/external/bison/src/ |
H A D | output.c | 213 | Prepare the muscles related to the rules: rhs, prhs, r1, r2, | 222 item_number *rhs = xnmalloc (nritems, sizeof *rhs); local 236 for (rhsp = rules[r].rhs; *rhsp >= 0; ++rhsp) 237 rhs[i++] = *rhsp; 243 rhs[i++] = -1; 253 muscle_insert_item_number_table ("rhs", rhs, ritem[0], 1, nritems); 264 free (rhs);
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/external/clang/lib/StaticAnalyzer/Checkers/ |
H A D | MallocOverflowSecurityChecker.cpp | 91 const Expr *rhs = binop->getRHS(); local 92 if (rhs->isEvaluatable(Context)) { 94 maxVal = rhs->EvaluateKnownConstInt(Context); 102 e = rhs; 183 const Expr *rhs = AssignEx->getRHS(); local 184 if (rhs->isEvaluatable(Context)) 190 const Expr *rhse = rhs->IgnoreParenImpCasts(); 228 const Expr * rhs = E->getRHS(); local 231 if (!isIntZeroExpr(lhs) && !isIntZeroExpr(rhs)) { 233 CheckExpr(rhs); [all...] |
/external/clang/test/Analysis/ |
H A D | ptr-arith.c | 171 void use_symbols(int *lhs, int *rhs) { argument 172 clang_analyzer_eval(lhs < rhs); // expected-warning{{UNKNOWN}} 173 if (lhs < rhs) 175 clang_analyzer_eval(lhs < rhs); // expected-warning{{FALSE}} 177 clang_analyzer_eval(lhs - rhs); // expected-warning{{UNKNOWN}} 178 if ((lhs - rhs) != 5) 180 clang_analyzer_eval((lhs - rhs) == 5); // expected-warning{{TRUE}} 183 void equal_implies_zero(int *lhs, int *rhs) { argument 184 clang_analyzer_eval(lhs == rhs); // expected-warning{{UNKNOWN}} 185 if (lhs == rhs) { 195 zero_implies_equal(int *lhs, int *rhs) argument 207 comparisons_imply_size(int *lhs, int *rhs) argument 229 size_implies_comparison(int *lhs, int *rhs) argument 255 zero_implies_reversed_equal(int *lhs, int *rhs) argument 271 canonical_equal(int *lhs, int *rhs) argument [all...] |
H A D | taint-generic.c | 216 void constraintManagerShouldTreatAsOpaque(int rhs) { argument 221 if (i < rhs) 223 if (i < rhs)
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/external/clang/test/SemaTemplate/ |
H A D | ms-lookup-template-base-classes.cpp | 187 bool operator=(const Container<S>& rhs) { argument 188 return base_fun(rhs); // expected-warning {{use of identifier 'base_fun' found via unqualified lookup into dependent bases of class templates is a Microsoft extension}}
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/external/drm_hwcomposer/ |
H A D | drmdisplaycomposition.h | 60 DrmCompositionPlane(DrmCompositionPlane &&rhs) = default; member in class:android::DrmCompositionPlane
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H A D | drmhwcomposer.h | 49 DrmHwcBuffer(DrmHwcBuffer &&rhs) : bo_(rhs.bo_), importer_(rhs.importer_) { argument 50 rhs.importer_ = NULL; 57 DrmHwcBuffer &operator=(DrmHwcBuffer &&rhs) { argument 59 importer_ = rhs.importer_; 60 rhs.importer_ = NULL; 61 bo_ = rhs.bo_; 88 DrmHwcNativeHandle(DrmHwcNativeHandle &&rhs) { argument 89 gralloc_ = rhs 97 operator =(DrmHwcNativeHandle &&rhs) argument [all...] |
H A D | separate_rects.h | 49 Rect(const Rect<T> &rhs) { argument 51 bounds[i] = rhs.bounds[i]; 55 Rect<TFloat> &operator=(const Rect<T> &rhs) { argument 57 bounds[i] = rhs.bounds[i]; 61 bool operator==(const Rect &rhs) const { 63 if (bounds[i] != rhs.bounds[i]) 116 bool operator==(const IdSet<TId> &rhs) const { 117 return bitset == rhs.bitset; 120 bool operator<(const IdSet<TId> &rhs) const { 121 return bitset < rhs [all...] |
/external/eigen/Eigen/src/Core/ |
H A D | Product.h | 93 EIGEN_DEVICE_FUNC Product(const Lhs& lhs, const Rhs& rhs) : m_lhs(lhs), m_rhs(rhs) argument 95 eigen_assert(lhs.cols() == rhs.rows() 104 EIGEN_DEVICE_FUNC const RhsNestedCleaned& rhs() const { return m_rhs; } function in class:Eigen::Product
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H A D | SolveTriangular.h | 57 static void run(const Lhs& lhs, Rhs& rhs) argument 63 bool useRhsDirectly = Rhs::InnerStrideAtCompileTime==1 || rhs.innerStride()==1; 65 ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhs,rhs.size(), 66 (useRhsDirectly ? rhs.data() : 0)); 69 MappedRhs(actualRhs,rhs.size()) = rhs; 76 rhs = MappedRhs(actualRhs, rhs.size()); 80 // the rhs is a matrix 88 static void run(const Lhs& lhs, Rhs& rhs) argument 121 run(const Lhs& lhs, Rhs& rhs) argument 141 run(const Lhs& lhs, Rhs& rhs) argument 147 run(const Lhs& lhs, Rhs& rhs) argument 209 triangular_solve_retval(const TriangularType& tri, const Rhs& rhs) argument [all...] |
