support view strategy in eager_fluid state

[pangyoki]

PR types

New features

PR changes

Others

Describe

动态图中间态添加View策略：输入输出Tensor共享底层数据。包括reshape、squeeze、unsqueeze、flatten API。

使用HandleViewBetweenInputAndOutput方法让输入输出共享底层数据，并共享inplace_version。

• ShareBufferWith
• ShareInplaceVersionCounterWith

中间态View op代码示例：

std::tuple<paddle::experimental::Tensor,paddle::experimental::Tensor> reshape2_dygraph_function(const paddle::experimental::Tensor& X,const paddle::experimental::Tensor& Shape, const paddle::framework::AttributeMap& attr_map) {

  paddle::platform::RecordEvent dygraph_entrance_record_event("reshape2 dygraph", paddle::platform::TracerEventType::Operator, 1);
  VLOG(3) << "Running Eager Forward Op: reshape2";
  // Dygraph Forward Pass

  std::map<std::string, std::vector<std::shared_ptr<egr::EagerVariable>>> ins = { { "X", egr::EagerUtils::TrySyncToVars(X) } };

  if(Shape.initialized()) ins["Shape"] = egr::EagerUtils::TrySyncToVars(Shape);
  std::map<std::string, std::vector<std::shared_ptr<egr::EagerVariable>>> outs = { { "Out", {std::make_shared<egr::EagerVariable>(egr::Controller::Instance().GenerateUniqueName())}},{ "XShape", {std::make_shared<egr::EagerVariable>(egr::Controller::Instance().GenerateUniqueName())}} };

  if (ins.count("X") && outs.count("Out")) {
    egr::EagerUtils::HandleViewBetweenInputAndOutput(ins["X"][0], outs["Out"][0]);
  };


  // Prepare Autograd Meta 
  egr::AutogradMeta* p_autograd_X = egr::EagerUtils::nullable_autograd_meta(X);
  egr::AutogradMeta* p_autograd_Shape = egr::EagerUtils::nullable_autograd_meta(Shape);

  bool trace_backward = egr::Controller::Instance().HasGrad();

  bool require_any_grad = egr::EagerUtils::ComputeRequireGrad(trace_backward, p_autograd_X, p_autograd_Shape);

  paddle::framework::AttributeMap attrs = attr_map;
  paddle::framework::AttributeMap default_attrs;
  egr::Controller::Instance().GetCurrentTracer()->TraceOp("reshape2", ins, outs, attrs, 
     egr::Controller::Instance().GetExpectedPlace(),
     &default_attrs, true, {});

  paddle::experimental::Tensor Out;
  egr::EagerUtils::GetOutput(outs["Out"][0], &Out);
  paddle::experimental::Tensor XShape;
  egr::EagerUtils::GetOutput(outs["XShape"][0], &XShape);

  {
    paddle::platform::RecordEvent node_creation_record_event("reshape2 node_creation", paddle::platform::TracerEventType::Operator, 1);
    egr::AutogradMeta* p_autograd_Out = egr::EagerUtils::autograd_meta(&Out);
    egr::AutogradMeta* p_autograd_XShape = egr::EagerUtils::autograd_meta(&XShape);
    if(require_any_grad) {
      VLOG(6) << " Construct Grad for reshape2 "; 
      egr::EagerUtils::PassStopGradient(false, p_autograd_Out, p_autograd_XShape);
      // Create GradOpNode
      auto grad_node = std::make_shared<GradNodereshape2>(2, 2);

      // Set Attributes
      grad_node->SetAttrMap(std::move(attrs));
      grad_node->SetDefaultAttrMap(std::move(default_attrs));

      // Set Tensor Wrappers
      grad_node->SetTensorWrapperXShape(XShape, false);

      grad_node->SetGradOutMeta(X, 0);
      if(p_autograd_X) grad_node->AddEdges(p_autograd_X, 0);
      grad_node->SetGradOutMeta(Shape, 1);
      if(p_autograd_Shape) grad_node->AddEdges(p_autograd_Shape, 1);
      egr::EagerUtils::SetOutRankWithSlot(p_autograd_Out, 0);
      egr::EagerUtils::SetHistory(p_autograd_Out, grad_node);
      grad_node->SetGradInMeta(Out, 0);
      egr::EagerUtils::CheckAndRetainGrad(Out);
      egr::EagerUtils::SetOutRankWithSlot(p_autograd_XShape, 1);
      grad_node->SetGradInMeta(XShape, 1);

    }
  }

  return std::make_tuple(Out,XShape);

}

[JiabinYang]

LGTM