/containers/linux_arm64/builder.patchelf/build_patchelf.sh
# See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== # Need a newer version of patchelf as the installed version is buggy in 20.04 # so get patchelf source from 22.04 ie 'jammy' and build it to avoid dependency # problems that would occur with a binary package mkdir -p /patchelf
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ci/official/containers/linux_arm64/devel.usertools/rename_and_verify_wheels.sh
set -euxo pipefail for wheel in /tf/pkg/*.whl; do echo "Checking and renaming $wheel..." time python3 -m auditwheel repair --plat manylinux2014_aarch64 "$wheel" --wheel-dir /tf/pkg 2>&1 | tee check.txt # We don't need the original wheel if it was renamed new_wheel=$(grep --extended-regexp --only-matching '/tf/pkg/\S+.whl' check.txt) if [[ "$new_wheel" != "$wheel" ]]; then rm "$wheel" wheel="$new_wheel" fi
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ci/official/README.md
# destroys some temporary bazel data and causes longer builds. # # You will need the NVIDIA Container Toolkit for GPU testing: # https://github.com/NVIDIA/nvidia-container-toolkit # # Note: if you interrupt a bazel command on docker (ctrl-c), you # will need to run `docker exec tf pkill bazel` to quit bazel. # # Note: new files created from the container are owned by "root".
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.github/bot_config.yml
* It has an added advantage since you can you easily switch to different hardware accelerators (cpu, gpu, tpu) as per the task. * All you need is a good internet connection and you are all set. * Try to build TF from sources by changing CPU optimization flags. *Please let us know if this helps.* windows_comment: >
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