| /external/libyuv/files/source/ |
| convert_jpeg.cc | 38 int rows) {
42 dest->v_stride, dest->w, rows);
43 dest->y += rows * dest->y_stride;
44 dest->u += ((rows + 1) >> 1) * dest->u_stride;
45 dest->v += ((rows + 1) >> 1) * dest->v_stride;
46 dest->h -= rows;
52 int rows) {
56 dest->v_stride, dest->w, rows);
57 dest->y += rows * dest->y_stride;
58 dest->u += ((rows + 1) >> 1) * dest->u_stride
[all...] |
| /external/libvpx/libvpx/third_party/libyuv/source/ |
| convert_jpeg.cc | 38 int rows) {
46 dest->w, rows);
47 dest->y += rows * dest->y_stride;
48 dest->u += ((rows + 1) >> 1) * dest->u_stride;
49 dest->v += ((rows + 1) >> 1) * dest->v_stride;
50 dest->h -= rows;
56 int rows) {
64 dest->w, rows);
65 dest->y += rows * dest->y_stride;
66 dest->u += ((rows + 1) >> 1) * dest->u_stride
[all...] |
| /external/eigen/test/ |
| spqr_support.cpp | 19 int rows = internal::random<int>(1,maxRows); local
20 int cols = internal::random<int>(1,rows);
21 double density = (std::max)(8./(rows*cols), 0.01);
23 A.resize(rows,cols);
24 dA.resize(rows,cols);
27 return rows;
40 Index m = A.rows();
|
| ctorleak.cpp | 42 Index rows = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE), cols = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE); local
43 Foo::object_limit = internal::random<Index>(0, rows*cols - 2);
49 std::cout << "\nMatrixX m(" << rows << ", " << cols << ");\n";
50 MatrixX m(rows, cols);
59 Foo::object_limit = (rows+1)*(cols+1);
60 MatrixX A(rows, cols);
61 VERIFY_IS_EQUAL(Foo::object_count, rows*cols);
63 VERIFY_IS_EQUAL(Foo::object_count, (rows+1)*cols);
65 VERIFY_IS_EQUAL(Foo::object_count, rows*(cols+1));
|
| dontalign.cpp | 27 Index rows = m.rows(); local
30 MatrixType a = MatrixType::Random(rows,cols);
31 SquareMatrixType square = SquareMatrixType::Random(rows,rows);
32 VectorType v = VectorType::Random(rows);
43 Scalar* array = internal::aligned_new<Scalar>(rows);
44 v = VectorType::MapAligned(array, rows);
45 internal::aligned_delete(array, rows);
|
| bandmatrix.cpp | 18 Index rows = _m.rows(); local
23 MatrixType m(rows,cols,supers,subs);
25 DenseMatrixType dm1(rows,cols);
48 Index d = (std::min)(rows,cols);
50 Index b = std::max<Index>(0,rows-d-subs);
51 if(a>0) dm1.block(0,d+supers,rows,a).setZero();
53 dm1.block(subs+1,0,rows-subs-1-b,rows-subs-1-b).template triangularView<Lower>().setZero();
65 Index rows = internal::random<Index>(1,10) local
[all...] |
| householder.cpp | 21 Index rows = m.rows(); local
34 Matrix<Scalar, EIGEN_SIZE_MAX(MatrixType::RowsAtCompileTime,MatrixType::ColsAtCompileTime), 1> _tmp((std::max)(rows,cols));
41 VectorType v1 = VectorType::Random(rows), v2;
46 if(rows>=2) VERIFY_IS_MUCH_SMALLER_THAN(v1.tail(rows-1).norm(), v1.norm());
47 v1 = VectorType::Random(rows);
52 MatrixType m1(rows, cols),
53 m2(rows, cols);
55 v1 = VectorType::Random(rows);
[all...] |
| sparse_vector.cpp | 12 template<typename Scalar,typename StorageIndex> void sparse_vector(int rows, int cols)
14 double densityMat = (std::max)(8./(rows*cols), 0.01);
15 double densityVec = (std::max)(8./(rows), 0.1);
22 SparseMatrixType m1(rows,rows);
23 SparseVectorType v1(rows), v2(rows), v3(rows);
24 DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
[all...] |
| product_selfadjoint.cpp | 21 Index rows = m.rows(); local
24 MatrixType m1 = MatrixType::Random(rows, cols),
25 m2 = MatrixType::Random(rows, cols),
27 VectorType v1 = VectorType::Random(rows),
28 v2 = VectorType::Random(rows),
29 v3(rows);
30 RowVectorType r1 = RowVectorType::Random(rows),
31 r2 = RowVectorType::Random(rows);
32 RhsMatrixType m4 = RhsMatrixType::Random(rows,10)
[all...] |
| inverse.cpp | 21 Index rows = m.rows(); local
26 MatrixType m1(rows, cols),
27 m2(rows, cols),
28 identity = MatrixType::Identity(rows, rows);
