| /external/eigen/failtest/ |
| map_nonconst_ctor_on_const_ptr_2.cpp | 11 void foo(CV_QUALIFIER float *ptr, DenseIndex rows, DenseIndex cols){
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| map_nonconst_ctor_on_const_ptr_3.cpp | 11 void foo(CV_QUALIFIER float *ptr, DenseIndex rows, DenseIndex cols){
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| map_nonconst_ctor_on_const_ptr_4.cpp | 11 void foo(const float *ptr, DenseIndex rows, DenseIndex cols){
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| map_nonconst_ctor_on_const_ptr_1.cpp | 11 void foo(CV_QUALIFIER float *ptr, DenseIndex size){
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| /external/eigen/unsupported/Eigen/CXX11/src/Tensor/ |
| TensorDimensionList.h | 39 template<DenseIndex n, typename Index, std::size_t Rank> const Index array_get(DimensionList<Index, Rank>&) {
42 template<DenseIndex n, typename Index, std::size_t Rank> const Index array_get(const DimensionList<Index, Rank>&) {
50 EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex) {
56 EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex) {
89 static constexpr bool run(const DenseIndex i, const DenseIndex value) {
95 EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
102 EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value)
[all...] |
| TensorIndexList.h | 40 template <DenseIndex n>
42 static const DenseIndex value = n;
43 EIGEN_DEVICE_FUNC constexpr operator DenseIndex() const { return n; }
44 EIGEN_DEVICE_FUNC void set(DenseIndex val) {
51 template <DenseIndex f, DenseIndex s>
53 static const DenseIndex first = f;
54 static const DenseIndex second = s;
56 constexpr EIGEN_DEVICE_FUNC operator IndexPair<DenseIndex>() const {
57 return IndexPair<DenseIndex>(f, s)
[all...] |
| TensorDimensions.h | 106 template <typename DenseIndex>
107 explicit EIGEN_DEVICE_FUNC Sizes(const array<DenseIndex, Base::count>& /*indices*/) {
111 template <typename... DenseIndex> EIGEN_DEVICE_FUNC Sizes(DenseIndex...) { }
126 template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
127 size_t IndexOfColMajor(const array<DenseIndex, Base::count>& indices) const {
128 return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, false>::run(indices, *static_cast<const Base*>(this));
130 template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
131 size_t IndexOfRowMajor(const array<DenseIndex, Base::count>& indices) const {
132 return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, true>::run(indices, *static_cast<const Base*>(this))
[all...] |
| TensorImagePatch.h | 30 template<DenseIndex Rows, DenseIndex Cols, typename XprType>
43 template<DenseIndex Rows, DenseIndex Cols, typename XprType>
49 template<DenseIndex Rows, DenseIndex Cols, typename XprType>
57 template<DenseIndex Rows, DenseIndex Cols, typename XprType>
68 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorImagePatchOp(const XprType& expr, DenseIndex patch_rows, DenseIndex patch_cols
[all...] |
| TensorVolumePatch.h | 25 template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType>
38 template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType>
44 template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType>
52 template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType
[all...] |
| TensorForwardDeclarations.h | 26 template<typename Scalar_, int NumIndices_, int Options_ = 0, typename IndexType = DenseIndex> class Tensor;
27 template<typename Scalar_, typename Dimensions, int Options_ = 0, typename IndexType = DenseIndex> class TensorFixedSize;
