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CITATION.cff
authors: - family-names: Abadi given-names: MartÃn - family-names: Agarwal given-names: Ashish - family-names: Barham given-names: Paul - family-names: Brevdo given-names: Eugene - family-names: Chen given-names: Zhifeng - family-names: Citro given-names: Craig - family-names: Corrado given-names: Greg S. - family-names: Davis given-names: Andy - family-names: Dean
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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
| sed -e 's|:.*||' \ | sort -u } # Verify that, given a build target and a license-list generator target, all of # the dependencies of that target which include a license notice file are then # included when generating that license. Necessary because the license targets # in TensorFlow are manually enumerated rather than generated automatically. do_external_licenses_check(){ BUILD_TARGET="$1" LICENSES_TARGET="$2"
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false # Change the value of CACHEBUSTER when upgrading the toolchain, or when testing # different compilation methods. E.g. for a PR to test a new CUDA version, set # the CACHEBUSTER to the PR number. build --action_env=CACHEBUSTER=20220325
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tensorflow/c/eager/c_api.h
// A tensorflow.ServerDef specifies remote workers (in addition to the current // workers name). Operations created in this context can then be executed on // any of these remote workers by setting an appropriate device. // // If the following is set, all servers identified by the // ServerDef must be up when the context is created. TF_CAPI_EXPORT extern void TFE_ContextSetServerDef(TFE_Context* ctx,
C - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Thu Apr 27 21:07:00 GMT 2023 - 22.8K bytes - Viewed (1) -
tensorflow/c/eager/immediate_execution_distributed_manager.h
class WorkerCacheInterface; class ImmediateExecutionDistributedManager { public: virtual ~ImmediateExecutionDistributedManager() {} // Set up distributed execution environment on local and remote tasks. // When `reset_context` is true, initialize new cluster context state based // on cluster configurations provided in `server_def`; otherwise, update // existing context state with the provided `server_def`. Contexts created
C - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Wed Feb 21 22:37:46 GMT 2024 - 2.9K bytes - Viewed (0) -
ci/official/requirements_updater/updater.sh
# limitations under the License. # ============================================================================== # script to run pip-compile for each requirement. # if there is a change in requirements.in then all lock files will be updated # accordingly # All commands run relative to this directory cd "$(dirname "${BASH_SOURCE[0]}")" mv BUILD.bazel BUILD SUPPORTED_VERSIONS=("3_9" "3_10" "3_11" "3_12")
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tensorflow/c/experimental/filesystem/plugins/posix/posix_filesystem_helper.cc
namespace tf_posix_filesystem { int TransferFileContents(const char* src, const char* dst, mode_t mode, off_t size) { int src_fd = open(src, O_RDONLY); if (src_fd < 0) return -1; // When creating file, use the same permissions as original mode_t open_mode = mode & (S_IRWXU | S_IRWXG | S_IRWXO); // O_WRONLY | O_CREAT | O_TRUNC: // Open file for write and if file does not exist, create the file.
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Thu Jan 16 05:36:52 GMT 2020 - 2.1K bytes - Viewed (1) -
.github/workflows/arm-ci-extended-cpp.yml
pyver: ['3.10'] steps: - name: Stop old running containers (if any) shell: bash run: | running_containers=$(docker ps -q) && \ if [[ $running_containers == "" ]]; then echo "No running containers"; else echo "Running container(s) found" && \ docker stop $running_containers; fi docker container prune -f
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.github/workflows/arm-cd.yml
steps: - name: Stop old running containers (if any) shell: bash run: | running_containers=$(docker ps -q) && \ if [[ $running_containers == "" ]]; then echo "No running containers"; else echo "Running container(s) found" && \ docker stop $running_containers; fi docker container prune -f
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tensorflow/c/experimental/filesystem/plugins/gcs/cleanup.h
#define TENSORFLOW_C_EXPERIMENTAL_FILESYSTEM_PLUGINS_GCS_CLEANUP_H_ #include <type_traits> #include <utility> namespace tf_gcs_filesystem { // A move-only RAII object that calls a stored cleanup functor when // destroyed. Cleanup<F> is the return type of gtl::MakeCleanup(F). template <typename F> class Cleanup { public: Cleanup() : released_(true), f_() {} template <typename G>
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