/external/deqp/framework/common/ |
D | tcuMatrix.hpp | 34 template <typename T, int Rows, int Cols> 38 typedef Vector<T, Rows> Element; 44 ROWS = Rows, enumerator 50 explicit Matrix (const T src[Rows*Cols]); 51 Matrix (const Vector<T, Rows>& src); 52 Matrix (const Matrix<T, Rows, Cols>& src); 55 Matrix<T, Rows, Cols>& operator= (const Matrix<T, Rows, Cols>& src); 56 Matrix<T, Rows, Cols>& operator*= (const Matrix<T, Rows, Cols>& src); 59 void setColumn (int colNdx, const Vector<T, Rows>& vec); 62 Vector<T, Rows>& getColumn (int ndx); [all …]
|
/external/llvm/include/llvm/CodeGen/PBQP/ |
D | Math.h | 169 Matrix(unsigned Rows, unsigned Cols) : in Matrix() argument 170 Rows(Rows), Cols(Cols), Data(new PBQPNum[Rows * Cols]) { in Matrix() 175 Matrix(unsigned Rows, unsigned Cols, PBQPNum InitVal) in Matrix() argument 176 : Rows(Rows), Cols(Cols), Data(new PBQPNum[Rows * Cols]) { in Matrix() 177 std::fill(Data, Data + (Rows * Cols), InitVal); in Matrix() 182 : Rows(M.Rows), Cols(M.Cols), Data(new PBQPNum[Rows * Cols]) { in Matrix() 183 std::copy(M.Data, M.Data + (Rows * Cols), Data); in Matrix() 188 : Rows(M.Rows), Cols(M.Cols), Data(M.Data) { in Matrix() 189 M.Rows = M.Cols = 0; in Matrix() 199 Rows = M.Rows; Cols = M.Cols; [all …]
|
/external/tensorflow/tensorflow/compiler/tests/ |
D | matrix_band_part_test.py | 35 'rows': 1, 40 'rows': 1, 45 'rows': 1, 50 'rows': 2, 55 'rows': 2, 60 'rows': 2, 65 'rows': 7, 70 'rows': 7, 75 'rows': 7, 80 'rows': 1, [all …]
|
/external/swiftshader/third_party/LLVM/include/llvm/CodeGen/PBQP/ |
D | Math.h | 116 Matrix(unsigned rows, unsigned cols) : in Matrix() argument 117 rows(rows), cols(cols), data(new PBQPNum[rows * cols]) { in Matrix() 122 Matrix(unsigned rows, unsigned cols, PBQPNum initVal) : in Matrix() argument 123 rows(rows), cols(cols), data(new PBQPNum[rows * cols]) { in Matrix() 124 std::fill(data, data + (rows * cols), initVal); in Matrix() 129 rows(m.rows), cols(m.cols), data(new PBQPNum[rows * cols]) { in Matrix() 130 std::copy(m.data, m.data + (rows * cols), data); in Matrix() 139 rows = m.rows; cols = m.cols; 140 data = new PBQPNum[rows * cols]; 141 std::copy(m.data, m.data + (rows * cols), data); [all …]
|
/external/swiftshader/third_party/llvm-7.0/llvm/include/llvm/CodeGen/PBQP/ |
D | Math.h | 128 Matrix(unsigned Rows, unsigned Cols) : in Matrix() argument 129 Rows(Rows), Cols(Cols), Data(llvm::make_unique<PBQPNum []>(Rows * Cols)) { in Matrix() 134 Matrix(unsigned Rows, unsigned Cols, PBQPNum InitVal) in Matrix() argument 135 : Rows(Rows), Cols(Cols), in Matrix() 136 Data(llvm::make_unique<PBQPNum []>(Rows * Cols)) { in Matrix() 137 std::fill(Data.get(), Data.get() + (Rows * Cols), InitVal); in Matrix() 142 : Rows(M.Rows), Cols(M.Cols), in Matrix() 143 Data(llvm::make_unique<PBQPNum []>(Rows * Cols)) { in Matrix() 144 std::copy(M.Data.get(), M.Data.get() + (Rows * Cols), Data.get()); in Matrix() 149 : Rows(M.Rows), Cols(M.Cols), Data(std::move(M.Data)) { in Matrix() [all …]
|
/external/eigen/test/ |
