Replace risky GetInputType method with secure IndicateVarDataType interface (#20668)

* replace part of the old implementation, test=develop

* restore concat op, test=develop

* update all ops implemention & delete GetDataTypeOfVar func, test=develop

paddle/fluid/framework/operator.cc

@@ -48,16 +48,6 @@ std::vector<std::tuple<platform::Place, LibraryType>> kKernelPriority = {
     std::make_tuple(platform::CPUPlace(), LibraryType::kPlain),
 };
 
-proto::VarType::Type GetDataTypeOfVar(const Variable* var) {
-  if (var->IsType<framework::LoDTensor>()) {
-    return var->Get<framework::LoDTensor>().type();
-  } else if (var->IsType<framework::SelectedRows>()) {
-    return var->Get<framework::SelectedRows>().value().type();
-  } else {
-    PADDLE_THROW("Var should be LoDTensor or SelectedRows");
-  }
-}
-
 static DDim GetDimsDebug(const Scope& scope, const std::string& name,
                          bool get_actual_dim = false) {
   Variable* var = scope.FindVar(name);

paddle/fluid/framework/operator.h

@@ -102,7 +102,6 @@ inline std::string GradOriginalVarName(const std::string& grad_var_name) {
   }
 }
 
-proto::VarType::Type GetDataTypeOfVar(const Variable* var);
 const Tensor* GetLoDTensorOrSelectedRowsValueFromVar(const Variable& var);
 Tensor* GetMutableLoDTensorOrSelectedRowsValueFromVar(Variable* var);
 

paddle/fluid/operators/activation_op.cc

@@ -114,9 +114,8 @@ framework::OpKernelType GetKernelType(const framework::ExecutionContext& ctx,
     layout = framework::DataLayout::kMKLDNN;
   }
 #endif
-  return framework::OpKernelType(
-      framework::GetDataTypeOfVar(ctx.InputVar(name)), ctx.GetPlace(), layout,
-      library);
+  return framework::OpKernelType(oper.IndicateVarDataType(ctx, name),
+                                 ctx.GetPlace(), layout, library);
 }
 
 class ActivationOp : public framework::OperatorWithKernel {

paddle/fluid/operators/add_position_encoding_op.cc

@@ -37,8 +37,9 @@ class AddPositionEncodingOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
-                                   platform::CPUPlace());
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"),
+        platform::CPUPlace());
   }
 };
 
@@ -56,9 +57,9 @@ class AddPositionEncodingOpGrad : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        ctx.Input<framework::LoDTensor>(framework::GradVarName("Out"))->type(),
-        platform::CPUPlace());
+    return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType(
+                                       ctx, framework::GradVarName("Out")),
+                                   platform::CPUPlace());
   }
 };
 

paddle/fluid/operators/affine_channel_op.cc

@@ -121,9 +121,9 @@ class AffineChannelOpGrad : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        ctx.Input<framework::Tensor>(framework::GradVarName("Out"))->type(),
-        ctx.GetPlace());
+    return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType(
+                                       ctx, framework::GradVarName("Out")),
+                                   ctx.GetPlace());
   }
 };
 

paddle/fluid/operators/affine_grid_op.cc

@@ -80,7 +80,7 @@ class AffineGridOp : public framework::OperatorWithKernel {
       library = framework::LibraryType::kCUDNN;
     }
 #endif
-    auto data_type = ctx.Input<Tensor>("Theta")->type();
+    auto data_type = OperatorWithKernel::IndicateVarDataType(ctx, "Theta");
     return framework::OpKernelType(data_type, ctx.GetPlace(),
                                    framework::DataLayout::kAnyLayout, library);
   }
@@ -191,9 +191,9 @@ class AffineGridOpGrad : public framework::OperatorWithKernel {
       library_ = framework::LibraryType::kCUDNN;
     }
 #endif
-    return framework::OpKernelType(ctx.Input<Tensor>("Theta")->type(),
-                                   ctx.GetPlace(),
-                                   framework::DataLayout::kAnyLayout, library_);
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "Theta"), ctx.GetPlace(),
+        framework::DataLayout::kAnyLayout, library_);
   }
 };
 

paddle/fluid/operators/assign_op.cc

@@ -89,8 +89,9 @@ class AssignOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
-                                   ctx.device_context());
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"),
+        ctx.device_context());
   }
 };
 