/external/eigen/Eigen/src/Core/products/ |
H A D | TriangularMatrixVector.h | 48 const RhsMap rhs(_rhs,cols,InnerStride<>(rhsIncr)); 49 typename conj_expr_if<ConjRhs,RhsMap>::type cjRhs(rhs); 77 RhsMapper(&rhs.coeffRef(pi), rhsIncr), 86 RhsMapper(&rhs.coeffRef(size), rhsIncr), 119 const RhsMap rhs(_rhs,cols); 120 typename conj_expr_if<ConjRhs,RhsMap>::type cjRhs(rhs); 148 RhsMapper(&rhs.coeffRef(s), rhsIncr), 157 RhsMapper(&rhs.coeffRef(0), rhsIncr), 176 template<typename Dest> static void run(Dest& dst, const Lhs &lhs, const Rhs &rhs, const typename Dest::Scalar& alpha) argument 178 eigen_assert(dst.rows()==lhs.rows() && dst.cols()==rhs 187 run(Dest& dst, const Lhs &lhs, const Rhs &rhs, const typename Dest::Scalar& alpha) argument 207 run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha) argument 283 run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha) argument [all...] |
/external/eigen/Eigen/src/Eigenvalues/ |
H A D | GeneralizedEigenSolver.h | 343 Matrix<Scalar, 2, 1> rhs = (alpha*mT.template block<2,Dynamic>(j-1,st,2,sz) - beta*mS.template block<2,Dynamic>(j-1,st,2,sz)) .lazyProduct( v.segment(st,sz) ); local 345 v.template segment<2>(j-1) = lhs.partialPivLu().solve(rhs); 394 Matrix<ComplexScalar, 2, 1> rhs = (alpha*mT.template block<2,Dynamic>(j-1,st,2,sz) - beta*mS.template block<2,Dynamic>(j-1,st,2,sz)) .lazyProduct( cv.segment(st,sz) ); local 396 cv.template segment<2>(j-1) = lhs.partialPivLu().solve(rhs);
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/external/eigen/Eigen/src/IterativeLinearSolvers/ |
H A D | BiCGSTAB.h | 20 * \param rhs The right hand side vector b 29 bool bicgstab(const MatrixType& mat, const Rhs& rhs, Dest& x, argument 42 VectorType r = rhs - mat * x; 46 RealScalar rhs_sqnorm = rhs.squaredNorm(); 76 r = rhs - mat * x;
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H A D | ConjugateGradient.h | 19 * \param rhs The right hand side vector b 28 void conjugate_gradient(const MatrixType& mat, const Rhs& rhs, Dest& x, argument 43 VectorType residual = rhs - mat * x; //initial residual 45 RealScalar rhsNorm2 = rhs.squaredNorm();
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H A D | LeastSquareConjugateGradient.h | 19 * \param rhs The right hand side vector b 28 void least_square_conjugate_gradient(const MatrixType& mat, const Rhs& rhs, Dest& x, argument 43 VectorType residual = rhs - mat * x; 46 RealScalar rhsNorm2 = (mat.adjoint()*rhs).squaredNorm();
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/external/eigen/Eigen/src/QR/ |
H A D | HouseholderQR.h | 217 void _solve_impl(const RhsType &rhs, DstType &dst) const; 350 void HouseholderQR<_MatrixType>::_solve_impl(const RhsType &rhs, DstType &dst) const argument 353 eigen_assert(rhs.rows() == rows()); 355 typename RhsType::PlainObject c(rhs);
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/external/eigen/Eigen/src/SVD/ |
H A D | SVDBase.h | 216 void _solve_impl(const RhsType &rhs, DstType &dst) const; 259 void SVDBase<Derived>::_solve_impl(const RhsType &rhs, DstType &dst) const argument 261 eigen_assert(rhs.rows() == rows()); 268 tmp.noalias() = m_matrixU.leftCols(l_rank).adjoint() * rhs;
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/external/eigen/Eigen/src/SparseCore/ |
H A D | SparseDenseProduct.h | 34 static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha) argument 44 for(Index c=0; c<rhs.cols(); ++c) 53 processRow(lhsEval,rhs,res,alpha,i,c); 59 processRow(lhsEval,rhs,res,alpha,i,c); 64 static void processRow(const LhsEval& lhsEval, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha, Index i, Index col) argument 68 tmp += it.value() * rhs.coeff(it.index(),col); 92 static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const AlphaType& alpha) argument 95 for(Index c=0; c<rhs.cols(); ++c) 99 // typename Res::Scalar rhs_j = alpha * rhs.coeff(j,c); 100 typename ScalarBinaryOpTraits<AlphaType, typename Rhs::Scalar>::ReturnType rhs_j(alpha * rhs 115 run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha) argument 134 run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha) argument 147 sparse_time_dense_product(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const AlphaType& alpha) argument 163 scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha) argument 185 scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha) argument 247 get(const RhsEval &rhs, Index outer, Dense = Dense()) const argument 252 get(const RhsEval &rhs, Index outer, Sparse = Sparse()) argument 266 sparse_dense_outer_product_evaluator(const Lhs1 &lhs, const ActualRhs &rhs) argument 273 sparse_dense_outer_product_evaluator(const ActualRhs &rhs, const Lhs1 &lhs) argument [all...] |
