Add matrix inverse

cmake/cblas.cmake

@@ -1,4 +1,4 @@
-# Find the CBlas libraries
+# Find the CBlas and lapack libraries
 #
 # It will search MKL, atlas, OpenBlas, reference-cblas in order.
 #
@@ -19,6 +19,8 @@ set(MKL_ROOT $ENV{MKL_ROOT} CACHE PATH "Folder contains MKL")
 
 find_path(MKL_INCLUDE_DIR mkl.h PATHS
   ${MKL_ROOT}/include)
+find_path(MKL_INCLUDE_DIR mkl_lapacke.h PATHS
+  ${MKL_ROOT}/include)
 find_library(MKL_CORE_LIB NAMES mkl_core PATHS
   ${MKL_ROOT}/lib
   ${MKL_ROOT}/lib/intel64)
@@ -37,6 +39,7 @@ if(MKL_INCLUDE_DIR AND MKL_CORE_LIB AND MKL_SEQUENTIAL_LIB AND MKL_INTEL_LP64)
           ${MKL_SEQUENTIAL_LIB}
           ${MKL_CORE_LIB})
   add_definitions(-DPADDLE_USE_MKL)
+  message(STATUS "Found MKL (include: ${CBLAS_INC_DIR}, library: ${CBLAS_LIBS})")
   return() # return file.
 endif()
 
@@ -55,15 +58,19 @@ set(ATLAS_LIB_SEARCH_PATHS
     )
 find_path(ATLAS_INC_DIR NAMES cblas.h 
   PATHS ${ATLAS_INCLUDE_SEARCH_PATHS})
+find_path(ATLAS_CLAPACK_INC_DIR NAMES clapack.h
+  PATHS ${ATLAS_INCLUDE_SEARCH_PATHS})
 find_library(ATLAS_CBLAS_LIB NAMES cblas libcblas.so.3 
   PATHS ${ATLAS_LIB_SEARCH_PATHS})
-find_library(ATLAS_LIB NAMES atlas libatlas.so.3
+find_library(ATLAS_LIB NAMES lapack_atlas liblapack_atlas.so.3
   PATHS ${ATLAS_LIB_SEARCH_PATHS})
 
 if(ATLAS_INC_DIR AND ATLAS_CBLAS_LIB AND ATLAS_LIB)
   set(CBLAS_PROVIDER ATLAS)
-  set(CBLAS_INC_DIR ${ATLAS_INC_DIR})
+  set(CBLAS_INC_DIR ${ATLAS_INC_DIR} ${ATLAS_CLAPACK_INC_DIR})
   set(CBLAS_LIBS ${ATLAS_LIB} ${ATLAS_CBLAS_LIB})
+  add_definitions(-DPADDLE_USE_ATLAS)  
+  message(STATUS "Found Atlas (include: ${CBLAS_INC_DIR}, library: ${CBLAS_LIBS})")
   return()
 endif()
 
@@ -83,13 +90,16 @@ set(OPENBLAS_LIB_SEARCH_PATHS
 
 find_path(OPENBLAS_INC_DIR NAMES cblas.h
   PATHS ${OPENBLAS_INCLUDE_SEARCH_PATHS})
+find_path(OPENBLAS_LAPACKE_INC_DIR NAMES lapacke.h
+  PATHS ${OPENBLAS_INCLUDE_SEARCH_PATHS})
 find_library(OPENBLAS_LIB NAMES openblas
   PATHS ${OPENBLAS_LIB_SEARCH_PATHS})
 
 if(OPENBLAS_INC_DIR AND OPENBLAS_LIB)
   set(CBLAS_PROVIDER OPENBLAS)
   set(CBLAS_INC_DIR ${OPENBLAS_INC_DIR})
   set(CBLAS_LIBS ${OPENBLAS_LIB})
+  message(STATUS "Found OpenBlas (include: ${CBLAS_INC_DIR}, library: ${CBLAS_LIBS})")
   return()
 endif()
 

