mirror of
https://gitlab.com/libeigen/eigen.git
synced 2026-04-10 11:34:33 +08:00
Improved support for RowMajor tensors
Misc fixes and API cleanups.
This commit is contained in:
Benoit Steiner
@@ -25,77 +25,118 @@ template<typename Derived>
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class TensorBase<Derived, ReadOnlyAccessors>
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{
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public:
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typedef typename internal::traits<Derived>::Scalar Scalar;
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typedef typename internal::traits<Derived>::Index Index;
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typedef Scalar CoeffReturnType;
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typedef typename internal::packet_traits<Scalar>::type PacketReturnType;
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typedef internal::traits<Derived> DerivedTraits;
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typedef typename DerivedTraits::Scalar Scalar;
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typedef typename DerivedTraits::Index Index;
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typedef typename internal::remove_const<Scalar>::type CoeffReturnType;
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typedef typename internal::packet_traits<CoeffReturnType>::type PacketReturnType;
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static const int NumDimensions = DerivedTraits::NumDimensions;
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// Dimensions
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE Index dimension(std::size_t n) const { return derived().dimensions()[n]; }
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE Index size() const { return internal::array_prod(derived().dimensions()); }
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// Generic nullary operation support.
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template <typename CustomNullaryOp> EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseNullaryOp<CustomNullaryOp, const Derived>
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nullaryExpr(const CustomNullaryOp& func) const {
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return TensorCwiseNullaryOp<CustomNullaryOp, const Derived>(derived(), func);
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}
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// Nullary operators
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// Coefficient-wise nullary operators
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived>
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constant(const Scalar& value) const {
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return TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived>
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(derived(), internal::scalar_constant_op<Scalar>(value));
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return nullaryExpr(internal::scalar_constant_op<Scalar>(value));
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseNullaryOp<internal::UniformRandomGenerator<Scalar>, const Derived>
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random() const {
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return TensorCwiseNullaryOp<internal::UniformRandomGenerator<Scalar>, const Derived>(derived());
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return nullaryExpr(internal::UniformRandomGenerator<Scalar>());
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}
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template <typename RandomGenerator> EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseNullaryOp<RandomGenerator, const Derived>
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random() const {
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return TensorCwiseNullaryOp<RandomGenerator, const Derived>(derived());
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return nullaryExpr(RandomGenerator());
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}
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// Generic unary operation support.
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template <typename CustomUnaryOp> EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<CustomUnaryOp, const Derived>
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unaryExpr(const CustomUnaryOp& func) const {
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return TensorCwiseUnaryOp<CustomUnaryOp, const Derived>(derived(), func);
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}
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// Coefficient-wise unary operators
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const Derived>
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operator-() const { return derived(); }
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operator-() const {
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return unaryExpr(internal::scalar_opposite_op<Scalar>());
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_sqrt_op<Scalar>, const Derived>
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sqrt() const { return derived(); }
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sqrt() const {
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return unaryExpr(internal::scalar_sqrt_op<Scalar>());
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_square_op<Scalar>, const Derived>
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square() const { return derived(); }
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square() const {
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return unaryExpr(internal::scalar_square_op<Scalar>());
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const Derived>
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inverse() const { return derived(); }
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inverse() const {
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return unaryExpr(internal::scalar_inverse_op<Scalar>());
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_exp_op<Scalar>, const Derived>
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exp() const { return derived(); }
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exp() const {
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return unaryExpr(internal::scalar_exp_op<Scalar>());
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_log_op<Scalar>, const Derived>
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log() const { return derived(); }
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log() const {
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return unaryExpr(internal::scalar_log_op<Scalar>());
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_abs_op<Scalar>, const Derived>
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abs() const { return derived(); }
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abs() const {
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return unaryExpr(internal::scalar_abs_op<Scalar>());
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_pow_op<Scalar>, const Derived>
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pow(Scalar exponent) const {
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return TensorCwiseUnaryOp<internal::scalar_pow_op<Scalar>, const Derived>
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(derived(), internal::scalar_pow_op<Scalar>(exponent));
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return unaryExpr(internal::scalar_pow_op<Scalar>(exponent));
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_add_op<Scalar>, const Derived>
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operator+ (Scalar rhs) const {
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return unaryExpr(internal::scalar_add_op<Scalar>(rhs));
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_sub_op<Scalar>, const Derived>
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operator- (Scalar rhs) const {
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EIGEN_STATIC_ASSERT((std::numeric_limits<Scalar>::is_signed || internal::is_same<Scalar, const std::complex<float> >::value), YOU_MADE_A_PROGRAMMING_MISTAKE);
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return unaryExpr(internal::scalar_sub_op<Scalar>(rhs));
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const Derived>
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operator * (Scalar scale) const {
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return TensorCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const Derived>
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(derived(), internal::scalar_multiple_op<Scalar>(scale));
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operator* (Scalar rhs) const {
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return unaryExpr(internal::scalar_multiple_op<Scalar>(rhs));
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_quotient1_op<Scalar>, const Derived>
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operator/ (Scalar rhs) const {
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// EIGEN_STATIC_ASSERT(!std::numeric_limits<Scalar>::is_integer, YOU_MADE_A_PROGRAMMING_MISTAKE);
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return unaryExpr(internal::scalar_quotient1_op<Scalar>(rhs));
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}
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EIGEN_DEVICE_FUNC
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@@ -110,86 +151,106 @@ class TensorBase<Derived, ReadOnlyAccessors>
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return cwiseMin(constant(threshold));
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}
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template <typename CustomUnaryOp> EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<CustomUnaryOp, const Derived>
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unaryExpr(const CustomUnaryOp& func) const {
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return TensorCwiseUnaryOp<CustomUnaryOp, const Derived>(derived(), func);
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}
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template <typename NewType> EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_cast_op<Scalar, NewType>, const Derived>
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cast() const {
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return derived();
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return unaryExpr(internal::scalar_cast_op<Scalar, NewType>());
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}
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// Generic binary operation support.
