| /external/tensorflow/tensorflow/core/kernels/ |
| eigen_activations_test.cc | 32 const ptrdiff_t cols = 48; local
34 Tensor<float, 4> input(depth, rows, cols, batch);
37 Tensor<float, 4> result(depth, rows, cols, batch);
41 for (int c = 0; c < cols; ++c) {
56 const ptrdiff_t cols = 48; local
58 Tensor<float, 4> input(depth, rows, cols, batch);
61 Tensor<float, 4> result(depth, rows, cols, batch);
65 for (int c = 0; c < cols; ++c) {
80 const ptrdiff_t cols = 48; local
82 Tensor<float, 4> input(depth, rows, cols, batch)
[all...] |
| 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
|
| /external/eigen/doc/examples/ |
| tut_matrix_resize_fixed_size.cpp | 11 << m.rows() << "x" << m.cols() << std::endl;
|
| tut_matrix_resize.cpp | 11 << m.rows() << "x" << m.cols() << std::endl;
17 << v.rows() << "x" << v.cols() << std::endl;
|
| /art/tools/ahat/src/main/com/android/ahat/ |
| SizeTable.java | 45 List<Column> cols = new ArrayList<Column>(); local
46 cols.add(left);
47 cols.add(new Column("Java Size", Column.Align.RIGHT));
48 cols.add(new Column("?", Column.Align.RIGHT, showDiff));
49 cols.add(new Column("Registered Native Size", Column.Align.RIGHT));
50 cols.add(new Column("?", Column.Align.RIGHT, showDiff));
51 cols.add(new Column("Total Size", Column.Align.RIGHT));
52 cols.add(new Column("?", Column.Align.RIGHT, showDiff));
53 cols.addAll(Arrays.asList(columns));
54 doc.table(cols.toArray(new Column[cols.size()]))
[all...] |
| /external/eigen/test/ |
| array_replicate.cpp | 24 Index cols = m.cols(); local
26 MatrixType m1 = MatrixType::Random(rows, cols),
27 m2 = MatrixType::Random(rows, cols);
37 x1.resize(rows*f1,cols*f2);
40 x1.block(i*rows,j*cols,rows,cols) = m1;
43 x2.resize(2*rows,3*cols);
48 x2.resize(rows,3*cols);
52 vx1.resize(3*rows,cols);
[all...] |
| upperbidiagonalization.cpp | 16 const typename MatrixType::Index cols = m.cols(); local
21 MatrixType a = MatrixType::Random(rows,cols);
23 RealMatrixType b(rows, cols);
25 b.block(0,0,cols,cols) = ubd.bidiagonal();
|
| mapstaticmethods.cpp | 73 Index rows = m.rows(), cols = m.cols(); local
77 PlainObjectType::Map(ptr, rows, cols).setZero();
78 PlainObjectType::MapAligned(ptr, rows, cols).setZero();
79 PlainObjectType::Map(const_ptr, rows, cols).sum();
80 PlainObjectType::MapAligned(const_ptr, rows, cols).sum();
82 PlainObjectType::Map(ptr, rows, cols, InnerStride<>(i)).setZero();
83 PlainObjectType::MapAligned(ptr, rows, cols, InnerStride<>(i)).setZero();
84 PlainObjectType::Map(const_ptr, rows, cols, InnerStride<>(i)).sum();
85 PlainObjectType::MapAligned(const_ptr, rows, cols, InnerStride<>(i)).sum()
[all...] |
| special_numbers.cpp | 16 int cols = internal::random<int>(1,300); local
22 MatType m1 = MatType::Random(rows,cols),
23 mnan = MatType::Random(rows,cols),
24 minf = MatType::Random(rows,cols),
25 mboth = MatType::Random(rows,cols);
30 mnan(internal::random<int>(0,rows-1), internal::random<int>(0,cols-1)) = nan;
31 minf(internal::random<int>(0,rows-1), internal::random<int>(0,cols-1)) = inf;
|
| array_for_matrix.cpp | 20 Index cols = m.cols(); local
22 MatrixType m1 = MatrixType::Random(rows, cols),
23 m2 = MatrixType::Random(rows, cols),
24 m3(rows, cols);
27 RowVectorType rv1 = RowVectorType::Random(cols);
34 VERIFY_IS_APPROX((m1.array() + s1).matrix(), MatrixType::Constant(rows,cols,s1) + m1);
35 VERIFY_IS_APPROX(((m1*Scalar(2)).array() - s2).matrix(), (m1+m1) - MatrixType::Constant(rows,cols,s2) );
61 VERIFY_IS_APPROX(m1.block(0,0,0,cols).colwise().sum(), RowVectorType::Zero(cols));
