Improve elementwise operators performance in same dimensions. (#19763)

Improve elementwise operators performance in same dimensions

paddle/fluid/operators/elementwise/elementwise_add_op.cc

@@ -20,6 +20,34 @@ limitations under the License. */
 namespace paddle {
 namespace operators {
 
+template <typename T>
+struct SameDimsElemwiseAdd<
+    platform::CPUDeviceContext, T,
+    typename std::enable_if<std::is_floating_point<T>::value>::type> {
+  void operator()(const framework::ExecutionContext &ctx,
+                  const framework::Tensor *x, const framework::Tensor *y,
+                  framework::Tensor *z) {
+    auto blas = math::GetBlas<platform::CPUDeviceContext, T>(ctx);
+    blas.VADD(x->numel(), x->data<T>(), y->data<T>(), z->data<T>());
+  }
+};
+
+template <typename T>
+struct SameDimsElemwiseAdd<
+    platform::CPUDeviceContext, T,
+    typename std::enable_if<!std::is_floating_point<T>::value>::type> {
+  void operator()(const framework::ExecutionContext &ctx,
+                  const framework::Tensor *x, const framework::Tensor *y,
+                  framework::Tensor *z) {
+    auto eigen_x = framework::EigenVector<T>::Flatten(*x);
+    auto eigen_y = framework::EigenVector<T>::Flatten(*y);
+    auto eigen_z = framework::EigenVector<T>::Flatten(*z);
+    auto &place = *ctx.template device_context<platform::CPUDeviceContext>()
+                       .eigen_device();
+    eigen_z.device(place) = eigen_x + eigen_y;
+  }
+};
+
 class ElementwiseAddOpMaker : public ElementwiseOpMaker {
  protected:
   std::string GetName() const override { return "Add"; }

paddle/fluid/operators/elementwise/elementwise_add_op.cu

@@ -11,13 +11,84 @@ distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
-
 #include "paddle/fluid/operators/elementwise/elementwise_add_op.h"
+#include "paddle/fluid/operators/elementwise/elementwise_op_function.cu.h"
 #include "paddle/fluid/platform/float16.h"
 
 namespace ops = paddle::operators;
 namespace plat = paddle::platform;
 
+namespace paddle {
+namespace operators {
+
+template <typename T>
+struct SameDimsElemwiseAdd<platform::CUDADeviceContext, T> {
+  void operator()(const framework::ExecutionContext& ctx,
+                  const framework::Tensor* x, const framework::Tensor* y,
+                  framework::Tensor* z) {
+    AddRangeFunctor<T> functor(x->data<T>(), y->data<T>(), z->data<T>());
+    auto& dev_ctx = ctx.template device_context<platform::CUDADeviceContext>();
+    platform::ForRange<platform::CUDADeviceContext> for_range(dev_ctx,
+                                                              x->numel());
+    for_range(functor);
+  }
+};
+
+template <>
+struct SameDimsElemwiseAdd<platform::CUDADeviceContext, platform::float16> {
+  void operator()(const framework::ExecutionContext& ctx,
+                  const framework::Tensor* x, const framework::Tensor* y,
+                  framework::Tensor* z) {
+    auto size = x->numel();
+    dim3 gird_size = dim3(
+        (size / 2 + PADDLE_CUDA_THREAD_SIZE - 1) / PADDLE_CUDA_THREAD_SIZE, 1);
+    dim3 block_size = dim3(PADDLE_CUDA_THREAD_SIZE, 1);
+    const half* x2 =
+        reinterpret_cast<const half*>(x->data<platform::float16>());
+    const half* y2 =
+        reinterpret_cast<const half*>(y->data<platform::float16>());
+    half* z2 = reinterpret_cast<half*>(z->data<platform::float16>());
+    SameDimsElemwiseAddCUDAKernel<<<
+        gird_size, block_size, 0,
+        ctx.template device_context<platform::CUDADeviceContext>().stream()>>>(
+        x2, y2, z2, size);
+  }
+};
+
+template <typename T>
+static __global__ void SimpleElemwiseAddGradCUDAKernel(const T* dout,
+                                                       int64_t size, T* dx,
+                                                       T* dy) {
+  int col = blockIdx.x * blockDim.x + threadIdx.x;
+
+  while (col < size) {
+    dx[col] = dout[col];
+    dy[col] = dout[col];
+    col += blockDim.x * gridDim.x;
+  }
+}
+
+template <typename DeviceContext, typename T>
+typename std::enable_if<
+    std::is_same<DeviceContext, plat::CUDADeviceContext>::value>::type
+elementwise_add_grad(const framework::ExecutionContext& ctx,
+                     const framework::Tensor* x, const framework::Tensor* y,
+                     const framework::Tensor* out,
+                     const framework::Tensor* dout, framework::Tensor* dx,
+                     framework::Tensor* dy) {
+  dim3 block_size = dim3(PADDLE_CUDA_THREAD_SIZE, 1);
+  auto size = x->numel();
+  dim3 gird_size =
+      dim3((size + PADDLE_CUDA_THREAD_SIZE - 1) / PADDLE_CUDA_THREAD_SIZE, 1);
+  SimpleElemwiseAddGradCUDAKernel<
+      T><<<gird_size, block_size, 0,
+           ctx.template device_context<plat::CUDADeviceContext>().stream()>>>(
+      dout->data<T>(), size, dx->mutable_data<T>(ctx.GetPlace()),
+      dy->mutable_data<T>(ctx.GetPlace()));
+}
+
+}  // namespace operators
+}  // namespace paddle
 REGISTER_OP_CUDA_KERNEL(
     elementwise_add, ops::ElementwiseAddKernel<plat::CUDADeviceContext, float>,
     ops::ElementwiseAddKernel<plat::CUDADeviceContext, double>,

paddle/fluid/operators/elementwise/elementwise_add_op.h

@@ -11,22 +11,15 @@ distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
-
 #pragma once
 
-#include "paddle/fluid/framework/eigen.h"
 #include "paddle/fluid/operators/elementwise/elementwise_op.h"
+#include "paddle/fluid/operators/elementwise/elementwise_op_function.cu.h"
 #include "paddle/fluid/operators/elementwise/elementwise_op_function.h"
 #include "paddle/fluid/operators/math/blas.h"
-
 namespace paddle {
 namespace operators {
 
-template <typename T>
-struct AddFunctor {
-  inline HOSTDEVICE T operator()(T a, T b) const { return a + b; }
-};
-
 template <typename DeviceContext, typename T>
 void default_elementwise_add(const framework::ExecutionContext &ctx,
                              const framework::Tensor *x,
@@ -36,31 +29,12 @@ void default_elementwise_add(const framework::ExecutionContext &ctx,
                                                         AddFunctor<T>(), z);
 }
 