paddle/cuda/include/hl_cuda_cublas.h

@@ -21,8 +21,8 @@ limitations under the License. */
 /**
  * @brief   Matrix transpose: C_d = T(A_d)
  *
- * @param[in]   A_d     input matrix (M x N).
- * @param[out]  C_d     output matrix (N x M).
+ * @param[in]   A_d     input matrix (dimM x dimN).
+ * @param[out]  C_d     output matrix (dimN x dimM).
  * @param[in]   dimM    matrix height.
  * @param[in]   dimN    matrix width.
  * @param[in]   lda     the first dimension of A_d.
@@ -39,8 +39,8 @@ extern void hl_matrix_transpose(real *A_d,
 /*
  * @brief Matrix transpose, while lda = dimN, ldc = dimM.
  *
- * @param[in]   A_d     input matrix (M x N).
- * @param[out]  C_d     output matrix (N x M).
+ * @param[in]   A_d     input matrix (dimM x dimN).
+ * @param[out]  C_d     output matrix (dimN x dimM).
  * @param[in]   dimM    matrix height.
  * @param[in]   dimN    matrix width.
  *
@@ -50,6 +50,22 @@ extern void hl_matrix_transpose(real *A_d,
                                 int dimM,
                                 int dimN);
 
+/*
+ * @brief Matrix inverse
+ *
+ * @param[in]   A_d    input matrix (dimN x dimN).
+ * @param[out]  C_d    output matrix (dimN x dimN).
+ * @param[in]   dimN   matrix height = matrix width
+ * @param[in]   lda    the first dimension of A_d
+ * @param[in]   ldc    the first dimension of C_d
+ *
+ */
+extern void hl_matrix_inverse(real *A_d,
+                              real *C_d,
+                              int dimN,
+                              int lda,
+                              int ldc);
+
 /**
  * @brief   C_d = alpha*(op(A_d) * op(B_d)) + beta*C_d
  *

paddle/cuda/include/stub/hl_cuda_cublas_stub.h

@@ -30,6 +30,12 @@ inline void hl_matrix_transpose(real *A_d,
                                 int dimM,
                                 int dimN) {}
 
+inline void hl_matrix_inverse(real *A_d,
+                              real *C_d,
+                              int dimN,
+                              int lda,
+                              int ldc) {}
+
 inline void hl_matrix_mul(real *A_d, hl_trans_op_t transa,
                           real *B_d, hl_trans_op_t transb,
                           real *C_d,

paddle/cuda/src/hl_cuda_cublas.cc

@@ -15,6 +15,7 @@ limitations under the License. */
 
 #include <sys/time.h>
 #include <mutex>
+#include "hl_cuda.h"
 #include "hl_cuda_cublas.h"
 #include "hl_thread.ph"
 #include "hl_dso_loader.h"
@@ -75,6 +76,8 @@ DYNAMIC_LOAD_CUBLAS_WRAP(cublasSgemmBatched)
 DYNAMIC_LOAD_CUBLAS_WRAP(cublasDgemmBatched)
 DYNAMIC_LOAD_CUBLAS_WRAP(cublasCgemmBatched)
 DYNAMIC_LOAD_CUBLAS_WRAP(cublasZgemmBatched)
+DYNAMIC_LOAD_CUBLAS_WRAP(cublasSgetrfBatched)
+DYNAMIC_LOAD_CUBLAS_WRAP(cublasSgetriBatched)
 CUBLAS_BLAS_ROUTINE_EACH(DYNAMIC_LOAD_CUBLAS_V2_WRAP)
 
 #undef DYNAMIC_LOAD_CUBLAS_WRAP
@@ -88,10 +91,14 @@ CUBLAS_BLAS_ROUTINE_EACH(DYNAMIC_LOAD_CUBLAS_V2_WRAP)
 #define     CUBLAS_GEAM     dynload::cublasSgeam
 #define     CUBLAS_GEMV     dynload::cublasSgemv
 #define     CUBLAS_GEMM     dynload::cublasSgemm
+#define     CUBLAS_GETRF    dynload::cublasSgetrfBatched
+#define     CUBLAS_GETRI    dynload::cublasSgetriBatched
 #else
 #define     CUBLAS_GEAM     dynload::cublasDgeam
 #define     CUBLAS_GEMV     dynload::cublasDgemv
 #define     CUBLAS_GEMM     dynload::cublasDgemm
+#define     CUBLAS_GETRF    dynload::cublasDgetrfBatched
+#define     CUBLAS_GETRI    dynload::cublasDgetriBatched
 #endif
 
 const char* hl_cublas_get_error_string(cublasStatus_t status) {
@@ -162,6 +169,54 @@ void hl_matrix_transpose(real *A_d, real *C_d, int dimM, int dimN) {
   hl_matrix_transpose(A_d, C_d, dimM, dimN, dimN, dimM);
 }
 