91 Index cols = m.cols(); local
179 Index cols = m.cols(); local
221 Index rows = t.rows(), cols = t.cols(); local
[all...] |
| 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...] |
| miscmatrices.cpp | 21 Index cols = m.cols(); local
23 Index r = internal::random<Index>(0, rows-1), r2 = internal::random<Index>(0, rows-1), c = internal::random<Index>(0, cols-1);
24 VERIFY_IS_APPROX(MatrixType::Ones(rows,cols)(r,c), static_cast<Scalar>(1));
25 MatrixType m1 = MatrixType::Ones(rows,cols);
|
| product.h | 34 Index cols = m.cols(); local
38 MatrixType m1 = MatrixType::Random(rows, cols),
39 m2 = MatrixType::Random(rows, cols),
40 m3(rows, cols);
46 square2 = ColSquareMatrixType::Random(cols, cols),
47 res2 = ColSquareMatrixType::Random(cols, cols);
49 ColVectorType vc2 = ColVectorType::Random(cols), vcres(cols)
[all...] |
| corners.cpp | 20 Index cols = m.cols(); local
23 Index c = internal::random<Index>(1,cols);
25 MatrixType matrix = MatrixType::Random(rows,cols);
26 const MatrixType const_matrix = MatrixType::Random(rows,cols);
29 COMPARE_CORNER(topRightCorner(r,c), block(0,cols-c,r,c));
31 COMPARE_CORNER(bottomRightCorner(r,c), block(rows-r,cols-c,r,c));
35 Index sc = internal::random<Index>(1,cols) - 1;
36 Index nc = internal::random<Index>(1,cols-sc);
38 COMPARE_CORNER(topRows(r), block(0,0,r,cols));
53 cols = MatrixType::ColsAtCompileTime, enumerator in enum:__anon19835
[all...] |
| /external/eigen/Eigen/src/QR/ |
| CompleteOrthogonalDecomposition.h | 93 CompleteOrthogonalDecomposition(Index rows, Index cols)
94 : m_cpqr(rows, cols), m_zCoeffs((std::min)(rows, cols)), m_temp(cols) {}
105 * matrix.cols());
114 : m_cpqr(matrix.rows(), matrix.cols()),
115 m_zCoeffs((std::min)(matrix.rows(), matrix.cols())),
116 m_temp(matrix.cols())
130 m_zCoeffs((std::min)(matrix.rows(), matrix.cols())),
131 m_temp(matrix.cols())
282 inline Index cols() const { return m_cpqr.cols(); } function in class:Eigen::CompleteOrthogonalDecomposition
418 const Index cols = m_cpqr.cols(); local
471 const Index cols = this->cols(); local
515 const Index cols = this->cols(); local
[all...] |
| ColPivHouseholderQR.h | 100 ColPivHouseholderQR(Index rows, Index cols)
101 : m_qr(rows, cols),
102 m_hCoeffs((std::min)(rows,cols)),
103 m_colsPermutation(PermIndexType(cols)),
104 m_colsTranspositions(cols),
105 m_temp(cols),
106 m_colNormsUpdated(cols),
107 m_colNormsDirect(cols),
117 * ColPivHouseholderQR<MatrixType> qr(matrix.rows(), matrix.cols());
125 : m_qr(matrix.rows(), matrix.cols()),
328 inline Index cols() const { return m_qr.cols(); } function in class:Eigen::ColPivHouseholderQR
490 Index cols = m_qr.cols(); local
[all...] |
| HouseholderQR.h | 78 HouseholderQR(Index rows, Index cols)
79 : m_qr(rows, cols),
80 m_hCoeffs((std::min)(rows,cols)),
81 m_temp(cols),
90 * HouseholderQR<MatrixType> qr(matrix.rows(), matrix.cols());
98 : m_qr(matrix.rows(), matrix.cols()),
99 m_hCoeffs((std::min)(matrix.rows(),matrix.cols())),
100 m_temp(matrix.cols()),
117 m_hCoeffs((std::min)(matrix.rows(),matrix.cols())),
118 m_temp(matrix.cols()),
206 inline Index cols() const { return m_qr.cols(); } function in class:Eigen::HouseholderQR
261 Index cols = mat.cols(); local
303 Index cols = mat.cols(); local
384 Index cols = m_qr.cols(); local
[all...] |
| /external/valgrind/drd/tests/ |
| matinv.c | 36 int cols; member in struct:gj_threadinfo
56 static elem_t* new_matrix(const int rows, const int cols)
59 assert(cols > 0);
60 return malloc(rows * cols * sizeof(elem_t));