-template <typename DeviceContext, typename T>
-typename std::enable_if<
-    std::is_floating_point<T>::value &&
-    std::is_same<DeviceContext, platform::CPUDeviceContext>::value>::type
-elementwise_add_same_dims(const framework::ExecutionContext &ctx,
-                          const framework::Tensor *x,
-                          const framework::Tensor *y, framework::Tensor *z) {
-  auto blas = math::GetBlas<DeviceContext, T>(ctx);
-  blas.VADD(x->numel(), x->data<T>(), y->data<T>(), z->data<T>());
-}
-
-template <typename DeviceContext, typename T>
-typename std::enable_if<
-    !std::is_floating_point<T>::value ||
-    !std::is_same<DeviceContext, platform::CPUDeviceContext>::value>::type
-elementwise_add_same_dims(const framework::ExecutionContext &ctx,
-                          const framework::Tensor *x,
-                          const framework::Tensor *y, framework::Tensor *z) {
-  auto eigen_x = framework::EigenVector<T>::Flatten(*x);
-  auto eigen_y = framework::EigenVector<T>::Flatten(*y);
-  auto eigen_z = framework::EigenVector<T>::Flatten(*z);
-
-  auto &place = *ctx.template device_context<DeviceContext>().eigen_device();
-  eigen_z.device(place) = eigen_x + eigen_y;
-}
+template <typename DeviceContext, typename T, class Enable = void>
+struct SameDimsElemwiseAdd {
+  void operator()(const framework::ExecutionContext &ctx,
+                  const framework::Tensor *x, const framework::Tensor *y,
+                  framework::Tensor *z);
+};
 
 template <typename DeviceContext, typename T>
 class ElementwiseAddKernel : public framework::OpKernel<T> {
@@ -69,12 +43,11 @@ class ElementwiseAddKernel : public framework::OpKernel<T> {
     auto *x = ctx.Input<framework::LoDTensor>("X");
     auto *y = ctx.Input<framework::LoDTensor>("Y");
     auto *z = ctx.Output<framework::LoDTensor>("Out");
-
     z->mutable_data<T>(ctx.GetPlace());
-
     auto dims_equal = x->dims() == y->dims();
     if (dims_equal) {
-      elementwise_add_same_dims<DeviceContext, T>(ctx, x, y, z);
+      SameDimsElemwiseAdd<DeviceContext, T> same_dims_add;
+      same_dims_add(ctx, x, y, z);
     } else {
       default_elementwise_add<DeviceContext, T>(ctx, x, y, z);
     }
@@ -112,7 +85,6 @@ elementwise_add_grad(const framework::ExecutionContext &ctx,
                      const framework::Tensor *dout, framework::Tensor *dx,
                      framework::Tensor *dy) {
   auto blas = math::GetBlas<DeviceContext, T>(ctx);
-
   if (dx) {
     blas.VCOPY(dout->numel(), dout->data<T>(),
                dx->mutable_data<T>(ctx.GetPlace()));
@@ -126,8 +98,8 @@ elementwise_add_grad(const framework::ExecutionContext &ctx,
 
 template <typename DeviceContext, typename T>
 typename std::enable_if<
-    !std::is_floating_point<T>::value ||
-    !std::is_same<DeviceContext, platform::CPUDeviceContext>::value>::type
+    !std::is_floating_point<T>::value &&
+    std::is_same<DeviceContext, platform::CPUDeviceContext>::value>::type
 elementwise_add_grad(const framework::ExecutionContext &ctx,
                      const framework::Tensor *x, const framework::Tensor *y,
                      const framework::Tensor *out,
@@ -136,6 +108,18 @@ elementwise_add_grad(const framework::ExecutionContext &ctx,
   default_elementwise_add_grad<DeviceContext, T>(ctx, x, y, out, dout, dx, dy);
 }
 
+#ifdef PADDLE_WITH_CUDA
+// cuda definition
+template <typename DeviceContext, typename T>
+typename std::enable_if<
+    std::is_same<DeviceContext, platform::CUDADeviceContext>::value>::type
+elementwise_add_grad(const framework::ExecutionContext &ctx,
+                     const framework::Tensor *x, const framework::Tensor *y,
+                     const framework::Tensor *out,
+                     const framework::Tensor *dout, framework::Tensor *dx,
+                     framework::Tensor *dy);
+#endif
+
 template <typename DeviceContext, typename T>
 class ElementwiseAddGradKernel : public ElemwiseGradKernel<T> {
  public:
@@ -151,8 +135,7 @@ class ElementwiseAddGradKernel : public ElemwiseGradKernel<T> {
     auto *out = dout;
     auto *x = dout, *y = dout;
 
-    if (platform::is_cpu_place(ctx.GetPlace()) && dx != nullptr &&
-        dy != nullptr && (dx->dims() == dy->dims())) {
+    if (dx != nullptr && dy != nullptr && (dx->dims() == dy->dims())) {
       elementwise_add_grad<DeviceContext, T>(ctx, x, y, out, dout, dx, dy);
     } else {
       default_elementwise_add_grad<DeviceContext, T>(ctx, x, y, out, dout, dx,

paddle/fluid/operators/elementwise/elementwise_div_op.cc

@@ -20,6 +20,34 @@ limitations under the License. */
 namespace paddle {
 namespace operators {
 
+template <typename T>
+struct SameDimsElemwiseDiv<
+    platform::CPUDeviceContext, T,
+    typename std::enable_if<std::is_floating_point<T>::value>::type> {
+  void operator()(const framework::ExecutionContext &ctx,
+                  const framework::Tensor *x, const framework::Tensor *y,
+                  framework::Tensor *z) {
+    auto blas = math::GetBlas<platform::CPUDeviceContext, T>(ctx);
+    blas.VDIV(x->numel(), x->data<T>(), y->data<T>(), z->data<T>());
+  }
+};
+
+template <typename T>
+struct SameDimsElemwiseDiv<
+    platform::CPUDeviceContext, T,
+    typename std::enable_if<!std::is_floating_point<T>::value>::type> {
+  void operator()(const framework::ExecutionContext &ctx,
+                  const framework::Tensor *x, const framework::Tensor *y,
+                  framework::Tensor *z) {
+    auto eigen_x = framework::EigenVector<T>::Flatten(*x);
+    auto eigen_y = framework::EigenVector<T>::Flatten(*y);
+    auto eigen_z = framework::EigenVector<T>::Flatten(*z);
+    auto &place = *ctx.template device_context<platform::CPUDeviceContext>()
+                       .eigen_device();
+    eigen_z.device(place) = eigen_x / eigen_y;
+  }
+};
+
 class ElementwiseDivOpMaker : public ElementwiseOpMaker {
  protected:
   std::string GetName() const override { return "Div"; }

paddle/fluid/operators/elementwise/elementwise_div_op.cu

@@ -12,9 +12,87 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
 #include "paddle/fluid/operators/elementwise/elementwise_div_op.h"
+#include "paddle/fluid/operators/elementwise/elementwise_op_function.cu.h"
+#include "paddle/fluid/operators/elementwise/elementwise_op_function.h"
 #include "paddle/fluid/platform/float16.h"
 
 namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+struct SameDimsElemwiseDiv<platform::CUDADeviceContext, T> {
+  void operator()(const framework::ExecutionContext& ctx,
+                  const framework::Tensor* x, const framework::Tensor* y,
+                  framework::Tensor* z) {
+    DivRangeFunctor<T> functor(x->data<T>(), y->data<T>(), z->data<T>());
+    auto& dev_ctx = ctx.template device_context<platform::CUDADeviceContext>();
+    platform::ForRange<platform::CUDADeviceContext> for_range(dev_ctx,
+                                                              x->numel());
+    for_range(functor);
+  }
+};
+
+template <>
+struct SameDimsElemwiseDiv<platform::CUDADeviceContext, platform::float16> {
+  void operator()(const framework::ExecutionContext& ctx,
+                  const framework::Tensor* x, const framework::Tensor* y,
+                  framework::Tensor* z) {
+    auto size = x->numel();
+    dim3 gird_size = dim3(
+        (size / 2 + PADDLE_CUDA_THREAD_SIZE - 1) / PADDLE_CUDA_THREAD_SIZE, 1);
+    dim3 block_size = dim3(PADDLE_CUDA_THREAD_SIZE, 1);
+    const half* x2 =
+        reinterpret_cast<const half*>(x->data<platform::float16>());
+    const half* y2 =
+        reinterpret_cast<const half*>(y->data<platform::float16>());
+    half* z2 = reinterpret_cast<half*>(z->data<platform::float16>());
+    SameDimsElemwiseDivCUDAKernel<<<
+        gird_size, block_size, 0,
+        ctx.template device_context<platform::CUDADeviceContext>().stream()>>>(
+        x2, y2, z2, size);
+  }
+};
+
+template <typename T>
+static __global__ void SimpleElemwiseDivGradCUDAKernel(const T* x, const T* y,
+                                                       const T* out,
+                                                       const T* dout,
+                                                       int64_t size, T* dx,
+                                                       T* dy) {
+  int col = blockIdx.x * blockDim.x + threadIdx.x;
+
+  while (col < size) {
+    T o = dout[col];
+    dx[col] = o / y[col];
+    dy[col] = -o * out[col] / y[col];
+    col += blockDim.x * gridDim.x;
+  }
+}
+
+template <typename DeviceContext, typename T>
+typename std::enable_if<
+    std::is_same<DeviceContext, plat::CUDADeviceContext>::value>::type
+elementwise_div_grad(const framework::ExecutionContext& ctx,
+                     const framework::Tensor* x, const framework::Tensor* y,
+                     const framework::Tensor* out,
+                     const framework::Tensor* dout, framework::Tensor* dx,
+                     framework::Tensor* dy) {
+  dim3 block_size = dim3(PADDLE_CUDA_THREAD_SIZE, 1);
+  auto size = x->numel();
+  dim3 gird_size =
+      dim3((size + PADDLE_CUDA_THREAD_SIZE - 1) / PADDLE_CUDA_THREAD_SIZE, 1);
+  SimpleElemwiseDivGradCUDAKernel<
+      T><<<gird_size, block_size, 0,
+           ctx.template device_context<plat::CUDADeviceContext>().stream()>>>(
+      x->data<T>(), y->data<T>(), out->data<T>(), dout->data<T>(), size,
+      dx->mutable_data<T>(ctx.GetPlace()), dy->mutable_data<T>(ctx.GetPlace()));
+}
+
+}  // namespace operators
+}  // namespace paddle
 
 REGISTER_OP_CUDA_KERNEL(
     elementwise_div,

paddle/fluid/operators/elementwise/elementwise_div_op.h

@@ -17,16 +17,29 @@ limitations under the License. */
 #include <vector>
 #include "paddle/fluid/operators/elementwise/elementwise_mul_op.h"
 #include "paddle/fluid/operators/elementwise/elementwise_op.h"
+#include "paddle/fluid/operators/elementwise/elementwise_op_function.cu.h"
 #include "paddle/fluid/operators/elementwise/elementwise_op_function.h"
 #include "paddle/fluid/operators/elementwise/elementwise_sub_op.h"
+#include "paddle/fluid/operators/math/blas.h"
 #include "paddle/fluid/operators/reduce_ops/reduce_op.h"
 
 namespace paddle {
 namespace operators {
 
-template <typename T>
-struct DivFunctor {
-  inline HOSTDEVICE T operator()(T a, T b) const { return a / b; }
+template <typename DeviceContext, typename T>
+void default_elementwise_div(const framework::ExecutionContext& ctx,
+                             const framework::Tensor* x,
+                             const framework::Tensor* y, framework::Tensor* z) {
+  int axis = ctx.Attr<int>("axis");
+  ElementwiseComputeEx<DivFunctor<T>, DeviceContext, T>(ctx, x, y, axis,
+                                                        DivFunctor<T>(), z);
+}
+
+template <typename DeviceContext, typename T, class Enable = void>
+struct SameDimsElemwiseDiv {
+  void operator()(const framework::ExecutionContext& ctx,
+                  const framework::Tensor* x, const framework::Tensor* y,
+                  framework::Tensor* z);
 };
 
 template <typename DeviceContext, typename T>
@@ -36,11 +49,15 @@ class ElementwiseDivKernel : public framework::OpKernel<T> {
     auto* x = ctx.Input<framework::LoDTensor>("X");
     auto* y = ctx.Input<framework::LoDTensor>("Y");
     auto* z = ctx.Output<framework::LoDTensor>("Out");
-
     z->mutable_data<T>(ctx.GetPlace());
-    int axis = ctx.Attr<int>("axis");
-    ElementwiseComputeEx<DivFunctor<T>, DeviceContext, T>(ctx, x, y, axis,
-                                                          DivFunctor<T>(), z);
+
+    auto dims_equal = x->dims() == y->dims();
+    if (dims_equal) {
+      SameDimsElemwiseDiv<DeviceContext, T> same_dims_div;
+      same_dims_div(ctx, x, y, z);
+    } else {
+      default_elementwise_div<DeviceContext, T>(ctx, x, y, z);
+    }
   }
 };
 
@@ -63,6 +80,31 @@ struct DivDoubleDY {
   }
 };
 
+template <typename DeviceContext, typename T>
+typename std::enable_if<
+    std::is_same<DeviceContext, platform::CPUDeviceContext>::value>::type
+elementwise_div_grad(const framework::ExecutionContext& ctx,
+                     const framework::Tensor* x, const framework::Tensor* y,
+                     const framework::Tensor* out,
+                     const framework::Tensor* dout, framework::Tensor* dx,
+                     framework::Tensor* dy) {
+  int axis = ctx.Attr<int>("axis");
+  ElemwiseGradCompute<DeviceContext, T, DivGradDX<T>, DivGradDY<T>>(
+      ctx, *x, *y, *out, *dout, axis, dx, dy, DivGradDX<T>(), DivGradDY<T>());
+}
+
+#ifdef PADDLE_WITH_CUDA
+// cuda definition
+template <typename DeviceContext, typename T>
+typename std::enable_if<
+    std::is_same<DeviceContext, platform::CUDADeviceContext>::value>::type
+elementwise_div_grad(const framework::ExecutionContext& ctx,
+                     const framework::Tensor* x, const framework::Tensor* y,
+                     const framework::Tensor* out,
+                     const framework::Tensor* dout, framework::Tensor* dx,
+                     framework::Tensor* dy);
+#endif
+
 template <typename DeviceContext, typename T>
 class ElementwiseDivGradKernel : public ElemwiseGradKernel<T> {
  public:
@@ -76,11 +118,15 @@ class ElementwiseDivGradKernel : public ElemwiseGradKernel<T> {
     auto* dx = ctx.Output<Tensor>(framework::GradVarName("X"));
     auto* dy = ctx.Output<Tensor>(framework::GradVarName("Y"));
     int axis = ctx.Attr<int>("axis");
-
     auto* x = dout;  // Fake x, not used
 
