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ci/official/README.md
# generated artifacts like .whl files, and "script.log", from the script. # Note that files created under Docker will be owned by "root". ls build_output ``` ## Contribution & Maintenance The TensorFlow team does not yet have guidelines in place for contributing to this directory. We are working on it. Please join a TF SIG Build meeting (see: bit.ly/tf-sig-build-notes) if you'd like to discuss the future of contributions.
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tensorflow/c/c_api.cc
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tensorflow/c/eager/c_api_experimental.h
// Creates a new eager Executor. Nodes in one executor are guaranteed to be // executed in sequence. Assigning nodes to different executors allows executing // nodes in parallel. // in_flight_nodes_limit: when is_async is true, this value controls the // maximum number of in flight async nodes. Enqueuing of additional async ops // after the limit is reached blocks until some inflight nodes finishes.
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tensorflow/c/experimental/grappler/grappler.h
typedef enum TF_TriState { TF_TriState_Default = 0, TF_TriState_Off, TF_TriState_On, } TF_TriState; // TF_GrapplerItem represents a combination of a graph, one of more fetch nodes, // and potentially a set of nodes to feed. typedef struct TF_GrapplerItem TF_GrapplerItem; // Flags indicating whether existing optimizers should be turned off. // It's optional for plugin to set functions to return true/false. If not
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tensorflow/c/eager/c_api.h
TF_Status* status); // Controls how to act when we try to run an operation on a given device but // some input tensors are not on that device. // LINT.IfChange // Note: Keep in sync with internal copy of enum in eager/context.h. typedef enum TFE_ContextDevicePlacementPolicy { // Running operations with input tensors on the wrong device will fail. TFE_DEVICE_PLACEMENT_EXPLICIT = 0,
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ci/official/envs/linux_arm64
TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_arm64_linux" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_arm64 # Note: this is not set to "--cpu", because that changes the package name # to tensorflow_cpu. These ARM builds are supposed to have the name "tensorflow" # despite lacking Nvidia CUDA support.
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tensorflow/c/experimental/grappler/grappler.cc
TF_SetStatus(status, TF_OK, ""); const std::unordered_set<std::string>& nodes = reinterpret_cast<const tensorflow::grappler::GrapplerItem*>(item) ->NodesToPreserve(); *num_values = nodes.size(); *storage_size = 0; for (const std::string& str : nodes) { *storage_size += str.size(); } }
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ci/official/containers/linux_arm64/Dockerfile
COPY devel.packages.txt /devel.packages.txt COPY cuda.packages.txt /cuda.packages.txt RUN /setup.sources.sh && /setup.packages.sh /devel.packages.txt # Install various tools. # - bats: bash unit testing framework # NOTE: v1.6.0 seems to have a bug that made "git" in setup_file break # - bazelisk: always use the correct bazel version # - buildifier: clean bazel build deps # - buildozer: clean bazel build deps
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tensorflow/api_template.__init__.py
The primary function of this module is to import all of the public TensorFlow interfaces into a single place. The interfaces themselves are located in sub-modules, as described below. Note that the file `__init__.py` in the TensorFlow source code tree is actually only a placeholder to enable test cases to run. The TensorFlow build replaces
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ci/official/requirements_updater/README.md
Instead, an independent Python toolchain is registered, ensuring the right dependencies are always used. \ See https://github.com/bazelbuild/rules_python/ for more details. ### Specifying the Python version Note: Only a number of minor Python versions are supported at any given time. By default, the lowest supported version is used. To set a different version, use the `TF_PYTHON_VERSION` environment variable, e.g. ```
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