| /external/eigen/test/ |
| product_selfadjoint.cpp | 22 Index cols = m.cols(); local
24 MatrixType m1 = MatrixType::Random(rows, cols),
25 m2 = MatrixType::Random(rows, cols),
56 m2.block(1,1,rows-1,cols-1).template selfadjointView<Lower>().rankUpdate(v1.tail(rows-1),v2.head(cols-1));
58 m3.block(1,1,rows-1,cols-1) += v1.tail(rows-1) * v2.head(cols-1).adjoint()+ v2.head(cols-1) * v1.tail(rows-1).adjoint();
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| product_small.cpp | 37 for(Index j=0;j<C.cols();++j)
38 for(Index k=0;k<A.cols();++k)
43 template<typename T, int Rows, int Cols, int Depth, int OC, int OA, int OB>
46 || (Cols ==1&&Depth!=1&&OB==RowMajor)
47 || (Depth==1&&Cols !=1&&OB==ColMajor)
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)
53 Matrix<T,Depth,Cols,OB> B(depth,cols); B.setRandom()
87 int cols = internal::random<int>(1,12); local
116 int cols = internal::random<int>(1,12); local
152 int cols = internal::random<int>(1,12); local
[all...] |
| product_syrk.cpp | 22 Index cols = m.cols(); local
24 MatrixType m1 = MatrixType::Random(rows, cols),
25 m2 = MatrixType::Random(rows, cols),
26 m3 = MatrixType::Random(rows, cols);
27 RMatrixType rm2 = MatrixType::Random(rows, cols);
29 Rhs1 rhs1 = Rhs1::Random(internal::random<int>(1,320), cols); Rhs1 rhs11 = Rhs1::Random(rhs1.rows(), cols);
30 Rhs2 rhs2 = Rhs2::Random(rows, internal::random<int>(1,320)); Rhs2 rhs22 = Rhs2::Random(rows, rhs2.cols());
35 Index c = internal::random<Index>(0,cols-1)
[all...] |
| qr.cpp | 18 Index cols = m.cols(); local
23 MatrixType a = MatrixType::Random(rows,cols);
35 enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime };
37 Matrix<Scalar,Rows,Cols> m1 = Matrix<Scalar,Rows,Cols>::Random();
38 HouseholderQR<Matrix<Scalar,Rows,Cols> > qr(m1);
40 Matrix<Scalar,Rows,Cols> r = qr.matrixQR();
42 for(int i = 0; i < Rows; i++) for(int j = 0; j < Cols; j++) if(i>j) r(i,j) = Scalar(0);
46 Matrix<Scalar,Cols,Cols2> m2 = Matrix<Scalar,Cols,Cols2>::Random(Cols,Cols2)
[all...] |
| qr_fullpivoting.cpp | 21 cols = internal::random<Index>(min_size,max_size), local
23 rank = internal::random<Index>(1, (std::min)(rows, cols)-1);
28 createRandomPIMatrixOfRank(rank,rows,cols,m1);
31 VERIFY_IS_EQUAL(cols - qr.rank(), qr.dimensionOfKernel());
42 for(int i = 0; i < rows; i++) for(int j = 0; j < cols; j++) if(i>j) r(i,j) = Scalar(0);
52 MatrixType m2 = MatrixType::Random(cols,cols2);
54 m2 = MatrixType::Random(cols,cols2);
|
| redux.cpp | 22 Index cols = m.cols(); local
24 MatrixType m1 = MatrixType::Random(rows, cols);
28 MatrixType m1_for_prod = MatrixType::Ones(rows, cols) + RealScalar(0.2) * m1;
30 VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows, cols).sum(), Scalar(1));
31 VERIFY_IS_APPROX(MatrixType::Ones(rows, cols).sum(), Scalar(float(rows*cols))); // the float() here to shut up excessive MSVC warning about int->complex conversion being lossy
33 for(int j = 0; j < cols; j++)
41 const Scalar mean = s/Scalar(RealScalar(rows*cols));
51 Index c0 = internal::random<Index>(0,cols-1)
[all...] |
| sparse_permutations.cpp | 47 const Index cols = ref.cols(); local