+    if (dx != nullptr && dy != nullptr && (dx->dims() == dy->dims())) {
+      elementwise_div_grad<DeviceContext, T>(ctx, x, y, out, dout, dx, dy);
+    } else {
       ElemwiseGradCompute<DeviceContext, T, DivGradDX<T>, DivGradDY<T>>(
-        ctx, *x, *y, *out, *dout, axis, dx, dy, DivGradDX<T>(), DivGradDY<T>());
+          ctx, *x, *y, *out, *dout, axis, dx, dy, DivGradDX<T>(),
+          DivGradDY<T>());
+    }
   }
 };
 

paddle/fluid/operators/elementwise/elementwise_mul_op.cc

@@ -20,6 +20,34 @@ limitations under the License. */
 namespace paddle {
 namespace operators {
 
+template <typename T>
+struct SameDimsElemwiseMul<
+    platform::CPUDeviceContext, T,
+    typename std::enable_if<std::is_floating_point<T>::value>::type> {
+  void operator()(const framework::ExecutionContext &ctx,
+                  const framework::Tensor *x, const framework::Tensor *y,
+                  framework::Tensor *z) {
+    auto blas = math::GetBlas<platform::CPUDeviceContext, T>(ctx);
+    blas.VMUL(x->numel(), x->data<T>(), y->data<T>(), z->data<T>());
+  }
+};
+
+template <typename T>
+struct SameDimsElemwiseMul<
+    platform::CPUDeviceContext, T,
+    typename std::enable_if<!std::is_floating_point<T>::value>::type> {
+  void operator()(const framework::ExecutionContext &ctx,
+                  const framework::Tensor *x, const framework::Tensor *y,
+                  framework::Tensor *z) {
+    auto eigen_x = framework::EigenVector<T>::Flatten(*x);
+    auto eigen_y = framework::EigenVector<T>::Flatten(*y);
+    auto eigen_z = framework::EigenVector<T>::Flatten(*z);
+    auto &place = *ctx.template device_context<platform::CPUDeviceContext>()
+                       .eigen_device();
+    eigen_z.device(place) = eigen_x * eigen_y;
+  }
+};
+
 class ElementwiseMulOpMaker : public ElementwiseOpMaker {
  protected:
   std::string GetName() const override { return "Mul"; }

paddle/fluid/operators/elementwise/elementwise_mul_op.cu

@@ -13,15 +13,49 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #include "paddle/fluid/operators/elementwise/elementwise_mul_op.h"
+#include "paddle/fluid/operators/elementwise/elementwise_op_function.cu.h"
 #include "paddle/fluid/platform/float16.h"
 
-#define TILE_SIZE 512
 namespace ops = paddle::operators;
 namespace plat = paddle::platform;
 
 namespace paddle {
 namespace operators {
 
+template <typename T>
+struct SameDimsElemwiseMul<platform::CUDADeviceContext, T> {
+  void operator()(const framework::ExecutionContext& ctx,
+                  const framework::Tensor* x, const framework::Tensor* y,
+                  framework::Tensor* z) {
+    MulRangeFunctor<T> functor(x->data<T>(), y->data<T>(), z->data<T>());
+    auto& dev_ctx = ctx.template device_context<platform::CUDADeviceContext>();
+    platform::ForRange<platform::CUDADeviceContext> for_range(dev_ctx,
+                                                              x->numel());
+    for_range(functor);
+  }
+};
+
+template <>
+struct SameDimsElemwiseMul<platform::CUDADeviceContext, platform::float16> {
+  void operator()(const framework::ExecutionContext& ctx,
+                  const framework::Tensor* x, const framework::Tensor* y,
+                  framework::Tensor* z) {
+    auto size = x->numel();
+    dim3 gird_size = dim3(
+        (size / 2 + PADDLE_CUDA_THREAD_SIZE - 1) / PADDLE_CUDA_THREAD_SIZE, 1);
+    dim3 block_size = dim3(PADDLE_CUDA_THREAD_SIZE, 1);
+    const half* x2 =
+        reinterpret_cast<const half*>(x->data<platform::float16>());
+    const half* y2 =
+        reinterpret_cast<const half*>(y->data<platform::float16>());
+    half* z2 = reinterpret_cast<half*>(z->data<platform::float16>());
+    SameDimsElemwiseMulCUDAKernel<<<
+        gird_size, block_size, 0,
+        ctx.template device_context<platform::CUDADeviceContext>().stream()>>>(
+        x2, y2, z2, size);
+  }
+};
+
 template <typename T>
 static __global__ void SimpleElemwiseMulGradCUDAKernel(const T* x, const T* y,
                                                        const T* out,
@@ -38,40 +72,24 @@ static __global__ void SimpleElemwiseMulGradCUDAKernel(const T* x, const T* y,
   }
 }
 
-template <typename T>
-class ElementwiseMulGradKernel<plat::CUDADeviceContext, T>
-    : public ElemwiseGradKernel<T> {
- public:
-  void Compute(const framework::ExecutionContext& ctx) const override {
-    ElemwiseGradKernel<T>::Compute(ctx);
-    using Tensor = framework::Tensor;
-
-    auto* x = ctx.Input<Tensor>("X");
-    auto* y = ctx.Input<Tensor>("Y");
-    auto* dout = ctx.Input<Tensor>(framework::GradVarName("Out"));
-    auto* out = dout;  // out is not necessary
-    auto* dx = ctx.Output<Tensor>(framework::GradVarName("X"));
-    auto* dy = ctx.Output<Tensor>(framework::GradVarName("Y"));
-    int axis = ctx.Attr<int>("axis");
-
-    if (x->dims() == y->dims() && dx && dy) {
-      dim3 block_size = dim3(TILE_SIZE, 1);
+template <typename DeviceContext, typename T>
+typename std::enable_if<
+    std::is_same<DeviceContext, plat::CUDADeviceContext>::value>::type
+elementwise_mul_grad(const framework::ExecutionContext& ctx,
+                     const framework::Tensor* x, const framework::Tensor* y,
+                     const framework::Tensor* out,
+                     const framework::Tensor* dout, framework::Tensor* dx,
+                     framework::Tensor* dy) {
+  dim3 block_size = dim3(PADDLE_CUDA_THREAD_SIZE, 1);
   auto size = x->numel();
-      dim3 gird_size = dim3((size + TILE_SIZE - 1) / TILE_SIZE, 1);
-      SimpleElemwiseMulGradCUDAKernel<T><<<
-          gird_size, block_size, 0,
+  dim3 gird_size =
+      dim3((size + PADDLE_CUDA_THREAD_SIZE - 1) / PADDLE_CUDA_THREAD_SIZE, 1);
+  SimpleElemwiseMulGradCUDAKernel<
+      T><<<gird_size, block_size, 0,
            ctx.template device_context<plat::CUDADeviceContext>().stream()>>>(
       x->data<T>(), y->data<T>(), out->data<T>(), dout->data<T>(), size,
-          dx->mutable_data<T>(ctx.GetPlace()),
-          dy->mutable_data<T>(ctx.GetPlace()));
-      return;
-    } else {
-      ElemwiseGradCompute<plat::CUDADeviceContext, T, MulGradDX<T>,
-                          MulGradDY<T>>(ctx, *x, *y, *out, *dout, axis, dx, dy,
-                                        MulGradDX<T>(), MulGradDY<T>());
-    }
-  }
-};
+      dx->mutable_data<T>(ctx.GetPlace()), dy->mutable_data<T>(ctx.GetPlace()));
+}
 