paddle/fluid/operators/attention_lstm_op.cc

@@ -129,8 +129,8 @@ void AttentionLSTMOp::InferShape(framework::InferShapeContext* ctx) const {
 
 framework::OpKernelType AttentionLSTMOp::GetExpectedKernelType(
     const framework::ExecutionContext& ctx) const {
-  return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
-                                 ctx.device_context());
+  return framework::OpKernelType(
+      OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.device_context());
 }
 
 void AttentionLSTMOpMaker::Make() {

paddle/fluid/operators/average_accumulates_op.cc

@@ -103,8 +103,8 @@ class AverageAccumulatesOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(ctx.Input<Tensor>("param")->type(),
-                                   ctx.GetPlace());
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "param"), ctx.GetPlace());
   }
 };
 

paddle/fluid/operators/batch_norm_op.cc

@@ -115,7 +115,7 @@ void BatchNormOp::InferShape(framework::InferShapeContext *ctx) const {
 
 framework::OpKernelType BatchNormOp::GetExpectedKernelType(
     const framework::ExecutionContext &ctx) const {
-  auto input_data_type = ctx.Input<Tensor>("X")->type();
+  auto input_data_type = OperatorWithKernel::IndicateVarDataType(ctx, "X");
   // By default, the type of the scale, bias, mean,
   // and var tensors should both be float. (For float or float16 input tensor)
   // or double (For double input tensor).
@@ -432,8 +432,9 @@ framework::OpKernelType BatchNormGradOp::GetExpectedKernelType(
   }
 #endif
 
-  return framework::OpKernelType(ctx.Input<Tensor>("X")->type(), ctx.GetPlace(),
-                                 layout, library);
+  return framework::OpKernelType(
+      OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace(), layout,
+      library);
 }
 
 template <typename T>

paddle/fluid/operators/beam_search_op.cc

@@ -109,10 +109,11 @@ class BeamSearchOp : public framework::OperatorWithKernel {
     // Compute on CPU for cases with batch_size > 4.
     if (batch_size <= 4) {
       return framework::OpKernelType(
-          ctx.Input<framework::LoDTensor>("pre_ids")->type(), ctx.GetPlace());
+          OperatorWithKernel::IndicateVarDataType(ctx, "pre_ids"),
+          ctx.GetPlace());
     } else {
       return framework::OpKernelType(
-          ctx.Input<framework::LoDTensor>("pre_ids")->type(),
+          OperatorWithKernel::IndicateVarDataType(ctx, "pre_ids"),
           platform::CPUPlace());
     }
   }

paddle/fluid/operators/bpr_loss_op.cc

@@ -52,8 +52,9 @@ class BprLossOp : public framework::OperatorWithKernel {
   // is determined by its input "X".
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
-                                   platform::CPUPlace());
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"),
+        platform::CPUPlace());
   }
 };
 
@@ -98,8 +99,9 @@ class BprLossGradientOp : public framework::OperatorWithKernel {
   // is determined by its input "X".
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
-                                   platform::CPUPlace());
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"),
+        platform::CPUPlace());
   }
 };
 

paddle/fluid/operators/center_loss_op.cc

@@ -61,8 +61,9 @@ class CenterLossOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
-                                   ctx.device_context());
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"),
+        ctx.device_context());
   }
 };
 
@@ -117,7 +118,8 @@ class CenterLossGradOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
     return framework::OpKernelType(
-        ctx.Input<Tensor>("SampleCenterDiff")->type(), ctx.device_context());
+        OperatorWithKernel::IndicateVarDataType(ctx, "SampleCenterDiff"),
+        ctx.device_context());
   }
 };
 

paddle/fluid/operators/collective/c_allreduce_op.h

@@ -41,8 +41,8 @@ class CAllReduceOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(ctx.Input<framework::Tensor>("X")->type(),
-                                   ctx.GetPlace());
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace());
   }
 };
 

paddle/fluid/operators/collective/c_broadcast_op.cc

@@ -28,8 +28,8 @@ class CBroadcastOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(ctx.Input<framework::Tensor>("X")->type(),
-                                   ctx.GetPlace());
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace());
   }
 };
 

