TF_CAPI_EXPORT extern TFE_ContextOptions* TFE_NewContextOptions(void);

// Set the config in TF_ContextOptions.options.
// config should be a serialized tensorflow.ConfigProto proto.
// If config was not parsed successfully as a ConfigProto, record the
// error information in *status.
TF_CAPI_EXPORT extern void TFE_ContextOptionsSetConfig(
    TFE_ContextOptions* options, const void* proto, size_t proto_len,
    TF_Status* status);

# Description:
# C API for TensorFlow, for use by client language bindings.

load("@bazel_skylib//lib:selects.bzl", "selects")
load("@local_config_tensorrt//:build_defs.bzl", "if_tensorrt")
load("@local_tsl//tsl/platform:rules_cc.bzl", "cc_library")
load(
    "//tensorflow:tensorflow.bzl",
    "check_deps",
    "if_google",
    "if_not_mobile",
    "tf_cc_test",
    "tf_copts",
    "tf_cuda_library",
    "tf_custom_op_library",

  tensorflow::core::RefCountPtr<tensorflow::FunctionRecord> record =
      tensorflow::unwrap(ctx)->FindRecord(name);

  if (record == nullptr) {
    status->status = tensorflow::errors::NotFound(
        "Unable to find Function with name: ", name);
    return nullptr;
  }

  TF_Function* result = new TF_Function();
  record->Ref();
  result->record = record.get();
  return result;
}

  auto function_record = tensorflow::unwrap(ctx)->FindRecord(function_name);
  if (function_record == nullptr) {
    status->status = tensorflow::errors::NotFound(
        "Unable to find function with name: ", function_name);
    return;
  }

  tensorflow::GraphDebugInfo debug_info =
      tensorflow::StackTracesMapToGraphDebugInfo(
          function_record->stack_traces());

  // Find and return a added function by its name.
  virtual const FunctionDef* FindFunctionDef(const string& name) const = 0;

  // Find and return a function record added by its name.
  virtual core::RefCountPtr<FunctionRecord> FindRecord(
      const string& name) const = 0;

  // Return the ParsedName of Host CPU device.

                                   graph_outputs.size(), graph_outputs.data(),
                                   nullptr, nullptr, name_.data(), s);
    *f = new GraphFunction(std::move(func->record->fdef()));
    TF_DeleteFunction(func);
    TF_RETURN_IF_ERROR(StatusFromTF_Status(s));
    TF_DeleteStatus(s);
    return absl::OkStatus();
  }

  Status RegisterFunction(AbstractFunction* func) override {

    // Make a copy so that we can mutate it.
    FunctionDef fdef_to_load = fdef;
    if (mutate_proto_func) {
      (*mutate_proto_func)(&fdef_to_load);
    }
    VLOG(1) << "Adding func to graph: " << fdef_to_load.DebugString();
    std::vector<char> binary_proto_buf(fdef_to_load.ByteSizeLong());
    fdef_to_load.SerializeToArray(binary_proto_buf.data(),
                                  binary_proto_buf.size());

  tensorflow::mutex_lock l(g->mu);
  status->status = g->graph.AddFunctionDef(func->record->fdef(),
                                           func->record->stack_traces());
  if (TF_GetCode(status) != TF_OK) return;
  if (!grad) return;

  status->status = g->graph.AddFunctionDef(grad->record->fdef(),
                                           grad->record->stack_traces());
  if (TF_GetCode(status) != TF_OK) return;