 }  // namespace operators
 }  // namespace paddle

paddle/fluid/operators/elementwise/elementwise_mul_op.h

@@ -14,17 +14,13 @@ limitations under the License. */
 
 #pragma once
 #include "paddle/fluid/operators/elementwise/elementwise_op.h"
+#include "paddle/fluid/operators/elementwise/elementwise_op_function.cu.h"
 #include "paddle/fluid/operators/elementwise/elementwise_op_function.h"
 #include "paddle/fluid/operators/math/blas.h"
 
 namespace paddle {
 namespace operators {
 
-template <typename T>
-struct MulFunctor {
-  inline HOSTDEVICE T operator()(T a, T b) const { return a * b; }
-};
-
 template <typename DeviceContext, typename T>
 void default_elementwise_mul(const framework::ExecutionContext& ctx,
                              const framework::Tensor* x,
@@ -33,32 +29,12 @@ void default_elementwise_mul(const framework::ExecutionContext& ctx,
   ElementwiseComputeEx<MulFunctor<T>, DeviceContext, T>(ctx, x, y, axis,
                                                         MulFunctor<T>(), z);
 }
-
-template <typename DeviceContext, typename T>
-typename std::enable_if<
-    std::is_floating_point<T>::value &&
-    std::is_same<DeviceContext, platform::CPUDeviceContext>::value>::type
-elementwise_mul_same_dims(const framework::ExecutionContext& ctx,
-                          const framework::Tensor* x,
-                          const framework::Tensor* y, framework::Tensor* z) {
-  auto blas = math::GetBlas<DeviceContext, T>(ctx);
-  blas.VMUL(x->numel(), x->data<T>(), y->data<T>(), z->data<T>());
-}
-
-template <typename DeviceContext, typename T>
-typename std::enable_if<
-    !std::is_floating_point<T>::value ||
-    !std::is_same<DeviceContext, platform::CPUDeviceContext>::value>::type
-elementwise_mul_same_dims(const framework::ExecutionContext& ctx,
-                          const framework::Tensor* x,
-                          const framework::Tensor* y, framework::Tensor* z) {
-  auto eigen_x = framework::EigenVector<T>::Flatten(*x);
-  auto eigen_y = framework::EigenVector<T>::Flatten(*y);
-  auto eigen_z = framework::EigenVector<T>::Flatten(*z);
-
-  auto& place = *ctx.template device_context<DeviceContext>().eigen_device();
-  eigen_z.device(place) = eigen_x * eigen_y;
-}
+template <typename DeviceContext, typename T, class Enable = void>
+struct SameDimsElemwiseMul {
+  void operator()(const framework::ExecutionContext& ctx,
+                  const framework::Tensor* x, const framework::Tensor* y,
+                  framework::Tensor* z);
+};
 
 template <typename DeviceContext, typename T>
 class ElementwiseMulKernel : public framework::OpKernel<T> {
@@ -92,7 +68,8 @@ class ElementwiseMulKernel : public framework::OpKernel<T> {
 
     z->mutable_data<T>(ctx.GetPlace());
     if (x.numel() == y->numel()) {
-      elementwise_mul_same_dims<DeviceContext, T>(ctx, &x, y, z);
+      SameDimsElemwiseMul<DeviceContext, T> same_dims_mul;
+      same_dims_mul(ctx, &x, y, z);
     } else {
       default_elementwise_mul<DeviceContext, T>(ctx, &x, y, z);
     }
@@ -109,6 +86,31 @@ struct MulGradDY {
   HOSTDEVICE T operator()(T x, T y, T out, T dout) const { return dout * x; }
 };
 
+template <typename DeviceContext, typename T>
+typename std::enable_if<
+    std::is_same<DeviceContext, platform::CPUDeviceContext>::value>::type
+elementwise_mul_grad(const framework::ExecutionContext& ctx,
+                     const framework::Tensor* x, const framework::Tensor* y,
+                     const framework::Tensor* out,
+                     const framework::Tensor* dout, framework::Tensor* dx,
+                     framework::Tensor* dy) {
+  int axis = ctx.Attr<int>("axis");
+  ElemwiseGradCompute<DeviceContext, T, MulGradDX<T>, MulGradDY<T>>(
+      ctx, *x, *y, *out, *dout, axis, dx, dy, MulGradDX<T>(), MulGradDY<T>());
+}
+
+#ifdef PADDLE_WITH_CUDA
+// cuda definition
+template <typename DeviceContext, typename T>
+typename std::enable_if<
+    std::is_same<DeviceContext, platform::CUDADeviceContext>::value>::type
+elementwise_mul_grad(const framework::ExecutionContext& ctx,
+                     const framework::Tensor* x, const framework::Tensor* y,
+                     const framework::Tensor* out,
+                     const framework::Tensor* dout, framework::Tensor* dx,
+                     framework::Tensor* dy);
+#endif
+
 template <typename DeviceContext, typename T>
 class ElementwiseMulGradKernel : public ElemwiseGradKernel<T> {
  public:
@@ -123,8 +125,13 @@ class ElementwiseMulGradKernel : public ElemwiseGradKernel<T> {
     auto* dx = ctx.Output<Tensor>(framework::GradVarName("X"));
     auto* dy = ctx.Output<Tensor>(framework::GradVarName("Y"));
     int axis = ctx.Attr<int>("axis");
+    if (dx != nullptr && dy != nullptr && (dx->dims() == dy->dims())) {
+      elementwise_mul_grad<DeviceContext, T>(ctx, x, y, out, dout, dx, dy);
+    } else {
       ElemwiseGradCompute<DeviceContext, T, MulGradDX<T>, MulGradDY<T>>(
-        ctx, *x, *y, *out, *dout, axis, dx, dy, MulGradDX<T>(), MulGradDY<T>());
+          ctx, *x, *y, *out, *dout, axis, dx, dy, MulGradDX<T>(),
+          MulGradDY<T>());
+    }
   }
 };
 

