| /external/eigen/Eigen/src/Geometry/ |
| D | Transform.h | 24 Dim = Transform::Dim, enumerator
42 int Dim,
58 int Dim,
211 Dim = _Dim, ///< space dimension in which the transformation holds
213 Rows = int(Mode)==(AffineCompact) ? Dim : HDim
224 typedef Matrix<Scalar,Dim,Dim,Options> LinearMatrixType;
226 …typedef Block<MatrixType,Dim,Dim,int(Mode)==(AffineCompact) && (int(Options)&RowMajor)==0> LinearP…
228 …typedef const Block<ConstMatrixType,Dim,Dim,int(Mode)==(AffineCompact) && (int(Options)&RowMajor)=…
232 Block<MatrixType,Dim,HDim> >::type AffinePart;
236 const Block<const MatrixType,Dim,HDim> >::type ConstAffinePart;
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| D | RotationBase.h | 32 enum { Dim = _Dim }; enumerator
37 typedef Matrix<Scalar,Dim,Dim> RotationMatrixType;
38 typedef Matrix<Scalar,Dim,1> VectorType;
56 …EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Isometry> operator*(const Translation<Scalar,Dim>& t…
57 { return Transform<Scalar,Dim,Isometry>(*this) * t; }
80 …EIGEN_DEVICE_FUNC friend inline Transform<Scalar,Dim,Affine> operator*(const DiagonalMatrix<Scalar…
82 Transform<Scalar,Dim,Affine> res(r);
89 …EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode> operator*(const Transform<Scalar,Dim,Mode,Opti…
103 enum { Dim = RotationDerived::Dim };
104 typedef Matrix<typename RotationDerived::Scalar,Dim,Dim> ReturnType;
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| D | Translation.h | 35 enum { Dim = _Dim }; enumerator
39 typedef Matrix<Scalar,Dim,1> VectorType;
41 typedef Matrix<Scalar,Dim,Dim> LinearMatrixType;
43 typedef Transform<Scalar,Dim,Affine> AffineTransformType;
45 typedef Transform<Scalar,Dim,Isometry> IsometryTransformType;
58 eigen_assert(Dim==2); in Translation()
65 eigen_assert(Dim==3); in Translation()
106 EIGEN_DEVICE_FUNC inline IsometryTransformType operator*(const RotationBase<Derived,Dim>& r) const
118 res.matrix().row(Dim).setZero();
119 res(Dim,Dim) = Scalar(1);
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| D | Scaling.h | 37 template <typename Scalar, int Dim, int Mode>
44 typedef Transform <Scalar, Dim, NewMode> type;
74 template<int Dim>
75 inline Transform<Scalar,Dim,Affine> operator* (const Translation<Scalar,Dim>& t) const;
78 template<int Dim, int Mode, int Options>
80 internal::uniformscaling_times_affine_returntype<Scalar,Dim,Mode>::type
81 operator* (const Transform<Scalar, Dim, Mode, Options>& t) const
83 typename internal::uniformscaling_times_affine_returntype<Scalar,Dim,Mode>::type res = t;
94 template<typename Derived,int Dim>
95 inline Matrix<Scalar,Dim,Dim> operator*(const RotationBase<Derived,Dim>& r) const
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| D | Homogeneous.h | 98 template<typename Scalar, int Dim, int Mode, int Options> friend
99 EIGEN_DEVICE_FUNC inline const Product<Transform<Scalar,Dim,Mode,Options>, Homogeneous >
100 operator* (const Transform<Scalar,Dim,Mode,Options>& lhs, const Homogeneous& rhs)
103 return Product<Transform<Scalar,Dim,Mode,Options>, Homogeneous>(lhs,rhs);
224 template<typename Scalar, int Dim, int Mode,int Options>
225 struct take_matrix_for_product<Transform<Scalar, Dim, Mode, Options> >