paddle/fluid/operators/concat_op.cc

@@ -102,7 +102,6 @@ class ConcatOp : public framework::OperatorWithKernel {
     if (flag == 0) {
       PADDLE_THROW("All Inputs of Concat OP are Empty!");
     }
-
 #ifdef PADDLE_WITH_MKLDNN
     if (platform::CanMKLDNNBeUsed(ctx)) {
       return framework::OpKernelType(input_data_type, ctx.GetPlace(),
@@ -175,9 +174,9 @@ class ConcatOpGrad : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    return framework::OpKernelType(
-        ctx.Input<Tensor>(framework::GradVarName("Out"))->type(),
-        ctx.GetPlace());
+    return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType(
+                                       ctx, framework::GradVarName("Out")),
+                                   ctx.GetPlace());
   }
 };
 

paddle/fluid/operators/conv_op.cc

@@ -135,7 +135,7 @@ framework::OpKernelType ConvOp::GetExpectedKernelType(
       framework::OpKernelType::kDefaultCustomizedTypeValue;
   framework::LibraryType library{framework::LibraryType::kPlain};
   // TODO(pzelazko-intel): enable MKLDNN layout when it's ready
-  auto input_data_type = ctx.Input<Tensor>("Input")->type();
+  auto input_data_type = OperatorWithKernel::IndicateVarDataType(ctx, "Input");
   std::string data_format =
       "AnyLayout";  // todo enable data layout when it's ready
   framework::DataLayout layout = framework::StringToDataLayout(data_format);
@@ -527,9 +527,9 @@ framework::OpKernelType ConvOpGrad::GetExpectedKernelType(
   }
 #endif
 
-  auto type = framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
-                                      ctx.GetPlace(), layout_, library_,
-                                      customized_type_value);
+  auto type = framework::OpKernelType(
+      OperatorWithKernel::IndicateVarDataType(ctx, "Input"), ctx.GetPlace(),
+      layout_, library_, customized_type_value);
 #ifdef PADDLE_WITH_CUDA
   if (library_ == framework::LibraryType::kCUDNN) {
     std::vector<framework::KernelConfig>& configs = kernel_configs_map_[type];
@@ -704,9 +704,9 @@ framework::OpKernelType ConvOpDoubleGrad::GetExpectedKernelType(
     customized_type_value = kConvMKLDNNFP32;
   }
 #endif
-  auto type = framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
-                                      ctx.GetPlace(), layout_, library_,
-                                      customized_type_value);
+  auto type = framework::OpKernelType(
+      OperatorWithKernel::IndicateVarDataType(ctx, "Input"), ctx.GetPlace(),
+      layout_, library_, customized_type_value);
 #ifdef PADDLE_WITH_CUDA
   if (library_ == framework::LibraryType::kCUDNN) {
     std::vector<framework::KernelConfig>& configs = kernel_configs_map_[type];

paddle/fluid/operators/conv_transpose_op.cc

@@ -132,8 +132,9 @@ framework::OpKernelType ConvTransposeOp::GetExpectedKernelType(
   }
 #endif
 
-  return framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
-                                 ctx.GetPlace(), layout_, library_);
+  return framework::OpKernelType(
+      OperatorWithKernel::IndicateVarDataType(ctx, "Input"), ctx.GetPlace(),
+      layout_, library_);
 }
 
 void Conv2DTransposeOpMaker::Make() {
@@ -384,8 +385,9 @@ framework::OpKernelType ConvTransposeOpGrad::GetExpectedKernelType(
   }
 
   framework::DataLayout layout_ = framework::DataLayout::kAnyLayout;
-  return framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
-                                 ctx.GetPlace(), layout_, library_);
+  return framework::OpKernelType(
+      OperatorWithKernel::IndicateVarDataType(ctx, "Input"), ctx.GetPlace(),
+      layout_, library_);
 }
 
 class ConvTransposeGradOpDescMaker : public framework::SingleGradOpDescMaker {

paddle/fluid/operators/crf_decoding_op.cc

@@ -160,8 +160,9 @@ class CRFDecodingOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(ctx.Input<LoDTensor>("Emission")->type(),
-                                   platform::CPUPlace());
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "Emission"),
+        platform::CPUPlace());
   }
 };
 }  // namespace operators

paddle/fluid/operators/crop_op.cc

@@ -53,8 +53,9 @@ class CropOp : public framework::OperatorWithKernel {
 
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
-                                   ctx.device_context());
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"),
+        ctx.device_context());
   }
 };
 