paddle/fluid/operators/elementwise/elementwise_op_function.cu.h

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+    http://www.apache.org/licenses/LICENSE-2.0
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#pragma once
+
+#include <glog/logging.h>
+#include "paddle/fluid/platform/float16.h"
+#include "paddle/fluid/platform/hostdevice.h"
+
+#define PADDLE_CUDA_THREAD_SIZE 512
+
+#ifdef PADDLE_WITH_CUDA
+#include <cuda.h>
+#endif  // PADDLE_WITH_CUDA
+
+#ifdef PADDLE_CUDA_FP16
+#include <cuda_fp16.h>
+#endif
+
+#if CUDA_VERSION < 9000
+#define __h2div h2div
+#endif
+
+namespace paddle {
+namespace operators {
+
+#define DEFINE_SIMPLE_BINARY_FUNCTOR(Func, expr)                   \
+  template <typename T>                                            \
+  struct Func##Functor {                                           \
+    inline HOSTDEVICE T operator()(const T& a, const T& b) const { \
+      return a expr b;                                             \
+    }                                                              \
+  };
+
+DEFINE_SIMPLE_BINARY_FUNCTOR(Add, +)
+DEFINE_SIMPLE_BINARY_FUNCTOR(Sub, -)
+DEFINE_SIMPLE_BINARY_FUNCTOR(Mul, *)
+DEFINE_SIMPLE_BINARY_FUNCTOR(Div, /)
+#undef DEFINE_SIMPLE_BINARY_FUNCTOR
+
+#define DEFINE_SIMPLE_CUDA_BINARY_FUNCTOR(Func, expr)                         \
+  template <typename T>                                                       \
+  struct Func##RangeFunctor {                                                 \
+    Func##RangeFunctor(const T* x, const T* y, T* z) : x_(x), y_(y), z_(z) {} \
+    inline HOSTDEVICE void operator()(size_t id) const {                      \
+      z_[id] = x_[id] expr y_[id];                                            \
+    }                                                                         \
+    const T* x_;                                                              \
+    const T* y_;                                                              \
+    T* z_;                                                                    \
+  };
+DEFINE_SIMPLE_CUDA_BINARY_FUNCTOR(Add, +)
+DEFINE_SIMPLE_CUDA_BINARY_FUNCTOR(Sub, -)
+DEFINE_SIMPLE_CUDA_BINARY_FUNCTOR(Mul, *)
+DEFINE_SIMPLE_CUDA_BINARY_FUNCTOR(Div, /)
+#undef DEFINE_SIMPLE_CUDA_BINARY_FUNCTOR
+
+#ifdef PADDLE_CUDA_FP16
+inline DEVICE half2 half2_add(const half2& a, const half2& b) {
+#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
+  return __hadd2(a, b);
+#else
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float b1 = __low2float(b);
+  float b2 = __high2float(b);
+  float r1 = a1 + b1;
+  float r2 = a2 + b2;
+  return __floats2half2_rn(r1, r2);
+#endif
+}
+
+inline DEVICE half2 half2_sub(const half2& a, const half2& b) {
+#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
+  return __hsub2(a, b);
+#else
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float b1 = __low2float(b);
+  float b2 = __high2float(b);
+  float r1 = a1 - b1;
+  float r2 = a2 - b2;
+  return __floats2half2_rn(r1, r2);
+#endif
+}
+
+inline DEVICE half2 half2_mul(const half2& a, const half2& b) {
+#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
+  return __hmul2(a, b);
+#else
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float b1 = __low2float(b);
+  float b2 = __high2float(b);
+  float r1 = a1 * b1;
+  float r2 = a2 * b2;
+  return __floats2half2_rn(r1, r2);
+#endif
+}
+
+inline DEVICE half2 half2_div(const half2& a, const half2& b) {
+#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
+  return __h2div(a, b);
+#else
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float b1 = __low2float(b);
+  float b2 = __high2float(b);
+  float r1 = a1 / b1;
+  float r2 = a2 / b2;
+  return __floats2half2_rn(r1, r2);
+#endif
+}
+
+#define DEFINE_SIMPLE_CUDA_BINARY_KERNEL(Func, expr, FP16Function)           \
+  template <typename T>                                                      \
+  __global__ void SameDimsElemwise##Func##CUDAKernel(const T* x, const T* y, \
+                                                     T* z, int64_t size) {   \
+    int col = blockIdx.x * blockDim.x + threadIdx.x;                         \
+    while (col < size) {                                                     \
+      z[col] = x[col] expr y[col];                                           \
+      col += blockDim.x * gridDim.x;                                         \
+    }                                                                        \
+  }                                                                          \
+  template <>                                                                \
+  inline __global__ void SameDimsElemwise##Func##CUDAKernel<half>(           \
+      const half* x, const half* y, half* z, int64_t size) {                 \
+    int start = threadIdx.x + blockDim.x * blockIdx.x;                       \
+    int stride = blockDim.x * gridDim.x;                                     \
+    int n2 = size / 2;                                                       \
+    const half2* x2 = reinterpret_cast<const half2*>(x);                     \
+    const half2* y2 = reinterpret_cast<const half2*>(y);                     \
+    half2* z2 = reinterpret_cast<half2*>(z);                                 \
+    for (int i = start; i < n2; i += stride) {                               \
+      z2[i] = FP16Function(x2[i], y2[i]);                                    \
+    }                                                                        \
+    if (start == 0 && (size % 2)) {                                          \
+      z[size - 1] = __float2half(__half2float(x[size - 1])                   \
+                                     expr __half2float(y[size - 1]));        \
+    }                                                                        \
+  }
+DEFINE_SIMPLE_CUDA_BINARY_KERNEL(Add, +, half2_add)
+DEFINE_SIMPLE_CUDA_BINARY_KERNEL(Sub, -, half2_sub)
+DEFINE_SIMPLE_CUDA_BINARY_KERNEL(Mul, *, half2_mul)
+DEFINE_SIMPLE_CUDA_BINARY_KERNEL(Div, /, half2_div)
+#undef DEFINE_SIMPLE_CUDA_BINARY_KERNEL
+
+#endif  // PADDLE_CUDA_FP16
+
+}  // namespace operators
+}  // namespace paddle

paddle/fluid/operators/elementwise/elementwise_sub_op.cc

@@ -20,6 +20,33 @@ limitations under the License. */
 namespace paddle {
 namespace operators {
 
