if (grad_it == gradients.end()) {
      result[i] = nullptr;
    } else {
      if (grad_it->second.size() > 1) {
        Gradient* grad = vspace.AggregateGradients(grad_it->second);
        grad_it->second.clear();
        grad_it->second.push_back(grad);
      }
      result[i] = grad_it->second[0];
      used_gradient_ids.insert(tensor_id);
    }
  }
  VLOG(1) << "Final gradients size: "

  // This is the size of cond_inputs, body_inputs, and body_outputs.
  const int ninputs;

  // The while condition graph. The inputs are the current values of the loop
  // variables. The output should be a scalar boolean.
  TF_Graph* const cond_graph;
  const TF_Output* const cond_inputs;
  TF_Output cond_output;

  absl::StatusOr<core::RefCountPtr<FunctionRecord>> GetFunctionRecord()
      override {
    return func_record_.GetNewRef();
  }

  // For LLVM style RTTI.
  static bool classof(const AbstractFunction* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:
  core::RefCountPtr<FunctionRecord> func_record_;
};
}  // namespace graph
}  // namespace tracing
}  // namespace tensorflow

    TF_Status* status);

TF_CAPI_EXPORT extern TF_Buffer* TF_CoordinationServiceGetKeyValueWithTimeout(
    const char* key, int64_t key_size, int64_t timeout_seconds,
    TF_CoordinationServiceAgent* agent, TF_Status* status);

TF_CAPI_EXPORT extern TF_Buffer* TF_CoordinationServiceTryGetKeyValue(
    const char* key, int64_t key_size, TF_CoordinationServiceAgent* agent,

  // 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.