D | sparse_basic.cpp | 22 const Index rows = ref.rows(); in sparse_basic() local 31 double density = (std::max)(8./(rows*cols), 0.01); in sparse_basic() 38 SparseMatrixType m(rows, cols); in sparse_basic() 39 DenseMatrix refMat = DenseMatrix::Zero(rows, cols); in sparse_basic() 40 DenseVector vec1 = DenseVector::Random(rows); in sparse_basic() 69 DenseMatrix m1(rows,cols); in sparse_basic() 71 SparseMatrixType m2(rows,cols); in sparse_basic() 73 Index nnz = internal::random<int>(1,int(rows)/2); in sparse_basic() 86 Index i = internal::random<Index>(0,rows-1); in sparse_basic() 103 DenseMatrix m1(rows,cols); in sparse_basic() [all …]
|
D | diagonalmatrices.cpp | 16 enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime }; in diagonalmatrices() enumerator 17 typedef Matrix<Scalar, Rows, 1> VectorType; in diagonalmatrices() 19 typedef Matrix<Scalar, Rows, Rows> SquareMatrixType; in diagonalmatrices() 21 typedef DiagonalMatrix<Scalar, Rows> LeftDiagonalMatrix; in diagonalmatrices() 23 typedef Matrix<Scalar, Rows==Dynamic?Dynamic:2*Rows, Cols==Dynamic?Dynamic:2*Cols> BigMatrix; in diagonalmatrices() 24 Index rows = m.rows(); in diagonalmatrices() local 27 MatrixType m1 = MatrixType::Random(rows, cols), in diagonalmatrices() 28 m2 = MatrixType::Random(rows, cols); in diagonalmatrices() 29 VectorType v1 = VectorType::Random(rows), in diagonalmatrices() 30 v2 = VectorType::Random(rows); in diagonalmatrices() [all …]
|
D | array_for_matrix.cpp | 19 Index rows = m.rows(); in array_for_matrix() local 22 MatrixType m1 = MatrixType::Random(rows, cols), in array_for_matrix() 23 m2 = MatrixType::Random(rows, cols), in array_for_matrix() 24 m3(rows, cols); in array_for_matrix() 26 ColVectorType cv1 = ColVectorType::Random(rows); in array_for_matrix() 34 VERIFY_IS_APPROX((m1.array() + s1).matrix(), MatrixType::Constant(rows,cols,s1) + m1); in array_for_matrix() 35 …VERIFY_IS_APPROX(((m1*Scalar(2)).array() - s2).matrix(), (m1+m1) - MatrixType::Constant(rows,cols,… in array_for_matrix() 62 VERIFY_IS_APPROX(m1.block(0,0,rows,0).rowwise().prod(), ColVectorType::Ones(rows)); in array_for_matrix() 90 Index rows = m.rows(); in comparisons() local 93 Index r = internal::random<Index>(0, rows-1), in comparisons() [all …]
|
D | dense_storage.cpp | 14 template <typename T, int Rows, int Cols> 17 static const int Size = ((Rows==Dynamic || Cols==Dynamic) ? Dynamic : Rows*Cols); in dense_storage_copy() 18 typedef DenseStorage<T,Size, Rows,Cols, 0> DenseStorageType; in dense_storage_copy() 20 const int rows = (Rows==Dynamic) ? 4 : Rows; in dense_storage_copy() local 22 const int size = rows*cols; in dense_storage_copy() 23 DenseStorageType reference(size, rows, cols); in dense_storage_copy() 34 template <typename T, int Rows, int Cols> 37 static const int Size = ((Rows==Dynamic || Cols==Dynamic) ? Dynamic : Rows*Cols); in dense_storage_assignment() 38 typedef DenseStorage<T,Size, Rows,Cols, 0> DenseStorageType; in dense_storage_assignment() 40 const int rows = (Rows==Dynamic) ? 4 : Rows; in dense_storage_assignment() local [all …]
|
D | householder.cpp | 21 Index rows = m.rows(); in householder() local 34 …E_MAX(MatrixType::RowsAtCompileTime,MatrixType::ColsAtCompileTime), 1> _tmp((std::max)(rows,cols)); in householder() 41 VectorType v1 = VectorType::Random(rows), v2; in householder() 46 if(rows>=2) VERIFY_IS_MUCH_SMALLER_THAN(v1.tail(rows-1).norm(), v1.norm()); in householder() 47 v1 = VectorType::Random(rows); in householder() 52 MatrixType m1(rows, cols), in householder() 53 m2(rows, cols); in householder() 55 v1 = VectorType::Random(rows); in householder() 56 if(even) v1.tail(rows-1).setZero(); in householder() 62 if(rows>=2) VERIFY_IS_MUCH_SMALLER_THAN(m1.block(1,0,rows-1,cols).norm(), m1.norm()); in householder() [all …]
