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tensorflow/c/eager/immediate_execution_distributed_manager.h
// Check if the remote task is alive. virtual Status CheckRemoteAlive(const std::string& remote_task_name, bool* is_alive) = 0; // Get pointer to the coordination service agent instance. virtual tsl::CoordinationServiceAgent* GetCoordinationServiceAgent() = 0; }; } // namespace tensorflow
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
# > on the host machine. If we don't have --distinct_host_configuration=false, # > the core TensorFlow code will be built once for the host and once for the # > target platform. # See also https://docs.bazel.build/versions/master/guide.html#build-configurations-and-cross-compilation build --distinct_host_configuration=false # Disable clang extension that rejects type definitions within offsetof.
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tensorflow/c/eager/abstract_operation.h
// clients from directly destroying this object since it may manage it's own // lifetime through ref counting. Thus this must be allocated on the heap and // clients MUST call Release() in order to destroy an instance of this class. virtual void Release() = 0; virtual Status Reset(const char* op, const char* raw_device_name) = 0; virtual const string& Name() const = 0; // Returns the operation's device name. //
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tensorflow/c/c_api.cc
if (!status->status.ok()) return nullptr; // Create a TF_Graph from the MetaGraphDef. This is safe as long as Session // extends using GraphDefs. The Graph instance is different, but equivalent // to the one used to create the session. // // TODO(jhseu): When Session is modified to take Graphs instead of // GraphDefs, return the Graph generated in LoadSavedModel().
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tensorflow/c/eager/abstract_op_attrs.h
class AbstractOpAttrs { protected: enum AbstractOpAttrsKind { kEager, kTfrt }; explicit AbstractOpAttrs(AbstractOpAttrsKind kind) : kind_(kind) {} public: // Returns which subclass is this instance of. AbstractOpAttrsKind getKind() const { return kind_; } virtual ~AbstractOpAttrs() = default; // Returns the AbstractFunction as a FunctionDef. virtual void GetNameAttrList(
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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
# > on the host machine. If we don't have --distinct_host_configuration=false, # > the core TensorFlow code will be built once for the host and once for the # > target platform. # See also https://docs.bazel.build/versions/master/guide.html#build-configurations-and-cross-compilation build --distinct_host_configuration=false # Store performance profiling log in the mounted artifact directory.
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ci/official/wheel_test/README.md
the local wheel file specified in the `requirements_lock_<python_version>.txt`. Packages are imported one by one in alphabetical order during runtime. The test doesn't identify package's order-dependent issues; for instance, importing "tf.foo" followed by "tf.bar" won't reveal that "tf.bar" depends on "tf.foo" being imported first. The `_api/v2/api_packages.txt` file is generated during the TensorFlow API v2
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tensorflow/c/eager/abstract_function.h
protected: enum AbstractFunctionKind { kGraph, kMlir }; explicit AbstractFunction(AbstractFunctionKind kind) : kind_(kind) {} public: // Returns which subclass is this instance of. AbstractFunctionKind getKind() const { return kind_; } // Returns the AbstractFunction as a FunctionDef. virtual Status GetFunctionDef(const FunctionDef**) = 0;
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.bazelrc
build:rbe_linux_cpu --python_path="/usr/bin/python3" # These you may need to change for your own GCP project. common:rbe_linux_cpu --remote_instance_name=projects/tensorflow-testing/instances/default_instance # TODO(kanglan): Remove it after toolchain update is complete. build:rbe_linux_cpu_old --config=rbe_linux
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tensorflow/c/eager/parallel_device/parallel_device_lib_test.cc
{{"y"}, "CollectiveReduce", {"x"}, {{"T", DT_FLOAT}, {"group_size", static_cast<int>(devices.size())}, {"group_key", 0}, {"instance_key", 0}, {"merge_op", "Add"}, {"final_op", "Id"}, {"subdiv_offsets", std::vector<int>()}}, /*dep=*/{"assert"}}, });
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