fix gpu build error

paddle/operators/math/math_function.cc

@@ -32,7 +32,7 @@ void gemm<platform::CPUPlace, float>(const CBLAS_TRANSPOSE transA,
                                      const float beta,
                                      float* C,
                                      const int ldc,
-                                     const platform::DeviceContext* context) {
+                                     platform::DeviceContext* context) {
   cblas_sgemm(CblasRowMajor,
               transA,
               transB,
@@ -63,7 +63,7 @@ void gemm<platform::CPUPlace, double>(const CBLAS_TRANSPOSE transA,
                                       const double beta,
                                       double* C,
                                       const int ldc,
-                                      const platform::DeviceContext* context) {
+                                      platform::DeviceContext* context) {
   cblas_dgemm(CblasRowMajor,
               transA,
               transB,
@@ -80,42 +80,6 @@ void gemm<platform::CPUPlace, double>(const CBLAS_TRANSPOSE transA,
               ldc);
 }
 
-template <>
-void axpy<platform::CPUPlace, float>(const int n,
-                                     const float alpha,
-                                     const float* x,
-                                     float* y,
-                                     const platform::DeviceContext* context) {
-  cblas_saxpy(n, alpha, x, 1, y, 1);
-}
-
-template <>
-void axpy<platform::CPUPlace, double>(const int n,
-                                      const double alpha,
-                                      const double* x,
-                                      double* y,
-                                      const platform::DeviceContext* context) {
-  cblas_daxpy(n, alpha, x, 1, y, 1);
-}
-
-template <>
-float dotProduct<platform::CPUPlace, float>(
-    const int n,
-    const float* x,
-    const float* y,
-    const platform::DeviceContext* context) {
-  return cblas_sdot(n, x, 1, y, 1);
-}
-
-template <>
-double dotProduct<platform::CPUPlace, double>(
-    const int n,
-    const double* x,
-    const double* y,
-    const platform::DeviceContext* context) {
-  return cblas_ddot(n, x, 1, y, 1);
-}
-
 }  // namespace math
 }  // namespace operators
 }  // namespace paddle

paddle/operators/math/math_function.cu

@@ -20,7 +20,7 @@ namespace operators {
 namespace math {
 
 template <>
-void gemm<platform::GPUPlace float>(const CBLAS_TRANSPOSE transA,
+void gemm<platform::GPUPlace, float>(const CBLAS_TRANSPOSE transA,
                                      const CBLAS_TRANSPOSE transB,
                                      const int M,
                                      const int N,
@@ -33,16 +33,16 @@ void gemm<platform::GPUPlace float>(const CBLAS_TRANSPOSE transA,
                                      const float beta,
                                      float* C,
                                      const int ldc,
-                                    const platform::DeviceContext* context) {
+                                     platform::DeviceContext* context) {
   // Note that cublas follows fortran order, so the order is different from
   // the cblas convention.
   cublasOperation_t cuTransA =
-      (TransA == CblasNoTrans) ? CUBLAS_OP_N : CUBLAS_OP_T;
+      (transA == CblasNoTrans) ? CUBLAS_OP_N : CUBLAS_OP_T;
   cublasOperation_t cuTransB =
-      (TransB == CblasNoTrans) ? CUBLAS_OP_N : CUBLAS_OP_T;
+      (transB == CblasNoTrans) ? CUBLAS_OP_N : CUBLAS_OP_T;
                      