45 template<DenseIndex Rows, DenseIndex Cols, typename XprType> class TensorImagePatchOp;
46 template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType> class TensorVolumePatchOp;
48 template<DenseIndex DimId, typename XprType> class TensorChippingOp;
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| /external/tensorflow/tensorflow/contrib/image/kernels/ |
| image_ops.h | 34 using Eigen::DenseIndex;
53 operator()(const array<DenseIndex, 4>& coords) const {
92 nearest_interpolation(const DenseIndex batch, const float y, const float x,
93 const DenseIndex channel, const T fill_value) const {
94 return read_with_fill_value(batch, DenseIndex(std::round(y)),
95 DenseIndex(std::round(x)), channel, fill_value);
99 bilinear_interpolation(const DenseIndex batch, const float y, const float x,
100 const DenseIndex channel, const T fill_value) const {
108 (x_ceil - x) * read_with_fill_value(batch, DenseIndex(y_floor),
109 DenseIndex(x_floor), channel
[all...] |
| /external/tensorflow/tensorflow/core/kernels/ |
| conv_ops_gpu_2.cu.cc | 30 Eigen::DenseIndex>;
33 Eigen::DenseIndex>;
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| split_lib.h | 30 const Eigen::DSizes<Eigen::DenseIndex, 2>& slice_indices,
31 const Eigen::DSizes<Eigen::DenseIndex, 2>& slice_sizes);
38 const Eigen::DSizes<Eigen::DenseIndex, 3>& slice_indices,
39 const Eigen::DSizes<Eigen::DenseIndex, 3>& slice_sizes);
47 const Eigen::DSizes<Eigen::DenseIndex, 3>& slice_indices,
48 const Eigen::DSizes<Eigen::DenseIndex, 3>& slice_sizes);
57 const Eigen::DSizes<Eigen::DenseIndex, 3>& slice_indices,
58 const Eigen::DSizes<Eigen::DenseIndex, 3>& slice_sizes);
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| eigen_pooling.h | 64 SpatialMaxPooling(const Input& input, DenseIndex patchRows,
65 DenseIndex patchCols, DenseIndex strideRows,
66 DenseIndex strideCols, const PaddingType padding_type,
67 DenseIndex in_strideRows = 1, DenseIndex in_strideCols = 1) {
77 const DenseIndex patchRowsEff =
79 const DenseIndex patchColsEff =
97 static_cast<DenseIndex>(in.dimension(idxRows)) - patchRowsEff + 1,
100 static_cast<DenseIndex>(in.dimension(idxCols)) - patchColsEff + 1
[all...] |
| tile_ops_impl.h | 31 const Eigen::DSizes<Eigen::DenseIndex, NDIM>& indices,
32 const Eigen::DSizes<Eigen::DenseIndex, NDIM>& sizes,
46 const Eigen::DSizes<Eigen::DenseIndex, 0>&,
47 const Eigen::DSizes<Eigen::DenseIndex, 0>&,
62 const Eigen::DSizes<Eigen::DenseIndex, REDUCEDNDIM>& reduce_dim,
63 const Eigen::DSizes<Eigen::DenseIndex, NDIM>& reshape_dim) const {
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| split_lib_cpu.cc | 31 const Eigen::DSizes<Eigen::DenseIndex, 3>& slice_indices,
32 const Eigen::DSizes<Eigen::DenseIndex, 3>& slice_sizes) {
50 const Eigen::DSizes<Eigen::DenseIndex, 3>& slice_indices,
51 const Eigen::DSizes<Eigen::DenseIndex, 3>& slice_sizes) {
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| /external/eigen/unsupported/test/ |
| cxx11_tensor_argmax.cpp | 26 Tensor<Tuple<DenseIndex, float>, 4, DataLayout> index_tuples(2,3,5,7);
29 for (DenseIndex n = 0; n < 2*3*5*7; ++n) {
30 const Tuple<DenseIndex, float>& v = index_tuples.coeff(n);
43 Tensor<Tuple<DenseIndex, float>, 4, DataLayout> index_tuples(2,3,5,7);
47 for (Eigen::DenseIndex n = 0; n < tensor.size(); ++n) {
48 const Tuple<DenseIndex, float>& v = index_tuples(n); //(i, j, k, l);
61 Tensor<Tuple<DenseIndex, float>, 4, DataLayout> index_tuples(2,3,5,7);
64 Tensor<Tuple<DenseIndex, float>, 0, DataLayout> reduced;
65 DimensionList<DenseIndex, 4> dims;