+template <typename T>
+struct SameDimsElemwiseSub<
+    platform::CPUDeviceContext, T,
+    typename std::enable_if<std::is_floating_point<T>::value>::type> {
+  void operator()(const framework::ExecutionContext &ctx,
+                  const framework::Tensor *x, const framework::Tensor *y,
+                  framework::Tensor *z) {
+    auto blas = math::GetBlas<platform::CPUDeviceContext, T>(ctx);
+    blas.VSUB(x->numel(), x->data<T>(), y->data<T>(), z->data<T>());
+  }
+};
+
+template <typename T>
+struct SameDimsElemwiseSub<
+    platform::CPUDeviceContext, T,
+    typename std::enable_if<!std::is_floating_point<T>::value>::type> {
+  void operator()(const framework::ExecutionContext &ctx,
+                  const framework::Tensor *x, const framework::Tensor *y,
+                  framework::Tensor *z) {
+    auto eigen_x = framework::EigenVector<T>::Flatten(*x);
+    auto eigen_y = framework::EigenVector<T>::Flatten(*y);
+    auto eigen_z = framework::EigenVector<T>::Flatten(*z);
+    auto &place = *ctx.template device_context<platform::CPUDeviceContext>()
+                       .eigen_device();
+    eigen_z.device(place) = eigen_x - eigen_y;
+  }
+};
 class ElementwiseSubOpMaker : public ElementwiseOpMaker {
  protected:
   std::string GetName() const override { return "Sub"; }

paddle/fluid/operators/elementwise/elementwise_sub_op.cu

@@ -11,10 +11,85 @@ distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
+#include "paddle/fluid/operators/elementwise/elementwise_op_function.cu.h"
+#include "paddle/fluid/operators/elementwise/elementwise_op_function.h"
 #include "paddle/fluid/operators/elementwise/elementwise_sub_op.h"
 #include "paddle/fluid/platform/float16.h"
 
 namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+struct SameDimsElemwiseSub<platform::CUDADeviceContext, T> {
+  void operator()(const framework::ExecutionContext& ctx,
+                  const framework::Tensor* x, const framework::Tensor* y,
+                  framework::Tensor* z) {
+    SubRangeFunctor<T> functor(x->data<T>(), y->data<T>(), z->data<T>());
+    auto& dev_ctx = ctx.template device_context<platform::CUDADeviceContext>();
+    platform::ForRange<platform::CUDADeviceContext> for_range(dev_ctx,
+                                                              x->numel());
+    for_range(functor);
+  }
+};
+
+template <>
+struct SameDimsElemwiseSub<platform::CUDADeviceContext, platform::float16> {
+  void operator()(const framework::ExecutionContext& ctx,
+                  const framework::Tensor* x, const framework::Tensor* y,
+                  framework::Tensor* z) {
+    auto size = x->numel();
+    dim3 gird_size = dim3(
+        (size / 2 + PADDLE_CUDA_THREAD_SIZE - 1) / PADDLE_CUDA_THREAD_SIZE, 1);
+    dim3 block_size = dim3(PADDLE_CUDA_THREAD_SIZE, 1);
+    const half* x2 =
+        reinterpret_cast<const half*>(x->data<platform::float16>());
+    const half* y2 =
+        reinterpret_cast<const half*>(y->data<platform::float16>());
+    half* z2 = reinterpret_cast<half*>(z->data<platform::float16>());
+    SameDimsElemwiseSubCUDAKernel<<<
+        gird_size, block_size, 0,
+        ctx.template device_context<platform::CUDADeviceContext>().stream()>>>(
+        x2, y2, z2, size);
+  }
+};
+
+template <typename T>
+static __global__ void SimpleElemwiseSubGradCUDAKernel(const T* dout,
+                                                       int64_t size, T* dx,
+                                                       T* dy) {
+  int col = blockIdx.x * blockDim.x + threadIdx.x;
+
+  while (col < size) {
+    dx[col] = dout[col];
+    dy[col] = -dout[col];
+    col += blockDim.x * gridDim.x;
+  }
+}
+
+template <typename DeviceContext, typename T>
+typename std::enable_if<
+    std::is_same<DeviceContext, plat::CUDADeviceContext>::value>::type
+elementwise_sub_grad(const framework::ExecutionContext& ctx,
+                     const framework::Tensor* x, const framework::Tensor* y,
+                     const framework::Tensor* out,
+                     const framework::Tensor* dout, framework::Tensor* dx,
+                     framework::Tensor* dy) {
+  dim3 block_size = dim3(PADDLE_CUDA_THREAD_SIZE, 1);
+  auto size = x->numel();
+  dim3 gird_size =
+      dim3((size + PADDLE_CUDA_THREAD_SIZE - 1) / PADDLE_CUDA_THREAD_SIZE, 1);
+  SimpleElemwiseSubGradCUDAKernel<
+      T><<<gird_size, block_size, 0,
+           ctx.template device_context<plat::CUDADeviceContext>().stream()>>>(
+      dout->data<T>(), size, dx->mutable_data<T>(ctx.GetPlace()),
+      dy->mutable_data<T>(ctx.GetPlace()));
+}
+
+}  // namespace operators
+}  // namespace paddle
 
 REGISTER_OP_CUDA_KERNEL(
     elementwise_sub,

paddle/fluid/operators/elementwise/elementwise_sub_op.h

@@ -14,14 +14,27 @@ limitations under the License. */
 
 #pragma once
 #include "paddle/fluid/operators/elementwise/elementwise_op.h"
+#include "paddle/fluid/operators/elementwise/elementwise_op_function.cu.h"
 #include "paddle/fluid/operators/elementwise/elementwise_op_function.h"
+#include "paddle/fluid/operators/math/blas.h"
 
 namespace paddle {
 namespace operators {
 
-template <typename T>
-struct SubFunctor {
-  inline HOSTDEVICE T operator()(T a, T b) const { return a - b; }
+template <typename DeviceContext, typename T>
+void default_elementwise_sub(const framework::ExecutionContext& ctx,
+                             const framework::Tensor* x,
+                             const framework::Tensor* y, framework::Tensor* z) {
+  int axis = ctx.Attr<int>("axis");
+  ElementwiseComputeEx<SubFunctor<T>, DeviceContext, T>(ctx, x, y, axis,
+                                                        SubFunctor<T>(), z);
+}
+
+template <typename DeviceContext, typename T, class Enable = void>
+struct SameDimsElemwiseSub {
+  void operator()(const framework::ExecutionContext& ctx,
+                  const framework::Tensor* x, const framework::Tensor* y,
+                  framework::Tensor* z);
 };
 
 template <typename DeviceContext, typename T>
@@ -31,11 +44,15 @@ class ElementwiseSubKernel : public framework::OpKernel<T> {
     auto* x = ctx.Input<framework::LoDTensor>("X");
     auto* y = ctx.Input<framework::LoDTensor>("Y");
     auto* z = ctx.Output<framework::LoDTensor>("Out");
-
     z->mutable_data<T>(ctx.GetPlace());
-    int axis = ctx.Attr<int>("axis");
-    ElementwiseComputeEx<SubFunctor<T>, DeviceContext, T>(ctx, x, y, axis,
-                                                          SubFunctor<T>(), z);
+
+    auto dims_equal = x->dims() == y->dims();
+    if (dims_equal) {
+      SameDimsElemwiseSub<DeviceContext, T> same_dims_sub;
+      same_dims_sub(ctx, x, y, z);
+    } else {
+      default_elementwise_sub<DeviceContext, T>(ctx, x, y, z);
+    }
   }
 };
 
@@ -49,6 +66,31 @@ struct SubGradDY {
   HOSTDEVICE T operator()(T x, T y, T out, T dout) const { return -dout; }
 };
 
