赛题八：paddleviz能力扩展——Tensor信息展示 #56837
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你的PR提交成功，感谢你对开源项目的贡献! |
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qiuwenbogdut
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| std::stringstream ss; | ||
| ss << this; | ||
| std::string this_pointer = ss.str(); |
| VLOG(3) << "Finish AD API Grad: GradNodeAccumulation"; | ||
| if (VLOG_IS_ON(4)) { | ||
| VLOG(6) << "gradnode_ptr = " << this; | ||
| if (VLOG_IS_ON(6)) { |
| const char* TENSOR_X_GRAD_TEMPLATE = "(grad_out, [%s]), "; | ||
| std::string output_x_grad_str = paddle::string::Sprintf( | ||
| TENSOR_X_GRAD_TEMPLATE, egr::EagerUtils::TensorStr(grad_out)); | ||
| output_str += output_x_grad_str; | ||
| VLOG(4) << paddle::string::Sprintf( | ||
| VLOG(6) << paddle::string::Sprintf( |
| @@ -72,6 +72,30 @@ AddNGradNodeFinal::operator()( | |||
| egr::CheckTensorHasNanOrInf("add_n_grad", returns); | |||
| } | |||
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| VLOG(6) << "gradnode_ptr = " << this; | |||
| if (VLOG_IS_ON(6)) { | |||
| @@ -162,6 +163,41 @@ Conv2dGradNodeFinal::operator()( | |||
| // Set TensorWrappers for Forward Outputs if needed | |||
| } | |||
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| VLOG(6) << "gradnode_ptr = " << this; | |||
| if (VLOG_IS_ON(6)) { | |||
| @@ -457,7 +458,7 @@ SyncBatchNormGradNode::operator()( | |||
| std::string output_bias_grad_str = paddle::string::Sprintf( | |||
| TENSOR_BIAS_GRAD_TEMPLATE, egr::EagerUtils::TensorStr(bias_grad)); | |||
| output_str += output_bias_grad_str; | |||
| VLOG(4) << paddle::string::Sprintf( | |||
| VLOG(6) << paddle::string::Sprintf( | |||
| //std::cout << "The pointer to the current object: " << this << std::endl; | ||
| //std::stringstream ss; | ||
| //ss << this; | ||
| //std::string this_pointer = ss.str(); | ||
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| @@ -259,10 +266,10 @@ class {} : public egr::GradNodeBase {{ | |||
| """ | |||
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| AFTER_LOG_PRINT_TEMPLATE = """ | |||
| if(VLOG_IS_ON(4)){{ | |||
| if(VLOG_IS_ON(6)){{ | |||
| const char* INPUT_PRINT_TEMPLATE = \"{{ Input: [%s], \\n Output: [%s] }} \"; | ||
| {} | ||
| VLOG(4) << paddle::string::Sprintf(INPUT_PRINT_TEMPLATE, input_str, output_str); | ||
| VLOG(6) << paddle::string::Sprintf(INPUT_PRINT_TEMPLATE, input_str, output_str); |
paddle/fluid/eager/grad_node_info.cc
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| //打印一下 next_node 对象的指针值 | ||
| std::cout << "next_node: " << next_node << std::endl; |
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这个日志是要保留的吗？如果要保留的话需要是英文注释，而且不能用std::cout,要用Vlog。如果不需要保留就删掉吧
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PR-CI-Codestyle-Check 需要解决格式问题 |
好的 这边处理一下 |
zyfncg
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Sep 19, 2023
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| VLOG(4) << paddle::string::Sprintf(INPUT_PRINT_TEMPLATE, input_str, output_str); | ||
| VLOG(6) << paddle::string::Sprintf(INPUT_PRINT_TEMPLATE, input_str, output_str); |
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这两行看上去一样，新加一个VLOG(6)的作用是什么呢？
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原始的日志等级是4 等级不够高 有些需要的信息没有打印出来,所以就增加了一个等级为6的日志打印
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是的, 确实存在重复打印的问题, 这边修改一下
可以在描述里再补充下这个PR具体做的工作，以及这些LOG的运行截图吗？
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已经增加了 这个PR的具体工作 和 日志打印图 |
zyfncg
approved these changes
Sep 20, 2023
zyfncg
reviewed
Sep 20, 2023
| @@ -870,6 +870,8 @@ PYBIND11_MODULE(libpaddle, m) { | |||
| [](const std::shared_ptr<egr::GradNodeBase> &self) { | |||
| return self->NextFunctions(); | |||
| }) | |||
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| .def("node_this_ptr", &egr::GradNodeBase::GetThisPtr) | |||
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node_this_ptr这么命名感觉有些奇怪，可以再想想有没有更好的命名
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@wanghuancoder 欢哥 命名这块有没有什么建议?
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要不改成.def("node_ptr", &egr::GradNodeBase::GetPtr)吧
这个PR不要改了。新提一个PR修改。这个PR先合入。
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Description
赛题简介：
飞桨深度学习框架提供了动态图编程的模式来开发深度学习模型（方便开发与调试），但动态图的反向图调试能力仍存在不足。@qiuwenbogdut 和 @Tomoko-hjf 两位社区开发者为Paddle开发了反向图可视化工具 paddleviz，很大程度上提升了反向图的调试能力。但我们还希望，在现有 paddleviz 基础上，扩展 paddleviz 的能力，进一步提升反向图的调试能力。
赛题要求：
深入学习Paddle动态图机制，掌握动态图反向图的基础数据结构之间的关系
学习了解 paddleviz 的原理
探索如何在 paddleviz 基础上，扩展反向图边（Tensor）的调试信息，包括不限于Tensor name、shape、dtype、place、stop_gradient 等。
探索以上数据可以通过框架的哪些数据结构中获得，何时、如何获得
探索如何将这些数据在 paddleviz 中展示
赛题八 任务描述
赛题八 tracking issue
当前这个PR计划完成的工作: