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ci/official/envs/linux_arm64_onednn
# limitations under the License. # ============================================================================== source ci/official/envs/linux_arm64
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.github/ISSUE_TEMPLATE/tflite-in-play-services.md
- Google Play Services version (`Settings` > `Apps` > `Google Play Services` > `App details`): **Standalone code to reproduce the issue** Provide a reproducible test case that is the bare minimum necessary to generate the problem. If possible, please share a link to or attach code demonstrating the problem. **Any other info / logs**
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ci/official/envs/macos_x86_cross_compile
TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config cross_compile_macos_x86" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=cross_compile_macos_x86 TFCI_MACOS_CROSS_COMPILE_ENABLE=1 TFCI_MACOS_CROSS_COMPILE_SDK_DEST="tensorflow/tools/toolchains/cross_compile/cc/MacOSX.sdk" TFCI_MACOS_CROSS_COMPILE_SDK_SOURCE="/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk"
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ci/official/utilities/cleanup_summary.sh
# Each failed target there will have its own representation, making failures # easier to find and read. function resultstore_extract { local \ XML_PATH="$TFCI_OUTPUT_DIR/Bazel_Test_and_Build_Results/sponge_log.xml" python3 \ "$TFCI_GIT_DIR/ci/official/utilities/extract_resultstore_links.py" \ "$TFCI_OUTPUT_DIR/script.log" \ --print \
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tensorflow/c/experimental/filesystem/plugins/gcs/expiring_lru_cache.h
const ComputeFunc& compute_func, TF_Status* status) { if (max_age_ == 0) { return compute_func(key, value, status); } // Note: we hold onto mu_ for the rest of this function. In practice, this // is okay, as stat requests are typically fast, and concurrent requests are // often for the same file. Future work can split this up into one lock per
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ci/official/utilities/setup_macos.sh
exit 1 fi # "TFCI_MACOS_BAZEL_TEST_DIR_PATH" specifies the directory that Bazel should use # when running tests. Each test will be executed in a separate subdirectory # inside this directory. TF Mac builds need ~150 GB of disk space to be able to # run all the tests. Since TFCI Mac VMs execute Bazel test commands in a # partition with insufficient storage, we specify the # 'TFCI_MACOS_BAZEL_TEST_DIR_PATH' environment variable to point to a partition
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ci/official/containers/linux_arm64/devel.usertools/repack_libtensorflow.sh
# simple way to parameterize this from bazel, hence this helper to # "normalize" the srcjar layout. # # Arguments: # src_jar - path to the original srcjar # dest_jar - path to the destination # Returns: # None function cp_normalized_srcjar() { src_jar="$1" dest_jar="$2" tmp_dir=$(mktemp -d) cp "${src_jar}" "${tmp_dir}/orig.jar" pushd "${tmp_dir}" # Extract any src/ files jar -xf "${tmp_dir}/orig.jar" src/
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tensorflow/c/eager/c_api_experimental.h
// and set the device name. It's effectively `TFE_OpSetDevice`, but it is faster // than separately calling it because if the existing op has the same // `raw_device_name`, it skips parsing and just leave as it is. TF_CAPI_EXPORT extern void TFE_OpReset(TFE_Op* op_to_reset, const char* op_or_function_name, const char* raw_device_name,
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ci/official/utilities/rename_and_verify_wheels.sh
fi # VERY basic check to ensure the [and-cuda] package variant is installable. # Checks TFCI_BAZEL_COMMON_ARGS for "gpu" or "cuda", implying that the test is # relevant. All of the GPU test machines have CUDA installed via other means, # so I am not sure how to verify that the dependencies themselves are valid for # the moment. if [[ "$TFCI_BAZEL_COMMON_ARGS" =~ gpu|cuda ]]; then echo "Checking to make sure tensorflow[and-cuda] is installable..."
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tensorflow/c/experimental/filesystem/modular_filesystem_registration.cc
// Copies a function table from plugin memory space to core memory space. // // This has three benefits: // * allows having newer plugins than the current core TensorFlow: the // additional entries in the plugin's table are just discarded; // * allows having older plugins than the current core TensorFlow (though // we are still warning users): the entries that core TensorFlow expects
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