|
D | sparse_vector.cpp | 12 template<typename Scalar,typename StorageIndex> void sparse_vector(int rows, int cols) in sparse_vector() argument 14 double densityMat = (std::max)(8./(rows*cols), 0.01); in sparse_vector() 15 double densityVec = (std::max)(8./(rows), 0.1); in sparse_vector() 22 SparseMatrixType m1(rows,rows); in sparse_vector() 23 SparseVectorType v1(rows), v2(rows), v3(rows); in sparse_vector() 24 DenseMatrix refM1 = DenseMatrix::Zero(rows, rows); in sparse_vector() 25 DenseVector refV1 = DenseVector::Random(rows), in sparse_vector() 26 refV2 = DenseVector::Random(rows), in sparse_vector() 27 refV3 = DenseVector::Random(rows); in sparse_vector() 58 SparseVectorType v4(rows); in sparse_vector() [all …]
|
D | product_small.cpp | 36 for(Index i=0;i<C.rows();++i) in ref_prod() 43 template<typename T, int Rows, int Cols, int Depth, int OC, int OA, int OB> 44 typename internal::enable_if<! ( (Rows ==1&&Depth!=1&&OA==ColMajor) 45 || (Depth==1&&Rows !=1&&OA==RowMajor) 48 || (Rows ==1&&Cols !=1&&OC==ColMajor) 49 || (Cols ==1&&Rows !=1&&OC==RowMajor)),void>::type 50 test_lazy_single(int rows, int cols, int depth) in test_lazy_single() argument 52 Matrix<T,Rows,Depth,OA> A(rows,depth); A.setRandom(); in test_lazy_single() 54 Matrix<T,Rows,Cols,OC> C(rows,cols); C.setRandom(); in test_lazy_single() 55 Matrix<T,Rows,Cols,OC> D(C); in test_lazy_single() [all …]
|
D | array.cpp | 20 Index rows = m.rows(); in array() local 23 ArrayType m1 = ArrayType::Random(rows, cols), in array() 24 m2 = ArrayType::Random(rows, cols), in array() 25 m3(rows, cols); in array() 29 ColVectorType cv1 = ColVectorType::Random(rows); in array() 37 VERIFY_IS_APPROX(m1 + s1, ArrayType::Constant(rows,cols,s1) + m1); in array() 39 VERIFY_IS_APPROX(m1 - s1, m1 - ArrayType::Constant(rows,cols,s1)); in array() 40 VERIFY_IS_APPROX(s1 - m1, ArrayType::Constant(rows,cols,s1) - m1); in array() 41 VERIFY_IS_APPROX((m1*Scalar(2)) - s2, (m1+m1) - ArrayType::Constant(rows,cols,s2) ); in array() 51 …ArrayType::Map(m1.data(), m1.rows(), m1.cols()) -= ArrayType::Map(m2.data(), m2.rows(), m2.cols()); in array() [all …]
|
D | mapstaticmethods.cpp | 73 Index rows = m.rows(), cols = m.cols(); in run() local 77 PlainObjectType::Map(ptr, rows, cols).setZero(); in run() 78 PlainObjectType::MapAligned(ptr, rows, cols).setZero(); in run() 79 PlainObjectType::Map(const_ptr, rows, cols).sum(); in run() 80 PlainObjectType::MapAligned(const_ptr, rows, cols).sum(); in run() 82 PlainObjectType::Map(ptr, rows, cols, InnerStride<>(i)).setZero(); in run() 83 PlainObjectType::MapAligned(ptr, rows, cols, InnerStride<>(i)).setZero(); in run() 84 PlainObjectType::Map(const_ptr, rows, cols, InnerStride<>(i)).sum(); in run() 85 PlainObjectType::MapAligned(const_ptr, rows, cols, InnerStride<>(i)).sum(); in run() 87 PlainObjectType::Map(ptr, rows, cols, InnerStride<2>()).setZero(); in run() [all …]
|