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template <typename CustomBinaryOp, typename OtherDerived> EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<CustomBinaryOp, const Derived, const OtherDerived>
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binaryExpr(const OtherDerived& other, const CustomBinaryOp& func) const {
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return TensorCwiseBinaryOp<CustomBinaryOp, const Derived, const OtherDerived>(derived(), other, func);
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}
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// Coefficient-wise binary operators.
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template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorCwiseBinaryOp<internal::scalar_sum_op<Scalar>, const Derived, const OtherDerived>
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operator+(const OtherDerived& other) const {
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return TensorCwiseBinaryOp<internal::scalar_sum_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
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return binaryExpr(other.derived(), internal::scalar_sum_op<Scalar>());
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}
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template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorCwiseBinaryOp<internal::scalar_difference_op<Scalar>, const Derived, const OtherDerived>
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operator-(const OtherDerived& other) const {
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return TensorCwiseBinaryOp<internal::scalar_difference_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
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return binaryExpr(other.derived(), internal::scalar_difference_op<Scalar>());
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}
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template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorCwiseBinaryOp<internal::scalar_product_op<Scalar>, const Derived, const OtherDerived>
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operator*(const OtherDerived& other) const {
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return TensorCwiseBinaryOp<internal::scalar_product_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
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return binaryExpr(other.derived(), internal::scalar_product_op<Scalar>());
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}
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template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorCwiseBinaryOp<internal::scalar_quotient_op<Scalar>, const Derived, const OtherDerived>
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operator/(const OtherDerived& other) const {
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return TensorCwiseBinaryOp<internal::scalar_quotient_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
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return binaryExpr(other.derived(), internal::scalar_quotient_op<Scalar>());
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}
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template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorCwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived, const OtherDerived>
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cwiseMax(const OtherDerived& other) const {
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return TensorCwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
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return binaryExpr(other.derived(), internal::scalar_max_op<Scalar>());
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}
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template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorCwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived, const OtherDerived>
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cwiseMin(const OtherDerived& other) const {
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return TensorCwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
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return binaryExpr(other.derived(), internal::scalar_min_op<Scalar>());
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}
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template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorCwiseBinaryOp<internal::scalar_boolean_and_op, const Derived, const OtherDerived>
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operator&&(const OtherDerived& other) const {
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return binaryExpr(other.derived(), internal::scalar_boolean_and_op());
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}
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template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorCwiseBinaryOp<internal::scalar_boolean_or_op, const Derived, const OtherDerived>
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operator||(const OtherDerived& other) const {
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return binaryExpr(other.derived(), internal::scalar_boolean_or_op());
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}
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// Comparisons and tests.
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template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorCwiseBinaryOp<std::less<Scalar>, const Derived, const OtherDerived>
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operator<(const OtherDerived& other) const {
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return TensorCwiseBinaryOp<std::less<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
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return binaryExpr(other.derived(), std::less<Scalar>());
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}
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template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorCwiseBinaryOp<std::less_equal<Scalar>, const Derived, const OtherDerived>
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operator<=(const OtherDerived& other) const {
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return TensorCwiseBinaryOp<std::less_equal<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
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return binaryExpr(other.derived(), std::less_equal<Scalar>());
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}
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template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorCwiseBinaryOp<std::greater<Scalar>, const Derived, const OtherDerived>
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operator>(const OtherDerived& other) const {
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return TensorCwiseBinaryOp<std::greater<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
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return binaryExpr(other.derived(), std::greater<Scalar>());
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}
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template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorCwiseBinaryOp<std::greater_equal<Scalar>, const Derived, const OtherDerived>
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operator>=(const OtherDerived& other) const {
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return TensorCwiseBinaryOp<std::greater_equal<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
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return binaryExpr(other.derived(), std::greater_equal<Scalar>());
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}
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template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorCwiseBinaryOp<std::equal_to<Scalar>, const Derived, const OtherDerived>
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operator==(const OtherDerived& other) const {
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return TensorCwiseBinaryOp<std::equal_to<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
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return binaryExpr(other.derived(), std::equal_to<Scalar>());
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}
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template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorCwiseBinaryOp<std::not_equal_to<Scalar>, const Derived, const OtherDerived>
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operator!=(const OtherDerived& other) const {
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return TensorCwiseBinaryOp<std::not_equal_to<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
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return binaryExpr(other.derived(), std::not_equal_to<Scalar>());
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}
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// Coefficient-wise ternary operators.