+void hl_matrix_inverse(real *A_d, real *C_d, int dimN, int lda, int ldc) {
+  /* Solve Ax = I */
+  CHECK_NOTNULL(A_d);
+  CHECK_NOTNULL(C_d);
+
+  /* Step 1: Compute the LU decomposition of matrix A */
+  real **inout_h = &A_d;
+  real **inout_d = (real **)hl_malloc_device(sizeof(real *));
+  hl_memcpy(inout_d, inout_h, sizeof(real *));
+
+  int *pivot_d = (int *)hl_malloc_device(dimN*sizeof(int));  
+  int *info_d = (int *)t_resource.gpu_mem;
+
+  /* Note: cublasSgetrfBatched is used to calculate a number of
+     small-sized matrices. There may be a better way to reconstruct
+     the API for better performance.
+   */
+  CHECK_CUBLAS(CUBLAS_GETRF(t_resource.handle,
+	       dimN, inout_d, lda, pivot_d,
+               info_d, 1));
+
+  int info_h; 
+  hl_memcpy(&info_h, info_d, sizeof(int));
+  if (info_h != 0) {
+      LOG(FATAL) << "Factorization of matrix failed: matrix may be singular.\n";
+  }
+
+  /* Step 2: Compute the inverse of the matrix given its LU decomposition */
+  real **out_h = &C_d;
+  real **out_d = (real **)hl_malloc_device(sizeof(real *));
+  hl_memcpy(out_d, out_h, sizeof(real *));
+
+  CHECK_CUBLAS(CUBLAS_GETRI(t_resource.handle,
+	       dimN, (const real **)inout_d, lda, pivot_d,
+	       out_d, ldc, info_d, 1));
+
+  hl_memcpy(&info_h, info_d, sizeof(int));
+  if (info_h != 0) {
+      LOG(FATAL) << "Inversion of matrix failed: matrix may be singular.\n";
+  }
+
+  hl_free_mem_device(inout_d);
+  hl_free_mem_device(pivot_d);
+  hl_free_mem_device(out_d);
+
+  CHECK_SYNC("hl_matrix_inverse failed");
+}
+
 void hl_matrix_mul(real *A_d, hl_trans_op_t transa,
                    real *B_d, hl_trans_op_t transb,
                    real *C_d,

paddle/math/MathFunctions.cpp

@@ -39,6 +39,46 @@ void gemm<double>(const CBLAS_TRANSPOSE transA, const CBLAS_TRANSPOSE transB,
               beta, C, ldc);
 }
 
+template<>
+int getrf<float>(const CBLAS_ORDER order, const int M, const int N,
+                  float *A, const int lda, int *ipiv) {
+#ifdef PADDLE_USE_ATLAS
+  return clapack_sgetrf(order, M, N, A, lda, ipiv);
+#else
+  return LAPACKE_sgetrf(order, M, N, A, lda, ipiv);
+#endif
+}
+
+template<>
+int getrf<double>(const CBLAS_ORDER order, const int M, const int N,
+                   double *A, const int lda, int *ipiv) {
+#ifdef PADDLE_USE_ATLAS
+  return clapack_dgetrf(order, M, N, A, lda, ipiv);
+#else
+  return LAPACKE_dgetrf(order, M, N, A, lda, ipiv);
+#endif
+}
+
+template<>
+int getri<float>(const CBLAS_ORDER order, const int N, float *A,
+                  const int lda, const int *ipiv) {
+#ifdef PADDLE_USE_ATLAS
+  return clapack_sgetri(order, N, A, lda, ipiv);
+#else
+  return LAPACKE_sgetri(order, N, A, lda, ipiv);
+#endif
+}
+
+template<>
+int getri<double>(const CBLAS_ORDER order, const int N, double *A,
+                  const int lda, const int *ipiv) {
+#ifdef PADDLE_USE_ATLAS
+  return clapack_dgetri(order, N, A, lda, ipiv);
+#else
+  return LAPACKE_dgetri(order, N, A, lda, ipiv);
+#endif
+}
+
 template<>
 void axpy<float>(const int n, const float alpha, const float* x, float* y) {
   cblas_saxpy(n, alpha, x, 1, y, 1);

paddle/math/MathFunctions.h

@@ -21,6 +21,13 @@ limitations under the License. */
 extern "C" {
 #include <cblas.h>
 }
+#ifdef PADDLE_USE_ATLAS
+extern "C" {
+#include <clapack.h>
+}
+#else
+#include <lapacke.h>
+#endif
 #endif
 