227 typedef Transform<Scalar, Dim, Mode, Options> TransformType;
232 template<typename Scalar, int Dim, int Options>
233 struct take_matrix_for_product<Transform<Scalar, Dim, Projective, Options> >
235 typedef Transform<Scalar, Dim, Projective, Options> TransformType;
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| /external/eigen/unsupported/test/ |
| D | BVH.cpp | 17 …e<typename Scalar, int Dim> AlignedBox<Scalar, Dim> bounding_box(const Matrix<Scalar, Dim, 1> &v) … in bounding_box() argument
22 template<int Dim>
25 EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(double, Dim)
27 typedef Matrix<double, Dim, 1> VectorType;
35 template<int Dim> AlignedBox<double, Dim> bounding_box(const Ball<Dim> &b) in bounding_box()
36 { return AlignedBox<double, Dim>(b.center.array() - b.radius, b.center.array() + b.radius); } in bounding_box()
40 template<int Dim>
44 typedef Matrix<double, Dim, 1> VectorType;
45 typedef Ball<Dim> BallType;
46 typedef AlignedBox<double, Dim> BoxType;
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| /external/llvm/lib/Target/AMDGPU/ |
| D | SIMachineFunctionInfo.h | 361 int getDebuggerWorkGroupIDStackObjectIndex(unsigned Dim) const { in getDebuggerWorkGroupIDStackObjectIndex() argument
362 assert(Dim < 3); in getDebuggerWorkGroupIDStackObjectIndex()
363 return DebuggerWorkGroupIDStackObjectIndices[Dim]; in getDebuggerWorkGroupIDStackObjectIndex()
367 void setDebuggerWorkGroupIDStackObjectIndex(unsigned Dim, int ObjectIdx) { in setDebuggerWorkGroupIDStackObjectIndex() argument
368 assert(Dim < 3); in setDebuggerWorkGroupIDStackObjectIndex()
369 DebuggerWorkGroupIDStackObjectIndices[Dim] = ObjectIdx; in setDebuggerWorkGroupIDStackObjectIndex()
373 int getDebuggerWorkItemIDStackObjectIndex(unsigned Dim) const { in getDebuggerWorkItemIDStackObjectIndex() argument
374 assert(Dim < 3); in getDebuggerWorkItemIDStackObjectIndex()
375 return DebuggerWorkItemIDStackObjectIndices[Dim]; in getDebuggerWorkItemIDStackObjectIndex()
379 void setDebuggerWorkItemIDStackObjectIndex(unsigned Dim, int ObjectIdx) { in setDebuggerWorkItemIDStackObjectIndex() argument
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| /external/tensorflow/tensorflow/core/ops/ |
| D | image_ops.cc | 36 TF_RETURN_IF_ERROR(c->WithValue(c->Dim(size, 0), 2, &unused)); in SetOutputToSizedImage()
65 return SetOutputToSizedImage(c, c->Dim(input, 0), 1 /* size_input_idx */, in ResizeShapeFn()
66 c->Dim(input, 3)); in ResizeShapeFn()
137 TF_RETURN_IF_ERROR(c->WithValue(c->Dim(input, -1), 3, &last_dim)); in ColorspaceShapeFn()
160 TF_RETURN_IF_ERROR(c->Merge(c->Dim(boxes, 0), c->Dim(scores, 0), &unused)); in NMSShapeFn()
162 TF_RETURN_IF_ERROR(c->WithValue(c->Dim(boxes, 1), 4, &unused)); in NMSShapeFn()
185 TF_RETURN_IF_ERROR(c->Merge(c->Dim(boxes, 0), c->Dim(scores, 0), &unused)); in SoftNMSShapeFn()
187 TF_RETURN_IF_ERROR(c->WithValue(c->Dim(boxes, 1), 4, &unused)); in SoftNMSShapeFn()
212 TF_RETURN_IF_ERROR(c->Merge(c->Dim(boxes, 0), c->Dim(scores, 0), &unused)); in CombinedNMSShapeFn()
214 TF_RETURN_IF_ERROR(c->Merge(c->Dim(boxes, 1), c->Dim(scores, 1), &unused)); in CombinedNMSShapeFn()