   PADDLE_ENFORCE(platform::dynload::cublasSgemm(
-      reinterpret_cast<const platform::CUDADeviceContext*>(context)->
+      reinterpret_cast<platform::CUDADeviceContext*>(context)->
         cublas_handle(),
       cuTransB,
       cuTransA,
@@ -73,15 +73,15 @@ void gemm<platform::GPUPlace, double>(const CBLAS_TRANSPOSE transA,
                                       const double beta,
                                       double* C,
                                       const int ldc,
-                                      const platform::DeviceContext* context) {
+                                      platform::DeviceContext* context) {
   // Note that cublas follows fortran order, so the order is different from
   // the cblas convention.
   cublasOperation_t cuTransA =
-      (TransA == CblasNoTrans) ? CUBLAS_OP_N : CUBLAS_OP_T;
+      (transA == CblasNoTrans) ? CUBLAS_OP_N : CUBLAS_OP_T;
   cublasOperation_t cuTransB =
-      (TransB == CblasNoTrans) ? CUBLAS_OP_N : CUBLAS_OP_T;
+      (transB == CblasNoTrans) ? CUBLAS_OP_N : CUBLAS_OP_T;
   PADDLE_ENFORCE(platform::dynload::cublasDgemm(
-      reinterpret_cast<const platform::CUDADeviceContext*>(context)->
+      reinterpret_cast<platform::CUDADeviceContext*>(context)->
         cublas_handle(),
       cuTransB,
       cuTransA,
@@ -99,48 +99,6 @@ void gemm<platform::GPUPlace, double>(const CBLAS_TRANSPOSE transA,
 }
 
 
-template <>
-void axpy<platform::GPUPlace, float>(const int n, 
-                                     const float alpha,
-                                     const float* x,
-                                     float* y,
-                                     const platform::DeviceContext* context) {
-  CUBLAS_ENFORCE(platform::dynload::cublasSaxpy(
-    reinterpret_cast<const platform::CUDADeviceContext*>(context)->
-      cublas_handle(), N, &alpha, X, 1, Y, 1));
-}
-
-template <>
-void axpy<platform::GPUPlace, double>(const int n,
-                                      const double alpha,
-                                      const double* x,
-                                      double* y,
-                                      const platform::DeviceContext* context) {
-  CUBLAS_ENFORCE(platform::dynload::cublasDaxpy(
-    reinterpret_cast<const platform::CUDADeviceContext*>(context)->
-      cublas_handle(), N, &alpha, X, 1, Y, 1));
-}
-
-template <>
-float dotProduct<platform::GPUPlace, float>(const int n,
-                                            const float* x,
-                                            const float* y,
-                                            const platform::DeviceContext* context) {
-  CUBLAS_ENFORCE(platform::dynload::cublasSdot(
-    reinterpret_cast<const platform::CUDADeviceContext*>(context)->
-      cublas_handle(), n, a, 1, b, 1, &result));
-}
-
-template <>
-double dotProduct<platform::GPUPlace, double>(const int n,
-                                              const double* x,
-                                              const double* y,
-                                              const platform::DeviceContext* context) {
-  CUBLAS_ENFORCE(platform::dynload::cublasDdot(
-    reinterpret_cast<const platform::CUDADeviceContext*>(context)->
-      cublas_handle(), n, a, 1, b, 1, &result));
-}
-
 }  // namespace math
 }  // namespace operators
 }  // namespace paddle

paddle/operators/math/math_function.h

@@ -58,20 +58,7 @@ void gemm(const CBLAS_TRANSPOSE transA,
           const T beta,
           T* C,
           const int ldc,
-          const platform::DeviceContext* context);
-
-template <typename Place, typename T>
-void axpy(const int n,
-          const T alpha,
-          const T* x,
-          T* y,
-          const platform::DeviceContext* context);
-
-template <typename Place, typename T>
-T dotProduct(const int n,
-             const T* x,
-             const T* y,
-             const platform::DeviceContext* context);
+          platform::DeviceContext* context);
 
 }  // namespace math
 }  // namespace operators

paddle/operators/mul_op.h

@@ -37,7 +37,8 @@ public:
     int N = out_dim[1];
     int K = in0_dim[1];
 
-    paddle::operators::math::template gemm<Place, T>(CblasNoTrans,
+    paddle::operators::math::template gemm<Place, T>(
+        CblasNoTrans,
         CblasNoTrans,
         M,
         N,
@@ -50,7 +51,7 @@ public:
         0,
         output->data<T>(),
         N,
-                                                     &context.device_context());
+        &const_cast<platform::DeviceContext&>(context.device_context()));
   }
 };