56 double density = (std::max)(8./(rows*cols), 0.01);
58 SparseMatrixType mat(rows, cols), up(rows,cols), lo(rows,cols);
60 DenseMatrix mat_d = DenseMatrix::Zero(rows, cols), up_sym_d, lo_sym_d, res_d;
76 randomPermutationVector(pi, cols);
|
| sparseqr.cpp | 18 int cols = internal::random<int>(1,maxCols); local
19 double density = (std::max)(8./(rows*cols), 0.01);
21 A.resize(rows,cols);
22 dA.resize(rows,cols);
25 int nop = internal::random<int>(0, internal::random<double>(0,1) > 0.5 ? cols/2 : 0);
28 int j0 = internal::random<int>(0,cols-1);
29 int j1 = internal::random<int>(0,cols-1);
35 // if(rows<cols) {
36 // A.conservativeResize(cols,cols);
[all...] |
| stable_norm.cpp | 55 Index cols = m.cols(); local
68 MatrixType vzero = MatrixType::Zero(rows, cols),
69 vrand = MatrixType::Random(rows, cols),
70 vbig(rows, cols),
71 vsmall(rows,cols);
112 Index j = internal::random<Index>(0,cols-1);
156 Index j2 = internal::random<Index>(0,cols-1);
|
| svd_common.h | 28 Index cols = m.cols(); local
40 MatrixType sigma = MatrixType::Zero(rows,cols);
65 Index cols = m.cols(); local
66 Index diagSize = (std::min)(rows, cols);
106 Index cols = m.cols(); local
116 RhsType rhs = RhsType::Random(rows, internal::random<Index>(1, cols));
172 Index cols = m.cols()
[all...] |
| triangular.cpp | 23 typename MatrixType::Index cols = m.cols(); local
25 MatrixType m1 = MatrixType::Random(rows, cols),
26 m2 = MatrixType::Random(rows, cols),
27 m3(rows, cols),
28 m4(rows, cols),
29 r1(rows, cols),
30 r2(rows, cols);
36 if (rows*cols>1)
66 m1 = MatrixType::Random(rows, cols);
143 Index cols = m.cols(); local
[all...] |
| vectorwiseop.cpp | 24 Index cols = m.cols(); local
26 c = internal::random<Index>(0, cols-1);
28 ArrayType m1 = ArrayType::Random(rows, cols),
29 m2(rows, cols),
30 m3(rows, cols);
33 RowVectorType rowvec = RowVectorType::Random(cols);
118 Array<bool,Dynamic,Dynamic> mb(rows,cols);
141 Index cols = m.cols(); local
[all...] |
| /external/eigen/unsupported/Eigen/src/IterativeSolvers/ |
| ConstrainedConjGrad.h | 55 Index rows = C.rows(), cols = C.cols(); local
57 TmpVec d(rows), e(rows), l(cols), p(rows), q(rows), r(rows);
124 SparseMatrix<Scalar,RowMajor> CINV(C.rows(), C.cols());
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| /external/eigen/unsupported/test/ |
| special_functions.cpp | 38 Index cols = 1; local
42 ArrayType m1 = ArrayType::Random(rows,cols);
58 ArrayType m1 = ArrayType::Random(rows,cols);
59 ArrayType m2 = ArrayType::Random(rows,cols);
69 ArrayType zero = ArrayType::Zero(rows, cols);
70 ArrayType one = ArrayType::Constant(rows, cols, Scalar(1.0));
|
| /external/gemmlowp/internal/ |
| dispatch_gemm_shape.h | 70 return DstType(src.data(), src.cols(), src.rows(), src.stride());
161 assert(lhs.cols() == rhs.rows());
164 int cols = result->cols(); local
165 int depth = lhs.cols();
167 if (rows == 0 || cols == 0 || depth == 0) {
173 if (rows < cols) {
|
| single_thread_gemm.h | 75 assert(lhs.cols() == rhs.rows());
78 int cols = result->cols(); local
79 int depth = lhs.cols();
83 assert(cols > 0);
86 // The case of rows<cols should have been caught earlier and transposed.