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| D | linalg_ops.cc | 35 TF_RETURN_IF_ERROR(c->Merge(c->Dim(s, -2), c->Dim(s, -1), &d)); in MakeBatchSquareMatrix()
59 DimensionHandle num_bands = c->Dim(lhs, -2); in BandedTriangularSolveShapeFn()
60 DimensionHandle m = c->Dim(lhs, -1); in BandedTriangularSolveShapeFn()
82 TF_RETURN_IF_ERROR(c->Merge(m, c->Dim(rhs, -2), &m)); in BandedTriangularSolveShapeFn()
87 c->Concatenate(output_batch_shape, c->Matrix(m, c->Dim(rhs, -1)), &out)); in BandedTriangularSolveShapeFn()
116 TF_RETURN_IF_ERROR(c->Merge(c->Dim(lhs, -2), c->Dim(rhs, -2), &m)); in MatrixSolveShapeFn()
117 DimensionHandle n = c->Dim(lhs, -1); in MatrixSolveShapeFn()
125 TF_RETURN_IF_ERROR(c->Concatenate(out, c->Vector(c->Dim(rhs, -1)), &out)); in MatrixSolveShapeFn()
148 TF_RETURN_IF_ERROR(c->Merge(c->Dim(lhs, -1), c->Dim(rhs, -2), &m)); in MatrixTriangularSolveShapeFn()
153 c->Concatenate(output_batch_shape, c->Matrix(m, c->Dim(rhs, -1)), &out)); in MatrixTriangularSolveShapeFn()
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| D | ctc_ops.cc | 50 TF_RETURN_IF_ERROR(c->Merge(c->Dim(labels_indices, 0), in __anon00853f120102()
51 c->Dim(labels_values, 0), &unused)); in __anon00853f120102()
57 c->Merge(c->Dim(inputs, 1), c->Dim(sequence_length, 0), &batch_size)); in __anon00853f120102()
87 TF_RETURN_IF_ERROR(c->Merge(c->Dim(labels_indices, 0), in __anon00853f120202()
88 c->Dim(labels_values, 0), &unused)); in __anon00853f120202()
94 c->Merge(c->Dim(inputs, 1), c->Dim(sequence_length, 0), &batch_size)); in __anon00853f120202()
122 c->Merge(c->Dim(inputs, 1), c->Dim(sequence_length, 0), &batch_size)); in __anon00853f120302()
153 c->Merge(c->Dim(inputs, 1), c->Dim(sequence_length, 0), &batch_size)); in __anon00853f120402()
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| D | boosted_trees_ops.cc | 330 TF_RETURN_IF_ERROR(c->Merge(c->Dim(node_ids_shape, 0), in __anon0a5055ea0902()
331 c->Dim(gradients_shape, 0), &unused_dim)); in __anon0a5055ea0902()
337 TF_RETURN_IF_ERROR(c->Merge(c->Dim(node_ids_shape, 0), in __anon0a5055ea0902()
338 c->Dim(bucketized_feature_shape, 0), in __anon0a5055ea0902()
368 shape_inference::DimensionHandle batch_size = c->Dim(c->input(0), 0); in __anon0a5055ea0a02()
376 TF_RETURN_IF_ERROR(c->Merge(c->Dim(gradients_shape, 0), in __anon0a5055ea0a02()
377 c->Dim(node_ids_shape, 0), &batch_size)); in __anon0a5055ea0a02()
378 TF_RETURN_IF_ERROR(c->Merge(c->Dim(hessians_shape, 0), in __anon0a5055ea0a02()
379 c->Dim(node_ids_shape, 0), &batch_size)); in __anon0a5055ea0a02()
380 TF_RETURN_IF_ERROR(c->Merge(c->Dim(feature_shape, 0), in __anon0a5055ea0a02()
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| D | random_index_shuffle_ops.cc | 45 if (seed_rank == 1 && c->Value(c->Dim(seed_shape, 0)) != 3) { in StatelessRandomPermuteShape()
47 c->Value(c->Dim(seed_shape, 0)), "]."); in StatelessRandomPermuteShape()
49 if (seed_rank == 2 && c->Value(c->Dim(seed_shape, 1)) != 3) { in StatelessRandomPermuteShape()
51 c->Value(c->Dim(seed_shape, 0)), ", ", in StatelessRandomPermuteShape()
52 c->Value(c->Dim(seed_shape, 1)), "]."); in StatelessRandomPermuteShape()