D | product.h | 33 Index rows = m.rows(); in product() local 38 MatrixType m1 = MatrixType::Random(rows, cols), in product() 39 m2 = MatrixType::Random(rows, cols), in product() 40 m3(rows, cols); in product() 42 identity = RowSquareMatrixType::Identity(rows, rows), in product() 43 square = RowSquareMatrixType::Random(rows, rows), in product() 44 res = RowSquareMatrixType::Random(rows, rows); in product() 48 RowVectorType v1 = RowVectorType::Random(rows); in product() 54 Index r = internal::random<Index>(0, rows-1), in product() 78 VERIFY_IS_APPROX(MatrixType::Identity(rows, cols)(r,c), static_cast<Scalar>(r==c)); in product() [all …]
|
/external/libaom/libaom/third_party/libyuv/source/ |
D | convert_jpeg.cc | 37 int rows) { in JpegCopyI420() argument 45 dest->w, rows); in JpegCopyI420() 46 dest->y += rows * dest->y_stride; in JpegCopyI420() 47 dest->u += ((rows + 1) >> 1) * dest->u_stride; in JpegCopyI420() 48 dest->v += ((rows + 1) >> 1) * dest->v_stride; in JpegCopyI420() 49 dest->h -= rows; in JpegCopyI420() 55 int rows) { in JpegI422ToI420() argument 63 dest->w, rows); in JpegI422ToI420() 64 dest->y += rows * dest->y_stride; in JpegI422ToI420() 65 dest->u += ((rows + 1) >> 1) * dest->u_stride; in JpegI422ToI420() [all …]
|
/external/eigen/doc/ |
D | AsciiQuickReference.txt | 6 Matrix<double, 3, 3> A; // Fixed rows and cols. Same as Matrix3d. 7 Matrix<double, 3, Dynamic> B; // Fixed rows, dynamic cols. 19 C.rows() // size(C,1) // number of rows 31 7, 8, 9; // and then the rows are stacked. 36 MatrixXd::Identity(rows,cols) // eye(rows,cols) 37 C.setIdentity(rows,cols) // C = eye(rows,cols) 38 MatrixXd::Zero(rows,cols) // zeros(rows,cols) 39 C.setZero(rows,cols) // C = zeros(rows,cols) 40 MatrixXd::Ones(rows,cols) // ones(rows,cols) 41 C.setOnes(rows,cols) // C = ones(rows,cols) [all …]
|
/external/gemmlowp/meta/generators/ |
D | gemm_NxMxK_neon.py | 20 def GenerateCommonTempsCountersAndConsts(emitter, rows): argument 35 if rows is not 0: 37 'std::int32_t*', 'zipped_lhs_%d_offsets' % rows, 38 'reinterpret_cast<std::int32_t*>(zipped_lhs + padded_k * %d)' % rows) 47 def GenerateQuantized8BitTempsCountersAndConsts(emitter, rows): argument 49 GenerateCommonTempsCountersAndConsts(emitter, rows) 64 def GenerateFullTempsCountersAndConsts(emitter, result_type, rows): argument 66 GenerateCommonTempsCountersAndConsts(emitter, rows) 76 def ZipName(rows, leftovers, aligned): argument 77 return zip_Nx8_neon.BuildName(rows, leftovers, aligned) [all …]
|
/external/eigen/Eigen/src/Core/ |
D | PlainObjectBase.h | 40 static EIGEN_ALWAYS_INLINE void run(Index rows, Index cols) 45 bool error = (rows == 0 || cols == 0) ? false 46 : (rows > max_index / cols); 151 EIGEN_STRONG_INLINE Index rows() const { return m_storage.rows(); } 165 return m_storage.data()[rowId + colId * m_storage.rows()]; 188 return m_storage.data()[rowId + colId * m_storage.rows()]; 209 return m_storage.data()[rowId + colId * m_storage.rows()]; 227 : rowId + colId * m_storage.rows())); 244 : rowId + colId * m_storage.rows()), val); 262 /** Resizes \c *this to a \a rows x \a cols matrix. [all …]
|
/external/libvpx/libvpx/third_party/libyuv/source/ |
D | convert_jpeg.cc | 38 int rows) { in JpegCopyI420() argument 42 dest->v_stride, dest->w, rows); in JpegCopyI420() 43 dest->y += rows * dest->y_stride; in JpegCopyI420() 44 dest->u += ((rows + 1) >> 1) * dest->u_stride; in JpegCopyI420() 45 dest->v += ((rows + 1) >> 1) * dest->v_stride; in JpegCopyI420() 46 dest->h -= rows; in JpegCopyI420() 52 int rows) { in JpegI422ToI420() argument 56 dest->v_stride, dest->w, rows); in JpegI422ToI420() 57 dest->y += rows * dest->y_stride; in JpegI422ToI420() 58 dest->u += ((rows + 1) >> 1) * dest->u_stride; in JpegI422ToI420() [all …]
