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ci/official/utilities/code_check_changed_files.bats
# Only shows Added, Changed, Modified, Renamed, and Type-changed files if [[ "$(git rev-parse --abbrev-ref HEAD)" == "pull_branch" ]]; then # TF's CI runs 'git fetch origin "pull/PR#/merge:pull_branch"' # To get the as-merged branch during the CI tests git diff --diff-filter ACMRT --name-only pull_branch^ pull_branch > $BATS_FILE_TMPDIR/changed_files else # If the branch is not present, then diff against origin/master
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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
add them to //tensorflow/tools/pip_package/BUILD. Otherwise, add the no_pip tag to the test, or change code_check_full.bats in the SIG Build repository. That's https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/tf_sig_build_dockerfiles/devel.usertools/code_check_full.bats Here are the affected tests: EOF while read dep; do echo "For dependency $dep:"
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CONTRIBUTING.md
pull requests are approved and pass continuous integration checks, a TensorFlow team member will apply `ready to pull` label to your change. This means we are working on getting your pull request submitted to our internal repository. After the change has been submitted internally, your pull request will be merged automatically on GitHub. If you want to contribute, start working through the TensorFlow codebase,
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ci/official/README.md
from the `envs` directory that is filled with configuration options: - Nightly jobs (Run nightly on the `nightly` branch) - Uses `wheel.sh`, `libtensorflow.sh`, `code_check_full.sh` - Continuous jobs (Run on every GitHub commit) - Uses `pycpp.sh` - Presubmit jobs (Run on every GitHub PR) - Uses `pycpp.sh`, `code_check_changed_files.sh`
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.github/ISSUE_TEMPLATE/tflite-in-play-services.md
the problem. **Any other info / logs** Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files
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.github/ISSUE_TEMPLATE/tflite-converter-issue.md
### 5. (optional) Any other info / logs
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ci/official/envs/linux_arm64
# despite lacking Nvidia CUDA support. TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_DOCKER_ENABLE=1 TFCI_DOCKER_IMAGE=gcr.io/tensorflow-sigs/build-arm64:tf-2-16-multi-python TFCI_DOCKER_PULL_ENABLE=1 TFCI_DOCKER_REBUILD_ARGS="--target=tf ci/official/containers/linux_arm64" TFCI_INDEX_HTML_ENABLE=1 TFCI_LIB_SUFFIX="-cpu-linux-arm64" TFCI_OUTPUT_DIR=build_output TFCI_WHL_AUDIT_ENABLE=1
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RELEASE.md
* `tf.data.Dataset.zip` now supports Python-style zipping, i.e. `Dataset.zip(a, b, c)`. * `tf.data.Dataset.shuffle` now supports `tf.data.UNKNOWN_CARDINALITY` When doing a "full shuffle" using `dataset = dataset.shuffle(dataset.cardinality())`. But remember, a "full shuffle" will load the full dataset into memory so that it can be shuffled, so make sure to only use this with small datasets or datasets of small objects (like filenames). * `tf.math`
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LICENSE
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. CONTRIBUTION AGREEMENT By contributing to the BVLC/caffe repository through pull-request, comment, or otherwise, the contributor releases their content to the
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tensorflow/BUILD
config_setting( name = "lite_protos_legacy", define_values = {"TENSORFLOW_PROTOS": "lite"}, visibility = ["//visibility:public"], ) config_setting( name = "full_protos", define_values = {"TENSORFLOW_PROTOS": "full"}, visibility = ["//visibility:public"], ) selects.config_setting_group( name = "lite_protos", match_any = [":lite_protos_legacy"],
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