87 assert(rows >= cols);
93 rows, cols, depth, 1, context->l1_bytes_to_use(),
101 (static_cast<std::uint64_t>(cols) << 32);
105 "(rows = %d, depth = %d, cols = %d, l2_rows = %d, l2_depth = %d,
[all...] |
| /external/gemmlowp/public/ |
| map.h | 43 MatrixMap(Scalar* data, int rows, int cols)
46 cols_(cols),
47 stride_(kOrder == MapOrder::ColMajor ? rows : cols) {}
48 MatrixMap(Scalar* data, int rows, int cols, int stride)
49 : data_(data), rows_(rows), cols_(cols), stride_(stride) {}
57 int cols() const { return cols_; } function in class:gemmlowp::MatrixMap
|
| /external/kernel-headers/original/uapi/linux/ |
| virtio_console.h | 48 __u16 cols; member in struct:virtio_console_config
|
| /external/libhevc/decoder/x86/ |
| ihevcd_fmt_conv_ssse3_intr.c | 63 WORD32 num_rows, num_cols, src_strd, dst_strd, cols, rows; local
66 cols = 0;
128 cols = num_cols >> 4;
143 for(j = 0; j < cols; j++)
219 for(j = 0; j < cols; j++)
250 pu1_u_dst += (cols << 4);
251 pu1_v_dst += (cols << 4);
252 pu1_u_src += 2 * (cols << 4);
253 pu1_v_src += 2 * (cols << 4);
|
| /external/syslinux/com32/lib/sys/ |
| ansicon_write.c | 83 ti.cols = 80;
89 firmware->o_ops->get_mode(&ti.cols, &ti.rows);
98 fp->o.cols = ti.cols;
172 uint8_t rows, cols, attribute; local
174 cols = ti.cols - 1;
178 firmware->o_ops->scroll_up(cols, rows, attribute);
|
| /external/syslinux/core/ |
| font.c | 156 uint8_t rows, cols; local
173 cols = oreg.eax.b[1];
175 VidCols = --cols; /* Store count-1 (same as rows) */
|
| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| lrn_ops.cc | 94 const int64 cols = in_grads_shape.dim_size(2); variable
99 in_image_shape.dim_size(2) == cols &&
103 out_image_shape.dim_size(2) == cols &&
|
| /external/tensorflow/tensorflow/core/kernels/ |
| deep_conv2d.h | 46 virtual void GetFilterTransformMatrix(const int64 rows, const int64 cols,
49 virtual void GetInputTransformMatrix(const int64 rows, const int64 cols,
52 virtual void GetOutputTransformMatrix(const int64 rows, const int64 cols,
56 Shape(int64 r, int64 c) : rows(r), cols(c) {}
58 int64 cols; member in struct:tensorflow::DeepConv2DTransform::Shape
|
| softmax_op_gpu.cu.cc | 74 int rows, int cols) {
81 context, output, input, 2, rows, cols, 1, 1, constants.kOne, op);
97 const int cols = logits_in.dimension(1); variable
117 reinterpret_cast<const T*>(logits_in_.flat<T>().data()), rows, cols);
120 const int numBlocks = Eigen::divup(rows * cols, numThreads);
131 reinterpret_cast<const T*>(max_logits.flat<T>().data()), cols));
135 cols);
141 const_cast<T*>(softmax_out->flat<T>().data()), rows, cols, log_);
|
| /packages/apps/MusicFX/src/com/android/musicfx/ |
| ControlPanelPicker.java | 53 String [] cols = new String [] { "_id", "title", "package", "name" }; local
54 MatrixCursor c = new MatrixCursor(cols);
|