 #include <cmath>
@@ -34,6 +41,14 @@ void gemm(const CBLAS_TRANSPOSE transA, const CBLAS_TRANSPOSE transB,
           const T* B, const int ldb,
           const T beta, T* C, const int ldc);
 
+template<class T>
+int getrf(const CBLAS_ORDER Order, const int M, const int N,
+          T *A, const int lda, int *ipiv);
+
+template<class T>
+int getri(const CBLAS_ORDER Order, const int N, T *A,
+          const int lda, const int *ipiv);
+
 template<class T>
 void axpy(const int n, const T alpha, const T* x, T* y);
 

paddle/math/Matrix.cpp

@@ -335,6 +335,30 @@ void GpuMatrix::transpose(MatrixPtr matTrans, bool memAlloc) {
   hl_matrix_transpose(data, dataTrans, height_, width_, lda, ldc);
 }
 
+
+MatrixPtr GpuMatrix::getInverse() {
+  MatrixPtr matInv;
+  inverse(matInv, true);
+  return matInv;
+}
+
+void GpuMatrix::inverse(MatrixPtr matInv, bool memAlloc) {
+  CHECK_EQ(height_, width_);
+
+  if (memAlloc) {
+    matInv = std::make_shared<GpuMatrix>(height_, width_);
+  } else {
+    CHECK(matInv != NULL);
+  }
+
+  real* data = getData();
+  real* dataInv = matInv->getData();
+  int lda = getStride();
+  int ldc = matInv->getStride();
+
+  hl_matrix_inverse(data, dataInv, height_, lda, ldc);
+}
+
 void GpuMatrix::addBias(Matrix& b, real scale) {
   CHECK(b.getHeight() == 1) << "the Bias should be a vector";
   BaseMatrix::addBias(b, scale);
@@ -1420,6 +1444,47 @@ void CpuMatrix::transpose(MatrixPtr matTrans, bool memAlloc) {
   }
 }
 
+
+MatrixPtr CpuMatrix::getInverse() {
+  MatrixPtr matInv;
+  inverse(matInv, true);
+  return matInv;
+}
+
+void CpuMatrix::inverse(MatrixPtr matInv, bool memAlloc) {
+  CHECK_EQ(height_, width_);
+
+  if (memAlloc) {
+    matInv = std::make_shared<CpuMatrix>(height_, width_);
+  } else {
+    CHECK(matInv != NULL);
+  }
+
+  CHECK_EQ(height_, matInv->getHeight());
+  CHECK_EQ(width_, matInv->getWidth());
+  matInv->copyFrom(*this);
+
+  real* data = getData();
+  real* dataInv = matInv->getData();
+  int ldc = matInv->getStride();
+
+  if (height_ == 1) {
+    CHECK_NE(*data, 0);
+    *dataInv = 1.0 / (*data);
+    return;
+  }
+
+  /* Compute the LU decomposition of the matrix */
+  std::vector<int> ipiv(height_);
+  CBLAS_ORDER order = (matInv->isTransposed() ? CblasColMajor : CblasRowMajor);
+  int info = getrf<real>(order, height_, height_, dataInv, ldc, ipiv.data());
+  CHECK_EQ(info, 0);
+
+  /* Compute the inverse of the matrix given its LU decompsotion */
+  info = getri<real>(order, height_, dataInv, ldc, ipiv.data());
+  CHECK_EQ(info, 0);
+}
+
 void CpuMatrix::convExpand(Matrix& feature, int feaImgHeight, int feaImgWidth,
                            int channels, int blockH, int blockW, int strideH,
                            int strideW, int paddingH, int paddingW,