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tensorflow/c/eager/immediate_execution_distributed_manager.h
// 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 // on remote tasks will be considered stale and garbage collected after // `keep_alive_secs` of inactivity.
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tensorflow/c/c_op_requires.h
// Convenience macros for asserting and handling exceptional conditions, for // C structs, including `TF_OpKernelContext`, `TF_Status`, etc. This is analogus // to the macros in tensorflow/core/framework/op_requires.h. This is provided // for plugin OpKernel developer's convenience. #define C_OPKERNELCONTEXT_REQUIRES_OK(CTX, C_STATUS, __VA_ARGS__) \ do { \
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tensorflow/c/eager/immediate_execution_tensor_handle.h
// metadata and synchronization. // // This allows us to hide concrete implementations of TensorHandle from header // files. The interface lists the common functionality that must be provided by // any concrete implementation. However, in cases where the true concrete class // is needed a static_cast can be applied. class ImmediateExecutionTensorHandle : public AbstractTensorHandle { public:
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ci/official/wheel_test/README.md
to the `../wheel_test/` directory. ### How it Works in the Presubmit Job `_requirements_lock` files will be generated by the presubmit job. A detailed description will be provided once it's integrated into presubmit. ### test_import_api_packages This Python test verifies whether the API v2 packages can be imported from the
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tensorflow/c/c_api_test.cc
} void TestGradientsSuccess(bool grad_inputs_provided) { TF_Output inputs[2]; TF_Output outputs[1]; TF_Output grad_outputs[2]; TF_Output expected_grad_outputs[2]; BuildSuccessGraph(inputs, outputs); BuildExpectedGraph(grad_inputs_provided, expected_grad_outputs); AddGradients(grad_inputs_provided, nullptr, inputs, 2, outputs, 1, grad_outputs);
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tensorflow/c/experimental/filesystem/modular_filesystem_test.cc
// only requests schemes that don't exist, first instantiation of the test would // filter out all the user provided schemes (as they are not registered) but // subsequent instantiations would return all registered schemes (since the // vector with the user provided schemes is cleared). static std::vector<std::string>* GetSchemesFromUserOrEnv() { std::vector<std::string>* all_schemes = new std::vector<std::string>;
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tensorflow/c/eager/c_api.h
// found in the provided `op`. TF_CAPI_EXPORT extern int TFE_OpGetInputLength(TFE_Op* op, const char* input_name, TF_Status* status); // Returns the length (number of tensors) of the output argument `output_name` // found in the provided `op`. TF_CAPI_EXPORT extern int TFE_OpGetOutputLength(TFE_Op* op,
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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
setup_file() { cd /tf/tensorflow bazel version # Start the bazel server } # Do a bazel query specifically for the licenses checker. It searches for # targets matching the provided query, which start with // or @ but not # //tensorflow (so it looks for //third_party, //external, etc.), and then # gathers the list of all packages (i.e. directories) which contain those # targets. license_query() {
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tensorflow/c/eager/parallel_device/parallel_device_lib.h
const ParallelDevice& device_; std::vector<TensorHandlePtr> tensors_; // Parallel tensors are immutable but compute their shape lazily unless it is // provided on construction. The optional has a value if the lazy computation // has been completed or the shape was provided on construction. mutable absl::optional<std::vector<int64_t>> shape_; const TF_DataType dtype_; }; template <typename DataType>
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tensorflow/c/c_api.cc
if (n == nullptr) continue; // Adding the gradients to the graph can alter the prefix to prevent // name collisions only if this prefix has not been provided explicitly // by the user. If it was provided, assert that it remained intact. if (prefix != nullptr && !absl::StartsWith(n->name(), prefix_cmp)) { status->status = tensorflow::errors::Internal(
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