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.github/workflows/sigbuild-docker-presubmit.yml
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ci/official/README.md
# click to "Invocation Details" and find BUILD_CONFIG, which will contain a # "build_file" item that indicates the script used. ci/official/wheel.sh # Advanced: Select specific build/test targets with "any.sh". # TF_ANY_TARGETS=":your/target" TF_ANY_MODE="test" ci/official/any.sh # Afterwards: Examine the results, which will include: The bazel cache, # generated artifacts like .whl files, and "script.log", from the script.
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ci/official/utilities/code_check_changed_files.bats
git config --system --add safe.directory '*' git config --system protocol.file.allow always # Note that you could generate a list of all the affected targets with e.g.: # bazel query $(paste -sd "+" $BATS_FILE_TMPDIR/changed_files) --keep_going # Only shows Added, Changed, Modified, Renamed, and Type-changed files
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ci/official/envs/linux_x86_tpu
source ci/official/envs/linux_x86 TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_cpu_linux --config=tpu" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_tpu TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_tpu" TFCI_LIB_SUFFIX="-tpu-linux-x86_64" TFCI_WHL_BAZEL_TEST_ENABLE=0 TFCI_WHL_IMPORT_TEST_ENABLE=0 TFCI_WHL_SIZE_LIMIT=580M
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ci/official/envs/macos_arm64
# limitations under the License. # ============================================================================== TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_macos_arm64" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=macos_arm64 TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_INDEX_HTML_ENABLE=1 TFCI_LIB_SUFFIX="-cpu-darwin-arm64" TFCI_MACOS_BAZEL_TEST_DIR_ENABLE=1
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ci/official/containers/linux_arm64/build.sh
fi fi # Build for both JAX and TF usage. We do these in one place because they share # almost all of the same cache layers export DOCKER_BUILDKIT=1 for target in jax tf; do IMAGE="gcr.io/tensorflow-sigs/build-arm64:$target-$TAG" docker pull "$IMAGE" || true # Due to some flakiness of resources pulled in the build, allow the docker # command to reattempt build a few times in the case of failure (b/302558736)
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ci/official/utilities/setup_macos.sh
fi set -x # When cross-compiling with RBE, we need to copy the macOS sysroot to be # inside the TensorFlow root directory. We then define them as a filegroup # target inside "tensorflow/tools/toolchains/cross_compile/cc" so that Bazel # can register it as an input to compile/link actions and send it to the remote # VMs when needed.
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SECURITY.md
ways to detect malicious models/graphs/checkpoints, so the recommended way to mitigate the risk in this scenario is to sandbox the model execution. ### Hardware attacks Physical GPUs or TPUs can also be the target of attacks. [Published research](https://scholar.google.com/scholar?q=gpu+side+channel) shows that it might be possible to use side channel attacks on the GPU to leak data from other
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tensorflow/c/experimental/filesystem/plugins/posix/BUILD
"//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"], deps = [ ":posix_filesystem_impl",
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ci/official/wheel_test/WORKSPACE
python_version = TF_PYTHON_VERSION, ) load("@python//:defs.bzl", "interpreter") load("@rules_python//python:pip.bzl", "pip_parse") pip_parse( name = "pypi", python_interpreter_target = interpreter, requirements = "//:requirements_lock_" + TF_PYTHON_VERSION.replace(".", "_") + ".txt", ) load("@pypi//:requirements.bzl", "install_deps")
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