74 const int64_t num_indices = index_rank ? c->Value(c->Dim(index_shape, 0)) : 1; in StatelessRandomPermuteShape()
76 seed_rank == 2 ? c->Value(c->Dim(seed_shape, 0)) : 1; in StatelessRandomPermuteShape()
78 max_index_rank ? c->Value(c->Dim(max_index_shape, 0)) : 1; in StatelessRandomPermuteShape()
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| D | sparse_csr_matrix_ops.cc | 54 TF_RETURN_IF_ERROR(c->Merge(c->Dim(matrix_shape, -2), in ValidateSquareMatrixShape()
55 c->Dim(matrix_shape, -1), matrix_dimension)); in ValidateSquareMatrixShape()
68 auto rank = c->Value(c->Dim(c->input(0), 1)); in __anon6adce4610102()
132 auto indices_col = c->Dim(indices, 1); in __anon6adce4610302()
138 ShapeHandle fake_values_vec = c->Vector(c->Dim(indices, 0)); in __anon6adce4610302()
190 auto row_ptrs_dh = c->Dim(csr_sparse_matrix, -2); in __anon6adce4610502()
213 out = c->Vector(c->Dim(sparse_matrix, 0)); in __anon6adce4610602()
269 auto output_rows = c->Dim(a_shape, transpose_a ? -1 : -2); in __anon6adce4610702()
270 auto output_cols = c->Dim(b_shape, transpose_b ? -2 : -1); in __anon6adce4610702()
286 TF_RETURN_IF_ERROR(c->Merge(c->Dim(a_shape, transpose_a ? -2 : -1), in __anon6adce4610702()
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| D | rnn_ops.cc | 42 DimensionHandle batch_size = c->Dim(x, 0); in __anona90d3fa60102()
43 DimensionHandle cell_size = c->Dim(h_prev, 1); in __anona90d3fa60102()
73 DimensionHandle batch_size = c->Dim(x, 0); in __anona90d3fa60202()
74 DimensionHandle cell_size = c->Dim(h_prev, 1); in __anona90d3fa60202()
75 DimensionHandle twice_cell_size = c->Dim(w_ru, 1); in __anona90d3fa60202()
110 DimensionHandle batch_size = c->Dim(x, 0); in __anona90d3fa60302()
111 DimensionHandle cell_size = c->Dim(cs_prev, 1); in __anona90d3fa60302()
148 DimensionHandle batch_size = c->Dim(x, 0); in __anona90d3fa60402()
149 DimensionHandle cell_size = c->Dim(cs_prev, 1); in __anona90d3fa60402()
188 DimensionHandle timelen = c->Dim(x, 0); in __anona90d3fa60502()
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| D | sparse_ops.cc | 59 c->set_output(0, c->Vector(c->Dim(a_indices, 0))); in __anonc55240e60202()
60 c->set_output(1, c->Vector(c->Dim(b_indices, 0))); in __anonc55240e60202()
81 0, c->Matrix(InferenceContext::kUnknownDim, c->Dim(a_shape, 0))); in __anonc55240e60302()
113 DimensionHandle output_right = c->Dim(b, adjoint_b ? 0 : 1); in __anonc55240e60402()
114 DimensionHandle output_left = c->Dim(a_shape, adjoint_a ? 1 : 0); in __anonc55240e60402()
115 DimensionHandle inner_left = c->Dim(a_shape, adjoint_a ? 0 : 1); in __anonc55240e60402()
116 DimensionHandle inner_right = c->Dim(b, adjoint_b ? 1 : 0); in __anonc55240e60402()
166 TF_RETURN_IF_ERROR(c->WithValue(c->Dim(c->input(0), -1), 3, &unused)); in __anonc55240e60702()
186 c->WithValue(c->Dim(serialized_sparse, 1), 3, &unused)); in __anonc55240e60802()
240 TF_RETURN_IF_ERROR(c->Merge(c->Dim(ind, 0), c->Dim(val, 0), &num_dim)); in __anonc55240e60a02()
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| D | array_ops.cc | 76 TF_RETURN_IF_ERROR(c->Add(c->Dim(input, i), pad0 + pad1, &dims[i])); in PadKnown()