@@ -174,9 +175,9 @@ class CropOpGrad : public framework::OperatorWithKernel {
 
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        ctx.Input<framework::LoDTensor>(framework::GradVarName("Out"))->type(),
-        ctx.device_context());
+    return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType(
+                                       ctx, framework::GradVarName("Out")),
+                                   ctx.device_context());
   }
 };
 

paddle/fluid/operators/crop_tensor_op.cc

@@ -98,8 +98,9 @@ class CropTensorOp : public framework::OperatorWithKernel {
 
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
-                                   ctx.device_context());
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"),
+        ctx.device_context());
   }
 
   framework::OpKernelType GetKernelTypeForVar(
@@ -254,9 +255,9 @@ class CropTensorOpGrad : public framework::OperatorWithKernel {
 
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    return framework::OpKernelType(
-        ctx.Input<framework::LoDTensor>(framework::GradVarName("Out"))->type(),
-        ctx.device_context());
+    return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType(
+                                       ctx, framework::GradVarName("Out")),
+                                   ctx.device_context());
   }
 
   framework::OpKernelType GetKernelTypeForVar(

paddle/fluid/operators/cross_entropy_op.cc

@@ -107,8 +107,9 @@ class CrossEntropyOpBase : public framework::OperatorWithKernel {
   // is determined by its input "X".
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
-                                   ctx.device_context());
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"),
+        ctx.device_context());
   }
 
   virtual bool IsSoftLabel(framework::InferShapeContext* ctx) const {
@@ -157,9 +158,9 @@ class CrossEntropyGradientOpBase : public framework::OperatorWithKernel {
   // is determined by its input "X".
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        ctx.Input<Tensor>(framework::GradVarName("Y"))->type(),
-        ctx.device_context());
+    return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType(
+                                       ctx, framework::GradVarName("Y")),
+                                   ctx.device_context());
   }
 
   virtual framework::DDim GetXDim(framework::InferShapeContext* ctx) const {

paddle/fluid/operators/ctc_align_op.cc

@@ -39,8 +39,9 @@ class CTCAlignOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
-                                   ctx.device_context());
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "Input"),
+        ctx.device_context());
   }
 };
 

paddle/fluid/operators/cvm_op.cc

@@ -52,8 +52,9 @@ class CVMOp : public framework::OperatorWithKernel {
   // is determined by its input "X".
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
-                                   platform::CPUPlace());
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"),
+        platform::CPUPlace());
   }
 };
 
@@ -93,8 +94,9 @@ class CVMGradientOp : public framework::OperatorWithKernel {
   // is determined by its input "X".
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
-                                   platform::CPUPlace());
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"),
+        platform::CPUPlace());
   }
 };
 

paddle/fluid/operators/data_norm_op.cc

@@ -81,7 +81,7 @@ class DataNormOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    auto input_data_type = ctx.Input<Tensor>("X")->type();
+    auto input_data_type = OperatorWithKernel::IndicateVarDataType(ctx, "X");
     // By default, the type of the scale, bias, mean,
     // and var tensors should both be float. (For float or float16 input tensor)
     // or double (For double input tensor).
@@ -89,12 +89,14 @@ class DataNormOp : public framework::OperatorWithKernel {
     if (input_data_type == framework::proto::VarType::FP64) {
       dn_param_type = framework::proto::VarType::FP64;
     }
-    PADDLE_ENFORCE_EQ(dn_param_type, ctx.Input<Tensor>("BatchSize")->type(),
+    PADDLE_ENFORCE_EQ(dn_param_type,
+                      OperatorWithKernel::IndicateVarDataType(ctx, "BatchSize"),
                       "BatchSize input should be of float type");
-    PADDLE_ENFORCE_EQ(dn_param_type, ctx.Input<Tensor>("BatchSum")->type(),
-                      "BatchSum input should be of float type");
     PADDLE_ENFORCE_EQ(dn_param_type,
-                      ctx.Input<Tensor>("BatchSquareSum")->type(),
+                      OperatorWithKernel::IndicateVarDataType(ctx, "BatchSum"),
+                      "BatchSum input should be of float type");
+    PADDLE_ENFORCE_EQ(dn_param_type, OperatorWithKernel::IndicateVarDataType(
+                                         ctx, "BatchSquareSum"),
                       "BatchSquareSum input should be of float type");
 
     // TODO(pzelazko-intel): enable MKLDNN layout when it's ready
@@ -276,8 +278,9 @@ class DataNormGradOp : public framework::OperatorWithKernel {
     }
 #endif
 
-    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
-                                   ctx.GetPlace(), layout, library);
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace(),
+        layout, library);
   }
 };