[ROCM] fix bmm_kernel (#45530)

paddle/phi/kernels/funcs/blas/blas_impl.hip.h

@@ -1128,6 +1128,108 @@ void Blas<phi::GPUContext>::BatchedGEMM(CBLAS_TRANSPOSE transA,
   });
 }
 
+// note(wangran16): unknown bug. parameters dislocation when calling
+// GEMM_STRIDED_BATCH<float> and GEMM_STRIDED_BATCH<double>
+template <>
+template <>
+inline void Blas<phi::GPUContext>::BatchedGEMM(CBLAS_TRANSPOSE transA,
+                                               CBLAS_TRANSPOSE transB,
+                                               int M,
+                                               int N,
+                                               int K,
+                                               float alpha,
+                                               const float *A,
+                                               const float *B,
+                                               float beta,
+                                               float *C,
+                                               int batchCount,
+                                               int64_t strideA,
+                                               int64_t strideB) const {
+  // Note that cublas follows fortran order, so the order is different from
+  // the cblas convention.
+  int lda = (transA == CblasNoTrans) ? K : M;
+  int ldb = (transB == CblasNoTrans) ? N : K;
+  int ldc = N;
+  rocblas_operation cuTransA = (transA == CblasNoTrans)
+                                   ? rocblas_operation_none
+                                   : rocblas_operation_transpose;
+  rocblas_operation cuTransB = (transB == CblasNoTrans)
+                                   ? rocblas_operation_none
+                                   : rocblas_operation_transpose;
+  const int64_t strideC = M * N;
+  context_.CublasCall([&](rocblas_handle handle) {
+    PADDLE_ENFORCE_GPU_SUCCESS(
+        paddle::platform::dynload::rocblas_sgemm_strided_batched(handle,
+                                                                 cuTransB,
+                                                                 cuTransA,
+                                                                 N,
+                                                                 M,
+                                                                 K,
+                                                                 &alpha,
+                                                                 B,
+                                                                 ldb,
+                                                                 strideB,
+                                                                 A,
+                                                                 lda,
+                                                                 strideA,
+                                                                 &beta,
+                                                                 C,
+                                                                 ldc,
+                                                                 strideC,
+                                                                 batchCount));
+  });
+}
+
+template <>
+template <>
+inline void Blas<phi::GPUContext>::BatchedGEMM(CBLAS_TRANSPOSE transA,
+                                               CBLAS_TRANSPOSE transB,
+                                               int M,
+                                               int N,
+                                               int K,
+                                               double alpha,
+                                               const double *A,
+                                               const double *B,
+                                               double beta,
+                                               double *C,
+                                               int batchCount,
+                                               int64_t strideA,
+                                               int64_t strideB) const {
+  // Note that cublas follows fortran order, so the order is different from
+  // the cblas convention.
+  int lda = (transA == CblasNoTrans) ? K : M;
+  int ldb = (transB == CblasNoTrans) ? N : K;
+  int ldc = N;
+  rocblas_operation cuTransA = (transA == CblasNoTrans)
+                                   ? rocblas_operation_none
+                                   : rocblas_operation_transpose;
+  rocblas_operation cuTransB = (transB == CblasNoTrans)
+                                   ? rocblas_operation_none
+                                   : rocblas_operation_transpose;
+  const int64_t strideC = M * N;
+  context_.CublasCall([&](rocblas_handle handle) {
+    PADDLE_ENFORCE_GPU_SUCCESS(
+        paddle::platform::dynload::rocblas_dgemm_strided_batched(handle,
+                                                                 cuTransB,
+                                                                 cuTransA,
+                                                                 N,
+                                                                 M,
+                                                                 K,
+                                                                 &alpha,
+                                                                 B,
+                                                                 ldb,
+                                                                 strideB,
+                                                                 A,
+                                                                 lda,
+                                                                 strideA,
+                                                                 &beta,
+                                                                 C,
+                                                                 ldc,
+                                                                 strideC,
+                                                                 batchCount));
+  });
+}
+
 template <>
 template <>
 inline void Blas<phi::GPUContext>::BatchedGEMM(CBLAS_TRANSPOSE transA,