|
/external/libyuv/files/source/ |
D | convert_jpeg.cc | 38 int rows) { in JpegCopyI420() argument 42 dest->v_stride, dest->w, rows); in JpegCopyI420() 43 dest->y += rows * dest->y_stride; in JpegCopyI420() 44 dest->u += ((rows + 1) >> 1) * dest->u_stride; in JpegCopyI420() 45 dest->v += ((rows + 1) >> 1) * dest->v_stride; in JpegCopyI420() 46 dest->h -= rows; in JpegCopyI420() 52 int rows) { in JpegI422ToI420() argument 56 dest->v_stride, dest->w, rows); in JpegI422ToI420() 57 dest->y += rows * dest->y_stride; in JpegI422ToI420() 58 dest->u += ((rows + 1) >> 1) * dest->u_stride; in JpegI422ToI420() [all …]
|
/external/skqp/src/compute/hs/gen/ |
D | transpose.c | 17 // Rows must be an even number. This is enforced elsewhere. 19 // The transpose requires (cols_log2 * rows/2) row-pair blends. 23 uint32_t const rows, in hsg_transpose() argument 35 uint32_t * map_curr = ALLOCA_MACRO(rows * sizeof(*map_curr)); in hsg_transpose() 36 uint32_t * map_next = ALLOCA_MACRO(rows * sizeof(*map_next)); in hsg_transpose() 39 for (uint32_t ii=0; ii<rows; ii++) in hsg_transpose() 42 // successively transpose rows using blends in hsg_transpose() 47 for (uint32_t ii=0; ii<rows; ii++) in hsg_transpose() 54 for (uint32_t jj=0; jj<rows; jj++) in hsg_transpose() 59 map_next[ii] = stay + (rows << (cc-1)); in hsg_transpose() [all …]
|
/external/skia/src/compute/hs/gen/ |
D | transpose.c | 17 // Rows must be an even number. This is enforced elsewhere. 19 // The transpose requires (cols_log2 * rows/2) row-pair blends. 23 uint32_t const rows, in hsg_transpose() argument 35 uint32_t * map_curr = ALLOCA_MACRO(rows * sizeof(*map_curr)); in hsg_transpose() 36 uint32_t * map_next = ALLOCA_MACRO(rows * sizeof(*map_next)); in hsg_transpose() 39 for (uint32_t ii=0; ii<rows; ii++) in hsg_transpose() 42 // successively transpose rows using blends in hsg_transpose() 47 for (uint32_t ii=0; ii<rows; ii++) in hsg_transpose() 54 for (uint32_t jj=0; jj<rows; jj++) in hsg_transpose() 59 map_next[ii] = stay + (rows << (cc-1)); in hsg_transpose() [all …]
|
/external/tensorflow/tensorflow/contrib/bigtable/kernels/test_kernels/ |
D | bigtable_test_client_test.cc | 40 auto rows = table.ReadRows(std::move(rowset), filter); in TEST() local 41 EXPECT_EQ(rows.begin(), rows.end()) << "Some rows were returned in response!"; in TEST() 54 auto rows = table.ReadRows(std::move(rowset), filter); in TEST() local 55 auto itr = rows.begin(); in TEST() 56 EXPECT_NE(itr, rows.end()) << "No rows were returned in response!"; in TEST() 65 EXPECT_EQ(itr, rows.end()); in TEST() 80 auto rows = table.ReadRows(std::move(rowset), filter); in TEST() local 81 auto itr = rows.begin(); in TEST() 83 EXPECT_NE(itr, rows.end()) << "Missing rows"; in TEST() 92 EXPECT_EQ(itr, rows.end()) << "Extra rows in the response."; in TEST() [all …]
|
/external/google-fruit/extras/benchmark/tables/ |
D | fruit_wiki.yml | 28 rows: *compiler_name_row 39 rows: *compiler_name_row 50 rows: *compiler_name_row 61 rows: *compiler_name_row 72 rows: *compiler_name_row 83 rows: *compiler_name_row 104 rows: *compiler_name_row 123 rows: *compiler_name_row 142 rows: *compiler_name_row 161 rows: *compiler_name_row [all …]
|