67 dims, internal::ArgMaxTupleReducer<Tuple<DenseIndex, float> >())
[all...] |
| cxx11_tensor_random.cpp | 46 int operator()(Eigen::DenseIndex element_location, Eigen::DenseIndex /*unused*/ = 0) const {
52 Eigen::DenseIndex packet_location, Eigen::DenseIndex /*unused*/ = 0) const {
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| cxx11_tensor_custom_op.cpp | 18 DSizes<DenseIndex, 2> dimensions(const Tensor<float, 2>& input) const {
19 DSizes<DenseIndex, 2> result;
28 array<DenseIndex, 2> strides;
33 Eigen::DSizes<DenseIndex, 2> offsets(1,1);
34 Eigen::DSizes<DenseIndex, 2> extents(output.dimension(0)-1, output.dimension(1)-1);
62 DSizes<DenseIndex, 3> dimensions(const Tensor<float, 3>& input1, const Tensor<float, 3>& input2) const {
63 DSizes<DenseIndex, 3> result;
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| /external/eigen/blas/ |
| level3_impl.h | 16 typedef void (*functype)(DenseIndex, DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, Scalar, internal::level3_blocking<Scalar,Scalar>&, Eigen::internal::GemmParallelInfo<DenseIndex>*);
19 (internal::general_matrix_matrix_product<DenseIndex,Scalar,ColMajor,false,Scalar,ColMajor,false,ColMajor>::run),
21 (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,false,Scalar,ColMajor,false,ColMajor>::run),
23 (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,false,ColMajor>::run)
[all...] |
| /external/eigen/unsupported/Eigen/src/Splines/ |
| Spline.h | 127 derivatives(Scalar u, DenseIndex order) const;
136 derivatives(Scalar u, DenseIndex order = DerivativeOrder) const;
171 basisFunctionDerivatives(Scalar u, DenseIndex order) const;
180 basisFunctionDerivatives(Scalar u, DenseIndex order = DerivativeOrder) const;
185 DenseIndex degree() const;
191 DenseIndex span(Scalar u) const;
196 static DenseIndex Span(typename SplineTraits<Spline>::Scalar u, DenseIndex degree, const typename SplineTraits<Spline>::KnotVectorType& knots);
210 static BasisVectorType BasisFunctions(Scalar u, DenseIndex degree, const KnotVectorType& knots);
218 const Scalar u, const DenseIndex order, const DenseIndex degree, const KnotVectorType& knots)
[all...] |
| SplineFitting.h | 45 void KnotAveraging(const KnotVectorType& parameters, DenseIndex degree, KnotVectorType& knots)
49 for (DenseIndex j=1; j<parameters.size()-degree; ++j)
85 DenseIndex numParameters = parameters.size();
86 DenseIndex numDerivatives = derivativeIndices.size();
94 DenseIndex startIndex;
95 DenseIndex endIndex;
97 DenseIndex numInternalDerivatives = numDerivatives;
120 DenseIndex numAverageKnots = endIndex - startIndex + 3;
125 for (DenseIndex i = startIndex; i <= endIndex; ++i)
133 for (DenseIndex i = 0; i < numAverageKnots - 1; ++i
[all...] |
| /external/eigen/unsupported/Eigen/src/Polynomials/ |
| PolynomialUtils.h | 31 for(DenseIndex i=poly.size()-2; i>=0; --i ){
56 for( DenseIndex i=1; i<poly.size(); ++i ){
85 for( DenseIndex i=0; i<poly.size()-1; ++i ){
104 DenseIndex i=0;
111 for( DenseIndex j=i+1; j<poly.size(); ++j ){
134 for( DenseIndex i=1; i< rv.size(); ++i )
136 for( DenseIndex j=i+1; j>0; --j ){ poly[j] = poly[j-1] - rv[i]*poly[j]; }
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| /external/eigen/test/ |
| resize.cpp | 12 template<DenseIndex rows, DenseIndex cols>
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| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| index_ops_kernel_argmax_float_1d.cc | 34 Eigen::DSizes<Eigen::DenseIndex, 1> in_eig_sizes(input_size);
37 Eigen::DSizes<Eigen::DenseIndex, 0> out_eig_sizes;
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