29 createRandomPIMatrixOfRank(rows,rows,rows,m1);
64 VectorType v3 = VectorType::Random(rows);
[all...] |
| 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...] |
| /external/eigen/bench/ |
| sparse_transpose.cpp | 38 int rows = SIZE; local
42 EigenSparseMatrix sm1(rows,cols), sm3(rows,cols);
47 fillMatrix(density, rows, cols, sm1);
52 DenseMatrix m1(rows,cols), m3(rows,cols);
59 std::cout << "Non zeros: " << sm1.nonZeros()/float(sm1.rows()*sm1.cols())*100 << "%\n";
81 GmmDynSparse gmmT3(rows,cols);
82 GmmSparse m1(rows,cols), m3(rows,cols)
[all...] |
| /external/python/cpython3/Modules/_decimal/libmpdec/ |
| transpose.h | 44 void std_trans(mpd_uint_t dest[], mpd_uint_t src[], mpd_size_t rows, mpd_size_t cols);
45 int transpose_pow2(mpd_uint_t *matrix, mpd_size_t rows, mpd_size_t cols);
46 void transpose_3xpow2(mpd_uint_t *matrix, mpd_size_t rows, mpd_size_t cols);
|
| /external/tensorflow/tensorflow/core/kernels/ |
| eigen_activations_test.cc | 31 const ptrdiff_t rows = 32; local
34 Tensor<float, 4> input(depth, rows, cols, batch);
37 Tensor<float, 4> result(depth, rows, cols, batch);
42 for (int r = 0; r < rows; ++r) {
55 const ptrdiff_t rows = 32; local
58 Tensor<float, 4> input(depth, rows, cols, batch);
61 Tensor<float, 4> result(depth, rows, cols, batch);
66 for (int r = 0; r < rows; ++r) {
79 const ptrdiff_t rows = 32; local
82 Tensor<float, 4> input(depth, rows, cols, batch)
[all...] |
| /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;
|
| /external/mesa3d/src/compiler/glsl/tests/ |
| uniform_initializer_utils.h | 37 unsigned columns, unsigned rows,
42 unsigned columns, unsigned rows, unsigned array_size,
|
| /frameworks/ml/nn/runtime/test/specs/V1_0/ |
| embedding_lookup.mod.py | 18 rows = 3 variable
22 actual_values = [x for x in range(rows * columns * features)]
23 for i in range(rows):
30 value = Input("value", "TENSOR_FLOAT32", "{%d, %d, %d}" % (rows, columns, features))
|
| hashtable_lookup_float.mod.py | 19 rows = 3 variable
22 table = [x for x in range(rows * features)]
23 for i in range(rows):
31 value = Input("value", "TENSOR_FLOAT32", "{%d, %d}" % (rows, features))
|
| hashtable_lookup_quant8.mod.py | 19 rows = 3 variable
22 table = [x for x in range(rows * features)]
23 for i in range(rows):
31 value = Input("value", "TENSOR_QUANT8_ASYMM", "{%d, %d}, 0.5f, 0" % (rows, features))
|
| /frameworks/ml/nn/runtime/test/specs/V1_1/ |
| embedding_lookup_relaxed.mod.py | 18 rows = 3 variable
22 actual_values = [x for x in range(rows * columns * features)]
23 for i in range(rows):
30 value = Input("value", "TENSOR_FLOAT32", "{%d, %d, %d}" % (rows, columns, features))
|
| hashtable_lookup_float_relaxed.mod.py | 19 rows = 3 variable
22 table = [x for x in range(rows * features)]
23 for i in range(rows):
31 value = Input("value", "TENSOR_FLOAT32", "{%d, %d}" % (rows, features))
|
| /external/python/cpython2/Lib/plat-mac/lib-scriptpackages/StdSuites/ |
| Table_Suite.py | 42 class rows(aetools.ComponentItem): class in inherits:aetools.ComponentItem
43 """rows - """
46 row = rows
66 rows._superclassnames = []
67 rows._privpropdict = {
69 rows._privelemdict = {
89 'crow' : rows,
|
| /prebuilts/gdb/darwin-x86/lib/python2.7/plat-mac/lib-scriptpackages/StdSuites/ |
| Table_Suite.py | 42 class rows(aetools.ComponentItem): class in inherits:aetools.ComponentItem
43 """rows - """
46 row = rows
66 rows._superclassnames = []
67 rows._privpropdict = {
69 rows._privelemdict = {
89 'crow' : rows,
|
| /prebuilts/python/darwin-x86/2.7.5/lib/python2.7/plat-mac/lib-scriptpackages/StdSuites/ |
| Table_Suite.py | 42 class rows(aetools.ComponentItem): class in inherits:aetools.ComponentItem
43 """rows - """
46 row = rows
66 rows._superclassnames = []
67 rows._privpropdict = {
69 rows._privelemdict = {
89 'crow' : rows,
|