87 TF_RETURN_IF_ERROR(c->WithValue(c->Dim(paddings, 1), 2, &unused)); in PadShapeFn()
91 DimensionHandle n_dim = c->Dim(paddings, 0); in PadShapeFn()
176 dims[i] = c->Dim(input, in_idx); in TransposeShapeFn()
208 DimensionHandle dim = c->Dim(out, i); in SetOutputShapeForReshape()
226 DimensionHandle dim = c->Dim(in, i); in SetOutputShapeForReshape()
265 DimensionHandle unknown_in_dim = c->Dim(in, in_unknown_idx); in SetOutputShapeForReshape()
272 DimensionHandle unknown_in_dim = c->Dim(in, in_unknown_idx); in SetOutputShapeForReshape()
311 if (!c->WithValue(c->Dim(c->input(i), 0), 1, &unused).ok()) { in __anon091a71b70202()
352 while (index < axis) dims.push_back(c->Dim(cur, index++)); in __anon091a71b70302()
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| D | uniform_quant_ops.cc | 46 DimensionHandle scales_size = context->Dim(scales, 0); in ScalesZeroPointsShapeValid()
47 DimensionHandle zero_points_size = context->Dim(zero_points, 0); in ScalesZeroPointsShapeValid()
70 DimensionHandle inner_lhs = context->Dim(lhs, 1); in DotHybridShape()
71 DimensionHandle inner_rhs = context->Dim(rhs, 0); in DotHybridShape()
75 DimensionHandle output_rows = context->Dim(lhs, 0); in DotHybridShape()
76 DimensionHandle output_cols = context->Dim(rhs, 1); in DotHybridShape()
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| /external/tensorflow/tensorflow/core/framework/ |
| D | common_shape_fns.cc | 120 DimensionHandle output_rows = transpose_a ? c->Dim(a, 1) : c->Dim(a, 0); in MatMulShape()
121 DimensionHandle output_cols = transpose_b ? c->Dim(b, 0) : c->Dim(b, 1); in MatMulShape()
124 DimensionHandle inner_a = transpose_a ? c->Dim(a, 0) : c->Dim(a, 1); in MatMulShape()
125 DimensionHandle inner_b = transpose_b ? c->Dim(b, 1) : c->Dim(b, 0); in MatMulShape()
236 ? c->Dim(input_shape, axis) in EinsumShape()
292 output_dims.push_back(c->Dim(output_bcast_shape, k)); in EinsumShape()
320 DimensionHandle output_rows = c->Dim(a_shape, adj_x ? -1 : -2); in BatchMatMulV2Shape()
321 DimensionHandle output_cols = c->Dim(b_shape, adj_y ? -2 : -1); in BatchMatMulV2Shape()
325 TF_RETURN_IF_ERROR(c->Merge(c->Dim(a_shape, adj_x ? -2 : -1), in BatchMatMulV2Shape()
326 c->Dim(b_shape, adj_y ? -1 : -2), &inner_merged)); in BatchMatMulV2Shape()
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| D | shape_inference_test.cc | 291 EXPECT_EQ("?", c.DebugString(c.Dim(in0, 0))); in TEST_F()
292 EXPECT_EQ("?", c.DebugString(c.Dim(in0, -1))); in TEST_F()
293 EXPECT_EQ("?", c.DebugString(c.Dim(in0, 1000))); in TEST_F()
299 auto d = c.Dim(in1, 0); in TEST_F()
301 EXPECT_TRUE(SameHandle(d, c.Dim(in1, -3))); in TEST_F()
304 d = c.Dim(in1, 1); in TEST_F()
307 EXPECT_TRUE(SameHandle(d, c.Dim(in1, -2))); in TEST_F()
309 d = c.Dim(in1, 2); in TEST_F()
311 EXPECT_TRUE(SameHandle(d, c.Dim(in1, -1))); in TEST_F()
330 EXPECT_FALSE(SameHandle(c.Dim(c.input(1), 1), c.NumElements(c.input(1)))); in TEST_F()
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| /external/angle/third_party/vulkan-deps/spirv-tools/src/source/val/ |
| D | validate_image.cpp | 83 spv::Dim dim = spv::Dim::Max;
113 info->dim = static_cast<spv::Dim>(inst->word(3)); in GetImageTypeInfo()
