C++调用和定义不匹配

Question

我正在查看此代码块 https://github.com/pytorch/pytorch/blob/master/torch/csrc/autograd/profiler.cpp#L141

pushCallback(
      [config](const RecordFunction& fn) {
        auto* msg = (fn.seqNr() >= 0) ? ", seq = " : "";
        if (config.report_input_shapes) {
          std::vector<std::vector<int64_t>> inputSizes;
          inputSizes.reserve(fn.inputs().size());
          for (const c10::IValue& input : fn.inputs()) {
            if (!input.isTensor()) {
              inputSizes.emplace_back();
              continue;
            }
            const at::Tensor& tensor = input.toTensor();
            if (tensor.defined()) {
              inputSizes.push_back(input.toTensor().sizes().vec());
            } else {
              inputSizes.emplace_back();
            }
          }
          pushRangeImpl(fn.name(), msg, fn.seqNr(), std::move(inputSizes));
        } else {
          pushRangeImpl(fn.name(), msg, fn.seqNr(), {});
        }
      },
      [](const RecordFunction& fn) {
        if (fn.getThreadId() != 0) {
          // If we've overridden the thread_id on the RecordFunction, then find
          //  the eventList that was created for the original thread_id. Then,
          // record the end event on this list so that the block is added to
          // the correct list, instead of to a new list. This should only run
          // when calling RecordFunction::end() in a different thread.
          if (state == ProfilerState::Disabled) {
            return;
          } else {
            std::lock_guard<std::mutex> guard(all_event_lists_map_mutex);
            const auto& eventListIter =
                all_event_lists_map.find(fn.getThreadId());
            TORCH_INTERNAL_ASSERT(
                eventListIter != all_event_lists_map.end(),
                "Did not find thread_id matching ",
                fn.getThreadId());

            auto& eventList = eventListIter->second;
            eventList->record(
                      EventKind::PopRange,
                      StringView(""),
                      fn.getThreadId(),
                      state == ProfilerState::CUDA);
          }
        } else {
          popRange();
        }
      },
      config.report_input_shapes);

这只有三个参数。但是pushCallback的定义好像是在这个位置 https://github.com/pytorch/pytorch/blob/master/torch/csrc/autograd/record_function.cpp#L35并接受四个参数。

void pushCallback(
      RecordFunctionCallback start,
      RecordFunctionCallback end,
      bool needs_inputs,
      bool sampled) {
    start_callbacks.push_back(std::move(start));
    end_callbacks.push_back(std::move(end));
    if (callback_needs_inputs > 0 || needs_inputs) {
      ++callback_needs_inputs;
    }
    is_callback_sampled.push_back(sampled);
    if (sampled) {
      ++num_sampled_callbacks;
    }
  }

我不知道为什么那个函数调用可以那样工作。

Answer 1

如果您查看 header ，您会发现它使用 4 个参数声明，其中最后三个参数具有默认值:

TORCH_API void pushCallback(
    RecordFunctionCallback start,
    RecordFunctionCallback end = [](const RecordFunction&){},
    bool needs_inputs = false,
    bool sampled = false);

默认参数只出现在声明中而不出现在定义中。