*   Improvements to the TensorFlow debugging experience:

    *   Previously, TensorFlow error stack traces involved many internal frames,
        which could be challenging to read through, while not being actionable
        for end users. As of TF 2.7, TensorFlow filters internal frames in most
        errors that it raises, to keep stack traces short, readable, and focused
        on what's actionable for end users (their own code).

          NodeDef* const node_def = graph_def.add_node();
          *node_def = node->def();
        }
      }
      *graph_def.mutable_library() = graph.flib_def().ToProto();
      if (flags::Global().more_stack_traces.value()) {
        *graph_def.mutable_debug_info() = graph.BuildDebugInfo();
      }
      session->graph->mu.unlock();
      status->status = session->session->Extend(std::move(graph_def));

    return;
  }

  AnnotateEagerRuntimeConstructionContext(*fdef_or.value());
  status->status = tensorflow::unwrap(ctx)->AddFunctionDefWithStackTraces(
      *fdef_or.value(), function->record->stack_traces());
}

TF_Function* TFE_ContextGetFunction(TFE_Context* ctx, const char* name,
                                    TF_Status* status) {
  tensorflow::core::RefCountPtr<tensorflow::FunctionRecord> record =

        "//tensorflow/c:tensor_interface",
        "//tensorflow/core:framework",
        "//tensorflow/core:lib",
        "//tensorflow/core:protos_all_cc",
        "//tensorflow/core/util:managed_stack_trace",
        "@com_google_absl//absl/types:optional",
        "@com_google_absl//absl/types:span",
    ],
)

cc_library(
    name = "abstract_context",
    hdrs = ["abstract_context.h"],

        "//tensorflow/core/profiler/lib:traceme",
        "//tensorflow/core/profiler/rpc/client:profiler_client_impl",
        "//tensorflow/core/profiler/rpc:profiler_server_impl",
        "//tensorflow/core/util:managed_stack_trace",
        "//tensorflow/core:all_kernels",
        "//tensorflow/core:core_cpu",
        "//tensorflow/core:direct_session",
        "//tensorflow/core:framework_internal",
        "//tensorflow/core:graph",

tracking requests and bugs, please see
[TensorFlow Forum](https://discuss.tensorflow.org/) for general questions and
discussion, and please direct specific questions to
[Stack Overflow](https://stackoverflow.com/questions/tagged/tensorflow).**

The TensorFlow project strives to abide by generally accepted best practices in
open-source software development.

## Patching guidelines

  CancellationManager* cancellation_manager_ TF_GUARDED_BY(execution_mutex_);
  //   Outputs:
  std::vector<TensorHandlePtr> op_outputs_ TF_GUARDED_BY(execution_mutex_);
  // TF_Status is an incomplete type and so can't be stack allocated. To avoid
  // unnecessary allocations each Execute call, we keep one heap-allocated
  // version for the thread.
  StatusPtr status_ TF_GUARDED_BY(execution_mutex_);

  const std::string device_;