+template <typename DeviceContext, typename T>
+typename std::enable_if<
+    std::is_same<DeviceContext, platform::CPUDeviceContext>::value>::type
+elementwise_sub_grad(const framework::ExecutionContext& ctx,
+                     const framework::Tensor* x, const framework::Tensor* y,
+                     const framework::Tensor* out,
+                     const framework::Tensor* dout, framework::Tensor* dx,
+                     framework::Tensor* dy) {
+  int axis = ctx.Attr<int>("axis");
+  ElemwiseExplicitGradCompute<DeviceContext, T, SubGradDX<T>, SubGradDY<T>>(
+      ctx, *x, *y, *out, *dout, axis, dx, dy, SubGradDX<T>(), SubGradDY<T>());
+}
+
+#ifdef PADDLE_WITH_CUDA
+// cuda definition
+template <typename DeviceContext, typename T>
+typename std::enable_if<
+    std::is_same<DeviceContext, platform::CUDADeviceContext>::value>::type
+elementwise_sub_grad(const framework::ExecutionContext& ctx,
+                     const framework::Tensor* x, const framework::Tensor* y,
+                     const framework::Tensor* out,
+                     const framework::Tensor* dout, framework::Tensor* dx,
+                     framework::Tensor* dy);
+#endif
+
 template <typename DeviceContext, typename T>
 class ElementwiseSubGradKernel : public ElemwiseGradKernel<T> {
  public:
@@ -63,9 +105,13 @@ class ElementwiseSubGradKernel : public ElemwiseGradKernel<T> {
     // skip out, x, y
     auto* out = dout;
     auto *x = dout, *y = dout;
-
+    if (dx != nullptr && dy != nullptr && (dx->dims() == dy->dims())) {
+      elementwise_sub_grad<DeviceContext, T>(ctx, x, y, out, dout, dx, dy);
+    } else {
       ElemwiseExplicitGradCompute<DeviceContext, T, SubGradDX<T>, SubGradDY<T>>(
-        ctx, *x, *y, *out, *dout, axis, dx, dy, SubGradDX<T>(), SubGradDY<T>());
+          ctx, *x, *y, *out, *dout, axis, dx, dy, SubGradDX<T>(),
+          SubGradDY<T>());
+    }
   }
 };
 

paddle/fluid/operators/math/blas.h

@@ -159,9 +159,15 @@ class Blas {
   template <typename T>
   void VADD(int n, const T* x, const T* y, T* z) const;
 
+  template <typename T>
+  void VSUB(int n, const T* x, const T* y, T* z) const;
+
   template <typename T>
   void VMUL(int n, const T* x, const T* y, T* z) const;
 
+  template <typename T>
+  void VDIV(int n, const T* x, const T* y, T* z) const;
+
   template <typename T>
   void VCOPY(int n, const T* x, T* y) const;
 
@@ -275,11 +281,21 @@ class BlasT : private Blas<DeviceContext> {
     Base()->template VADD<T>(args...);
   }
 
+  template <typename... ARGS>
+  void VSUB(ARGS... args) const {
+    Base()->template VSUB<T>(args...);
+  }
+
   template <typename... ARGS>
   void VMUL(ARGS... args) const {
     Base()->template VMUL<T>(args...);
   }
 
+  template <typename... ARGS>
+  void VDIV(ARGS... args) const {
+    Base()->template VDIV<T>(args...);
+  }
+
   template <typename... ARGS>
   void VCOPY(ARGS... args) const {
     Base()->template VCOPY<T>(args...);

paddle/fluid/operators/math/blas_impl.h

@@ -99,11 +99,21 @@ struct CBlas<float> {
     platform::dynload::vsAdd(args...);
   }
 
+  template <typename... ARGS>
+  static void VSUB(ARGS... args) {
+    platform::dynload::vsSub(args...);
+  }
+
   template <typename... ARGS>
   static void VMUL(ARGS... args) {
     platform::dynload::vsMul(args...);
   }
 
+  template <typename... ARGS>
+  static void VDIV(ARGS... args) {
+    platform::dynload::vsDiv(args...);
+  }
+
   template <typename... ARGS>
   static void VEXP(ARGS... args) {
     platform::dynload::vsExp(args...);
@@ -210,11 +220,21 @@ struct CBlas<double> {
     platform::dynload::vdAdd(args...);
   }
 
+  template <typename... ARGS>
+  static void VSUB(ARGS... args) {
+    platform::dynload::vdSub(args...);
+  }
+
   template <typename... ARGS>
   static void VMUL(ARGS... args) {
     platform::dynload::vdMul(args...);
   }
 
+  template <typename... ARGS>
+  static void VDIV(ARGS... args) {
+    platform::dynload::vdDiv(args...);
+  }
+
   template <typename... ARGS>
   static void VEXP(ARGS... args) {
     platform::dynload::vdExp(args...);
@@ -443,6 +463,20 @@ void Blas<platform::CPUDeviceContext>::VADD(int n, const T *x, const T *y,
 #endif
 }
 
+template <>
+template <typename T>
+void Blas<platform::CPUDeviceContext>::VSUB(int n, const T *x, const T *y,
+                                            T *z) const {
+#ifdef PADDLE_WITH_MKLML
+  CBlas<T>::VSUB(n, x, y, z);
+#else
+  // try to find if openblas support vsub
+  for (int i = 0; i < n; ++i) {
+    z[i] = x[i] - y[i];
+  }
+#endif
+}
+
 template <>
 template <typename T>
 void Blas<platform::CPUDeviceContext>::VMUL(int n, const T *x, const T *y,
@@ -457,6 +491,20 @@ void Blas<platform::CPUDeviceContext>::VMUL(int n, const T *x, const T *y,
 #endif
 }
 
+template <>
+template <typename T>
+void Blas<platform::CPUDeviceContext>::VDIV(int n, const T *x, const T *y,
+                                            T *z) const {
+#ifdef PADDLE_WITH_MKLML
+  CBlas<T>::VDIV(n, x, y, z);
+#else
+  // try to find if openblas support vdiv
+  for (int i = 0; i < n; ++i) {
+    z[i] = x[i] / y[i];
+  }
+#endif
+}
+
 template <>
 template <typename T>
 void Blas<platform::CPUDeviceContext>::VEXP(int n, const T *x, T *y) const {

paddle/fluid/platform/dynload/mklml.h

 /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
-
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
 You may obtain a copy of the License at
-
     http://www.apache.org/licenses/LICENSE-2.0
-
 Unless required by applicable law or agreed to in writing, software
 distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
@@ -76,8 +73,12 @@ extern void* mklml_dso_handle;
   __macro(cblas_dscal);             \
   __macro(vsAdd);                   \
   __macro(vdAdd);                   \
+  __macro(vsSub);                   \
+  __macro(vdSub);                   \
   __macro(vsMul);                   \
   __macro(vdMul);                   \
+  __macro(vsDiv);                   \
+  __macro(vdDiv);                   \
   __macro(vsExp);                   \
   __macro(vdExp);                   \
   __macro(vsSqr);                   \