support inplace in dygraph eager_final state

[pangyoki]

PR types

New features

PR changes

Others

Describe

中间态inplace功能见PR #40400 。
本PR为最终态inplace功能实现，主要修改自动代码生成部分。添加了inplace relu_示例。

• python-c层

static PyObject * eager_final_state_api_relu_(PyObject *self, PyObject *args, PyObject *kwargs)
{
  paddle::platform::RecordEvent pythonc_record_event("relu_ pybind_imperative_func", paddle::platform::TracerEventType::Operator, 1);

  PyThreadState *tstate = nullptr;
  try
  {
    VLOG(6) << "Running Eager Final State API: relu_";

    // Get EagerTensors from args
    auto x = GetTensorFromArgs("relu_", "x", args, 0, false);


    // Parse Attributes


    tstate = PyEval_SaveThread();
    
    auto out = relu__final_state_dygraph_function(x);
    
    PyEval_RestoreThread(tstate);
    tstate = nullptr;

    ssize_t arg_id = GetIdxFromCoreOpsInfoMap(core_ops_final_state_args_info, "final_state_relu_", "x");
    ssize_t return_id = GetIdxFromCoreOpsInfoMap(core_ops_final_state_returns_info, "final_state_relu_", "out");
    return ToPyObject(out, return_id, args, arg_id);

  }
  catch(...) {
    if (tstate) {
      PyEval_RestoreThread(tstate);
    }
    ThrowExceptionToPython(std::current_exception());
    return nullptr;
  }
}

• 动态图层

paddle::experimental::Tensor relu__final_state_dygraph_function(paddle::experimental::Tensor& x) {
    paddle::platform::RecordEvent dygraph_entrance_record_event("relu_ dygraph", paddle::platform::TracerEventType::Operator, 1);
    


    // Get AutoGradMeta
    egr::AutogradMeta* x_autograd_meta = egr::EagerUtils::nullable_autograd_meta(x);
    bool trace_backward = egr::Controller::Instance().HasGrad();
    bool require_any_grad = egr::EagerUtils::ComputeRequireGrad(trace_backward,x_autograd_meta);

    // Check Inplace
    egr::EagerUtils::CheckInplace(x, x_autograd_meta, require_any_grad);


    // Forward API Call
    auto api_result = paddle::experimental::relu_(x);

    // Bump Inplace Version
    x.bump_inplace_version();
    VLOG(3) << "Tensor(" << x.name() << ") uses Inplace Strategy.";


    {

        paddle::platform::RecordEvent node_creation_record_event("relu_ node_creation", paddle::platform::TracerEventType::Operator, 1);

        
        egr::AutogradMeta* out_autograd_meta = egr::EagerUtils::autograd_meta(&api_result);
        if(require_any_grad) {
            egr::EagerUtils::PassStopGradient(false,out_autograd_meta);
            
            // Node Construction
            auto grad_node = std::make_shared<FinalGradNoderelu>(1, 1);
            // SetAttributes

            // SetTensorWrappers
            grad_node->SetTensorWrapperx(x, true);
            // SetGradOutMeta & SetEdges
            grad_node->SetGradOutMeta(x_autograd_meta, 0);
            grad_node->AddEdges(x_autograd_meta, 0);
            // SetOutRank & SetHistory & SetGradInMeta & RetainGrad
            egr::EagerUtils::SetOutRankWithSlot(out_autograd_meta, 0);
            egr::EagerUtils::SetHistory(out_autograd_meta, grad_node);
            grad_node->SetGradInMeta(out_autograd_meta, 0);
            egr::EagerUtils::CheckAndRetainGrad(api_result);
        }
    }



    // Returns
    return api_result;
}

[paddle-bot-old]

你的PR提交成功，感谢你对开源项目的贡献!
请关注后续CI自动化测试结果，详情请参考Paddle-CI手册。
Your PR has been submitted. Thanks for your contribution!
Please wait for the result of CI firstly. See Paddle CI Manual for details.

[JiabinYang]

LGTM