Add experimental C API to access EagerContext context ID.
PiperOrigin-RevId: 317476439 Change-Id: I9e97bce61cf526695f0c903b5f4f837116fef455
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@ -60,6 +60,12 @@ void TFE_ContextDisableGraphCollection(TFE_Context* ctx) {
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context->SetShouldStoreGraphs(false);
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}
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uint64_t TFE_GetContextId(TFE_Context* ctx) {
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tensorflow::EagerContext* context =
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tensorflow::ContextFromInterface(tensorflow::unwrap(ctx));
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return context->GetContextId();
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}
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void TFE_MonitoringCounterCellIncrementBy(TFE_MonitoringCounterCell* cell,
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int64_t value) {
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cell->cell.IncrementBy(value);
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@ -300,6 +300,14 @@ TF_CAPI_EXPORT extern void TFE_ContextOptionsSetLazyRemoteInputsCopy(
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TF_CAPI_EXPORT extern void TFE_ContextOptionsSetTfrt(TFE_ContextOptions*,
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bool use_tfrt);
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// Returns the context_id from the EagerContext which is used by the
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// EagerService to maintain consistency between client and worker. The
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// context_id is initialized with a dummy value and is later set when the worker
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// is initialized (either locally or remotely). The context_id can change during
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// the process lifetime although this should cause the worker to be
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// reinitialized (e.g. cleared caches) as well.
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TF_CAPI_EXPORT extern uint64_t TFE_GetContextId(TFE_Context* ctx);
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// -----------------------------------------------------------------------------
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// Cancellation APIs.
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@ -461,6 +461,9 @@ PYBIND11_MODULE(_pywrap_tfe, m) {
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m.def("TFE_ContextClearCaches", [](py::handle& o) {
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TFE_ContextClearCaches(tensorflow::InputTFE_Context(o));
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});
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m.def("TFE_GetContextId", [](py::handle& ctx) {
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return TFE_GetContextId(tensorflow::InputTFE_Context(ctx));
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});
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m.def("TFE_ContextGetDevicePlacementPolicy", [](py::handle& ctx) {
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return TFE_ContextGetDevicePlacementPolicy(
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tensorflow::InputTFE_Context(ctx));
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