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693 |
jeremybenn |
/* { dg-do compile } */
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template < typename > class basic_stringstream;
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struct basic_string {
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basic_string();
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};
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struct ios_base {
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virtual ~ios_base();
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};
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class ostream:ios_base {};
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class istream:virtual ios_base {};
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template < typename > struct basic_iostream:public istream, ostream {
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~basic_iostream () {}
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};
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extern template class basic_iostream < char >;
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template < typename > struct basic_stringstream:public basic_iostream < char > {
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basic_string _M_stringbuf;
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~basic_stringstream () {}
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};
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extern template class basic_stringstream < char >;
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template < typename > struct AnyMatrixBase;
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template < typename, int _Rows, int _Cols, int = _Rows, int = _Cols > class Matrix;
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template < typename > class CwiseNullaryOp;
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template < typename Derived > struct MatrixBase:public AnyMatrixBase < Derived > {
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typedef CwiseNullaryOp < Derived > ConstantReturnType;
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ConstantReturnType Constant ();
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template < typename > Derived cast ();
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static CwiseNullaryOp < Derived > Random (int);
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};
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template < typename Derived > struct AnyMatrixBase {
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Derived derived () {}
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Derived & derived () const {}
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};
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template < typename, int > struct ei_matrix_storage {};
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template < typename _Scalar, int, int, int _MaxRows, int _MaxCols > struct Matrix:MatrixBase < Matrix < _Scalar, _MaxRows, _MaxCols > > {
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typedef MatrixBase < Matrix > Base;
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ei_matrix_storage < int, _MaxCols > m_storage;
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Matrix operator= (const Matrix other) {
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_resize_to_match (other);
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lazyAssign (other.derived ());
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}
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template < typename OtherDerived > Matrix lazyAssign (MatrixBase < OtherDerived > other) {
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_resize_to_match (other);
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return Base (other.derived ());
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}
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Matrix ();
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template < typename OtherDerived > Matrix (const MatrixBase < OtherDerived > &other) {
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*this = other;
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}
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template < typename OtherDerived > void _resize_to_match (const MatrixBase < OtherDerived > &) {
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throw 1;
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}
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};
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template < typename MatrixType > class CwiseNullaryOp:
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public MatrixBase < CwiseNullaryOp < MatrixType > > {};
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int f()
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{
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bool align_cols;
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if (align_cols) {
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basic_stringstream sstr;
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f();
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}
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}
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template < typename > struct AutoDiffScalar;
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template < typename Functor > struct AutoDiffJacobian:Functor {
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AutoDiffJacobian (Functor);
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typedef typename Functor::InputType InputType;
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typedef typename Functor::ValueType ValueType;
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typedef Matrix < int, Functor::InputsAtCompileTime, 1 > DerivativeType;
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typedef AutoDiffScalar < DerivativeType > ActiveScalar;
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typedef Matrix < ActiveScalar, Functor::InputsAtCompileTime, 1 > ActiveInput;
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void operator () (InputType x, ValueType *) {
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ActiveInput ax = x.template cast < ActiveScalar > ();
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}
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};
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template < int NX, int NY > struct TestFunc1 {
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enum {
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InputsAtCompileTime = NX
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};
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typedef Matrix < float, NX, 1 > InputType;
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typedef Matrix < float, NY, 1 > ValueType;
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typedef Matrix < float, NY, NX > JacobianType;
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int inputs ();
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};
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template < typename Func > void forward_jacobian (Func f) {
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typename Func::InputType x = Func::InputType::Random (f.inputs ());
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typename Func::ValueType y;
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typename Func::JacobianType jref = jref.Constant ();
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AutoDiffJacobian < Func > autoj (f);
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autoj (x, &y);
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}
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void test_autodiff_scalar ()
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{
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forward_jacobian (TestFunc1 < 2, 2 > ());
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forward_jacobian (TestFunc1 < 3, 2 > ());
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}
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