70 static void init_matrix(elem_t* const a, const int rows, const int cols)
77 a[i * cols + j] = 1.0 / (1 + abs(i-j));
84 const elem_t* const a, const int rows, const int cols)
90 for (j = 0; j < cols; j++)
92 printf("%g ", a[i * cols + j]);
175 const int cols = p->cols local
[all...] |
| omp_matinv.c | 44 static elem_t* new_matrix(const int rows, const int cols)
47 assert(cols > 0);
48 return malloc(rows * cols * sizeof(elem_t));
58 static void init_matrix(elem_t* const a, const int rows, const int cols)
65 a[i * cols + j] = 1.0 / (1 + abs(i-j));
72 const elem_t* const a, const int rows, const int cols)
78 for (j = 0; j < cols; j++)
80 printf("%g ", a[i * cols + j]);
158 static void gj(elem_t* const a, const int rows, const int cols)
169 if (a[k * cols + i] > a[j * cols + i]
[all...] |
| /external/eigen/bench/ |
| sparse_product.cpp | 53 // mkl_scscmm(&n, lhs.rows(), rhs.cols(), lhs.cols(), &alpha, matdescra,
56 // // mkl_somatcopy('C', 'T', lhs.rows(), lhs.cols(), 1,
101 int cols = SIZE; local
104 EigenSparseMatrix sm1(rows,cols), sm2(rows,cols), sm3(rows,cols), sm4(rows,cols);
111 fillMatrix2(nnzPerCol, rows, cols, sm1);
112 fillMatrix2(nnzPerCol, rows, cols, sm2)
[all...] |
| /external/gemmlowp/meta/generators/ |
| gemv_1xMxK_neon.py | 83 def GenerateMulCols(emitter, result_type, lhs_add, rhs_add, aligned, cols,
104 if cols > 4:
111 zip_Nx8_neon.BuildName(cols - 4, leftovers, aligned),
115 mul_1x8_Mx8_neon.BuildName(result_type, lhs_add, rhs_add, cols),
117 elif cols > 0:
119 zip_Nx8_neon.BuildName(cols, leftovers, aligned),
123 mul_Nx8_Mx8_neon.BuildName(result_type, lhs_add, rhs_add, 1, cols),
127 def GenerateQuantized8BitMul(emitter, aligned, cols, leftovers):
129 GenerateMulCols(emitter, 'int32', False, True, aligned, cols, leftovers)
131 qnt_Nx8_neon.BuildName(1, cols, aligned)
[all...] |
| /external/libvpx/libvpx/vp8/common/ |
| debugmodes.c | 14 void vp8_print_modes_and_motion_vectors(MODE_INFO *mi, int rows, int cols,
26 for (mb_col = 0; mb_col < cols; ++mb_col) {
42 for (mb_col = 0; mb_col < cols; ++mb_col) {
59 for (mb_col = 0; mb_col < cols; ++mb_col) {
80 for (b_col = 0; b_col < 4 * cols; ++b_col) {
81 mb_index = (b_row >> 2) * (cols + 1) + (b_col >> 2);
100 for (mb_col = 0; mb_col < cols; ++mb_col) {
122 for (b_col = 0; b_col < 4 * cols; ++b_col) {
123 mb_index = (b_row >> 2) * (cols + 1) + (b_col >> 2);
|
| /external/eigen/Eigen/src/Core/ |
| Random.h | 33 * The parameters \a rows and \a cols are the number of rows and of columns of
39 * it is redundant to pass \a rows and \a cols as arguments, so Random() should be used
56 DenseBase<Derived>::Random(Index rows, Index cols)
58 return NullaryExpr(rows, cols, internal::scalar_random_op<Scalar>());
133 return *this = Random(rows(), cols());
165 * \param cols the new number of columns
174 PlainObjectBase<Derived>::setRandom(Index rows, Index cols)
176 resize(rows, cols);
|
| /external/eigen/Eigen/src/misc/ |
| Kernel.h | 27 // is the number of cols of the original matrix
46 m_cols(m_rank==dec.cols() ? 1 : dec.cols() - m_rank)
49 inline Index rows() const { return m_dec.cols(); }
50 inline Index cols() const { return m_cols; } function in struct:Eigen::internal::kernel_retval_base
74 using Base::cols; \
|
| /external/ltp/testcases/open_posix_testsuite/functional/threads/pi_test/ |
| do-plot | 12 if ! cols=$(grep "#[ ]*COLUMNS" $FILE)
18 cols=$(echo $cols | sed 's/#//')
19 columns=$(echo $cols | awk '{print $2;}')
23 column[$count]=$(echo $cols | awk -vcount=$count '{print $(2 + count);}')
|
