Merge pull request #3178 from reyoung/feature/GetEigenDeviceReturnReference

Return Reference Instead Pointer to GetEigenDevice

paddle/framework/operator.cc

@@ -20,16 +20,16 @@ namespace paddle {
 namespace framework {
 
 template <>
-Eigen::DefaultDevice* ExecutionContext::GetEigenDevice<
+Eigen::DefaultDevice& ExecutionContext::GetEigenDevice<
     platform::CPUPlace, Eigen::DefaultDevice>() const {
-  return device_context_.get_eigen_device<Eigen::DefaultDevice>();
+  return *device_context_.get_eigen_device<Eigen::DefaultDevice>();
 }
 
 #ifndef PADDLE_ONLY_CPU
 template <>
-Eigen::GpuDevice*
+Eigen::GpuDevice&
 ExecutionContext::GetEigenDevice<platform::GPUPlace, Eigen::GpuDevice>() const {
-  return device_context_.get_eigen_device<Eigen::GpuDevice>();
+  return *device_context_.get_eigen_device<Eigen::GpuDevice>();
 }
 #endif
 

paddle/framework/operator.h

@@ -253,7 +253,7 @@ class ExecutionContext : public OperatorContext {
   template <typename PlaceType,
             typename DeviceType =
                 typename EigenDeviceConverter<PlaceType>::EigenDeviceType>
-  DeviceType* GetEigenDevice() const;
+  DeviceType& GetEigenDevice() const;
 
   platform::Place GetPlace() const { return device_context_.GetPlace(); }
 

paddle/operators/add_op.h

@@ -28,8 +28,7 @@ public:
 
     output->mutable_data<T>(context.GetPlace());
 
-    EigenVector<T>::Flatten(*output).device(
-        *(context.GetEigenDevice<Place>())) =
+    EigenVector<T>::Flatten(*output).device(context.GetEigenDevice<Place>()) =
         framework::EigenVector<T>::Flatten(*input0) +
         framework::EigenVector<T>::Flatten(*input1);
   }

paddle/operators/mean_op.h

@@ -27,7 +27,7 @@ public:
 
     output->mutable_data<T>(context.GetPlace());
 
-    EigenScalar<T>::From(*output).device(*(context.GetEigenDevice<Place>())) =
+    EigenScalar<T>::From(*output).device(context.GetEigenDevice<Place>()) =
         EigenVector<T>::Flatten(*input).mean();
   }
 };

paddle/operators/mul_op.h

@@ -29,7 +29,7 @@ public:
     auto output = context.Output<Tensor>(0);
     output->mutable_data<T>(context.GetPlace());
 
-    EigenMatrix<T>::From(*output).device(*(context.GetEigenDevice<Place>())) =
+    EigenMatrix<T>::From(*output).device(context.GetEigenDevice<Place>()) =
         EigenMatrix<T>::From(*context.Input<Tensor>("X"))
             .contract(EigenMatrix<T>::From(*context.Input<Tensor>("Y")),
                       dim_pair);

paddle/operators/rowwise_add_op.h

@@ -33,7 +33,7 @@ public:
     const int rest_size = input.size() / bias_size;
     Eigen::DSizes<int, 1> one_d(input.size());
     Eigen::DSizes<int, 1> bcast(rest_size);
-    output.reshape(one_d).device(*(context.GetEigenDevice<Place>())) =
+    output.reshape(one_d).device(context.GetEigenDevice<Place>()) =
         input.reshape(one_d) + bias.broadcast(bcast).reshape(one_d);
   }
 };

paddle/operators/sgd_op.h

@@ -29,7 +29,7 @@ public:
 
     param_out->mutable_data<T>(ctx.GetPlace());
 
-    EigenVector<T>::Flatten(*param_out).device(*(ctx.GetEigenDevice<Place>())) =
+    EigenVector<T>::Flatten(*param_out).device(ctx.GetEigenDevice<Place>()) =
         EigenVector<T>::Flatten(*param) - lr * EigenVector<T>::Flatten(*grad);
   }
 };

paddle/operators/sigmoid_op.h

@@ -27,8 +27,7 @@ public:
     auto output = context.Output<Tensor>(0);
     output->mutable_data<T>(context.GetPlace());
 
-    EigenVector<T>::Flatten(*output).device(
-        *(context.GetEigenDevice<Place>())) =
+    EigenVector<T>::Flatten(*output).device(context.GetEigenDevice<Place>()) =
         1.0 / (1.0 + (-1.0 * EigenVector<T>::Flatten(*input)).exp());
   }
 };

paddle/operators/softmax_op.h

@@ -46,9 +46,9 @@ public:
                                .reshape(batch_by_one)
                                .broadcast(one_by_class));
 
-    softmax.device(*(context.GetEigenDevice<Place>())) = shifted_logits.exp();
+    softmax.device(context.GetEigenDevice<Place>()) = shifted_logits.exp();
 
-    softmax.device(*(context.GetEigenDevice<Place>())) =
+    softmax.device(context.GetEigenDevice<Place>()) =
         (softmax *
          softmax.sum(along_class)
              .inverse()