206 case spv::Dim::Dim1D: in GetPlaneCoordSize()
207 case spv::Dim::Buffer: in GetPlaneCoordSize()
210 case spv::Dim::Dim2D: in GetPlaneCoordSize()
211 case spv::Dim::Rect: in GetPlaneCoordSize()
212 case spv::Dim::SubpassData: in GetPlaneCoordSize()
213 case spv::Dim::TileImageDataEXT: in GetPlaneCoordSize()
216 case spv::Dim::Dim3D: in GetPlaneCoordSize()
217 case spv::Dim::Cube: in GetPlaneCoordSize()
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| /external/swiftshader/third_party/SPIRV-Tools/source/val/ |
| D | validate_image.cpp | 84 spv::Dim dim = spv::Dim::Max;
114 info->dim = static_cast<spv::Dim>(inst->word(3)); in GetImageTypeInfo()
207 case spv::Dim::Dim1D: in GetPlaneCoordSize()
208 case spv::Dim::Buffer: in GetPlaneCoordSize()
211 case spv::Dim::Dim2D: in GetPlaneCoordSize()
212 case spv::Dim::Rect: in GetPlaneCoordSize()
213 case spv::Dim::SubpassData: in GetPlaneCoordSize()
216 case spv::Dim::Dim3D: in GetPlaneCoordSize()
217 case spv::Dim::Cube: in GetPlaneCoordSize()
221 case spv::Dim::Max: in GetPlaneCoordSize()
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| /external/eigen/bench/ |
| D | geometry.cpp | 43 enum {Dim = T::Dim}; enumerator
57 template<typename Scalar, int Dim, typename Data>
58 EIGEN_DONT_INLINE void transform(const Transform<Scalar,Dim,Projective>& t, Data& data) in transform() argument
60 data = (t * data.colwise().homogeneous()).template block<Dim,Data::ColsAtCompileTime>(0,0); in transform()
63 template<typename T> struct get_dim { enum { Dim = T::Dim }; }; enumerator
65 struct get_dim<Matrix<S,R,C,O,MR,MC> > { enum { Dim = R }; }; enumerator
72 Matrix<typename Transformation::Scalar,get_dim<Transformation>::Dim,N> data; in run()
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| /external/mesa3d/src/amd/addrlib/src/core/ |
| D | coord.h | 37 enum Dim enum
51 Coordinate(enum Dim dim, INT_32 n);
53 VOID set(enum Dim dim, INT_32 n);
55 enum Dim getdim();
67 enum Dim dim;
85 UINT_32 Filter(INT_8 f, Coordinate& co, UINT_32 start = 0, enum Dim axis = NUM_DIMS);
112 UINT_32 Filter(INT_8 f, Coordinate& co, UINT_32 start = 0, enum Dim axis = NUM_DIMS);
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| /external/eigen/unsupported/Eigen/src/BVH/ |
| D | KdBVH.h | 18 template<typename Scalar, int Dim>
21 EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(Scalar, Dim)
22 typedef Matrix<Scalar, Dim, 1> VectorType;
71 enum { Dim = _Dim };
75 typedef AlignedBox<Scalar, Dim> Volume;
171 typedef internal::vector_int_pair<Scalar, Dim> VIPair;
173 typedef Matrix<Scalar, Dim, 1> VectorType;
196 build(objCenters, from, mid, objBoxes, (dim + 1) % Dim);
206 build(objCenters, from, mid, objBoxes, (dim + 1) % Dim);
208 build(objCenters, mid, to, objBoxes, (dim + 1) % Dim);
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| /external/tensorflow/tensorflow/lite/kernels/shim/ |
| D | shape_test.cc | 89 TEST(Shape, Dim) { in TEST() argument
90 EXPECT_EQ(-1, Shape().Dim(2)); in TEST()
91 EXPECT_EQ(3, Shape({2, 3}).Dim(1)); in TEST()
92 EXPECT_EQ(3, Shape({-1, 3}).Dim(1)); in TEST()
93 EXPECT_EQ(-1, Shape({-1, 3}).Dim(0)); in TEST()
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