/external/eigen/test/ |
H A D | qr_colpivoting.cpp | 52 MatrixType rhs = matrix * exact_solution; local 53 MatrixType cod_solution = cod.solve(rhs); 54 VERIFY_IS_APPROX(rhs, matrix * cod_solution); 58 MatrixType svd_solution = svd.solve(rhs); 62 VERIFY_IS_APPROX(cod_solution, pinv * rhs); 84 Matrix<Scalar, Rows, Cols2> rhs = matrix * exact_solution; local 85 Matrix<Scalar, Cols, Cols2> cod_solution = cod.solve(rhs); 86 VERIFY_IS_APPROX(rhs, matrix * cod_solution); 90 Matrix<Scalar, Cols, Cols2> svd_solution = svd.solve(rhs);
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/external/eigen/unsupported/Eigen/CXX11/src/Tensor/ |
H A D | TensorAssign.h | 21 * the rhs expression to the memory locations denoted by the lhs expression. 70 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorAssignOp(LhsXprType& lhs, const RhsXprType& rhs) argument 71 : m_lhs_xpr(lhs), m_rhs_xpr(rhs) {} 115 // The dimensions of the lhs and the rhs tensors should be equal to prevent 125 // null value), attempt to evaluate the rhs expression in place. Returns true iff in place 127 // by the rhs to the lhs.
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H A D | TensorCostModel.h | 98 const TensorOpCost& rhs) const { 99 double bytes_loaded = numext::mini(bytes_loaded_, rhs.bytes_loaded()); 100 double bytes_stored = numext::mini(bytes_stored_, rhs.bytes_stored()); 101 double compute_cycles = numext::mini(compute_cycles_, rhs.compute_cycles()); 107 const TensorOpCost& rhs) const { 108 double bytes_loaded = numext::maxi(bytes_loaded_, rhs.bytes_loaded()); 109 double bytes_stored = numext::maxi(bytes_stored_, rhs.bytes_stored()); 110 double compute_cycles = numext::maxi(compute_cycles_, rhs.compute_cycles()); 115 const TensorOpCost& rhs) { 116 bytes_loaded_ += rhs 114 operator +=( const TensorOpCost& rhs) argument 122 operator *=(double rhs) argument 129 operator +( TensorOpCost lhs, const TensorOpCost& rhs) argument 134 operator *( TensorOpCost lhs, double rhs) argument 139 operator *( double lhs, TensorOpCost rhs) argument [all...] |
H A D | TensorCustomOp.h | 212 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorCustomBinaryOp(const LhsXprType& lhs, const RhsXprType& rhs, const CustomBinaryFunc& func) argument 214 : m_lhs_xpr(lhs), m_rhs_xpr(rhs), m_func(func) {}
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H A D | TensorMeta.h | 125 Tuple& operator= (const Tuple& rhs) { argument 126 if (&rhs == this) return *this; 127 first = rhs.first; 128 second = rhs.second; 133 void swap(Tuple& rhs) { argument 135 swap(first, rhs.first); 136 swap(second, rhs.second);
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H A D | TensorUInt128.h | 78 bool operator == (const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs) argument 80 return (lhs.high == rhs.high) & (lhs.low == rhs.low); 85 bool operator != (const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs) argument 87 return (lhs.high != rhs.high) | (lhs.low != rhs.low); 92 bool operator >= (const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs) argument 94 if (lhs.high != rhs.high) { 95 return lhs.high > rhs.high; 97 return lhs.low >= rhs 102 operator <(const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs) argument 112 operator +(const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs) argument 123 operator -(const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs) argument 135 operator *(const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs) argument 210 operator /(const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs) argument [all...] |
/external/eigen/unsupported/Eigen/src/IterativeSolvers/ |
H A D | GMRES.h | 56 bool gmres(const MatrixType & mat, const Rhs & rhs, Dest & x, const Preconditioner & precond, argument 74 VectorType p0 = rhs - mat*x; 189 p0.noalias() = rhs - mat*x;
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