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template<typename ThenDerived, typename ElseDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorSelectOp<const Derived, const ThenDerived, const ElseDerived>
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select(const ThenDerived& thenTensor, const ElseDerived& elseTensor) const {
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return TensorSelectOp<const Derived, const ThenDerived, const ElseDerived>(derived(), thenTensor.derived(), elseTensor.derived());
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}
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// Contractions.
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@@ -208,29 +269,72 @@ class TensorBase<Derived, ReadOnlyAccessors>
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return TensorConvolutionOp<const Dimensions, const Derived, const KernelDerived>(derived(), kernel.derived(), dims);
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}
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// Coefficient-wise ternary operators.
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template<typename ThenDerived, typename ElseDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorSelectOp<const Derived, const ThenDerived, const ElseDerived>
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select(const ThenDerived& thenTensor, const ElseDerived& elseTensor) const {
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return TensorSelectOp<const Derived, const ThenDerived, const ElseDerived>(derived(), thenTensor.derived(), elseTensor.derived());
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}
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// Reductions.
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template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorReductionOp<internal::SumReducer<Scalar>, const Dims, const Derived>
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const TensorReductionOp<internal::SumReducer<CoeffReturnType>, const Dims, const Derived>
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sum(const Dims& dims) const {
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return TensorReductionOp<internal::SumReducer<Scalar>, const Dims, const Derived>(derived(), dims, internal::SumReducer<Scalar>());
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return TensorReductionOp<internal::SumReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::SumReducer<CoeffReturnType>());
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}
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const TensorReductionOp<internal::SumReducer<CoeffReturnType>, const array<Index, NumDimensions>, const Derived>
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sum() const {
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array<Index, NumDimensions> in_dims;
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for (int i = 0; i < NumDimensions; ++i) in_dims[i] = i;
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return TensorReductionOp<internal::SumReducer<CoeffReturnType>, const array<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::SumReducer<CoeffReturnType>());
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}
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template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorReductionOp<internal::MaxReducer<Scalar>, const Dims, const Derived>
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const TensorReductionOp<internal::MeanReducer<CoeffReturnType>, const Dims, const Derived>
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mean(const Dims& dims) const {
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return TensorReductionOp<internal::MeanReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::MeanReducer<CoeffReturnType>());
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}
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const TensorReductionOp<internal::MeanReducer<CoeffReturnType>, const array<Index, NumDimensions>, const Derived>
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mean() const {
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array<Index, NumDimensions> in_dims;
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for (int i = 0; i < NumDimensions; ++i) in_dims[i] = i;
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return TensorReductionOp<internal::MeanReducer<CoeffReturnType>, const array<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::MeanReducer<CoeffReturnType>());
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}
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template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorReductionOp<internal::ProdReducer<CoeffReturnType>, const Dims, const Derived>
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prod(const Dims& dims) const {
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return TensorReductionOp<internal::ProdReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::ProdReducer<CoeffReturnType>());
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}
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const TensorReductionOp<internal::ProdReducer<CoeffReturnType>, const array<Index, NumDimensions>, const Derived>
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prod() const {
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array<Index, NumDimensions> in_dims;
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for (int i = 0; i < NumDimensions; ++i) in_dims[i] = i;
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return TensorReductionOp<internal::ProdReducer<CoeffReturnType>, const array<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::ProdReducer<CoeffReturnType>());
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}
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template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const Dims, const Derived>
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maximum(const Dims& dims) const {
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return TensorReductionOp<internal::MaxReducer<Scalar>, const Dims, const Derived>(derived(), dims, internal::MaxReducer<Scalar>());
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return TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::MaxReducer<CoeffReturnType>());
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}
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const TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const array<Index, NumDimensions>, const Derived>
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maximum() const {
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array<Index, NumDimensions> in_dims;
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for (int i = 0; i < NumDimensions; ++i) in_dims[i] = i;
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return TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const array<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::MaxReducer<CoeffReturnType>());
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}
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template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorReductionOp<internal::MinReducer<Scalar>, const Dims, const Derived>
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const TensorReductionOp<internal::MinReducer<CoeffReturnType>, const Dims, const Derived>
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minimum(const Dims& dims) const {
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return TensorReductionOp<internal::MinReducer<Scalar>, const Dims, const Derived>(derived(), dims, internal::MinReducer<Scalar>());
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return TensorReductionOp<internal::MinReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::MinReducer<CoeffReturnType>());
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}
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const TensorReductionOp<internal::MinReducer<CoeffReturnType>, const array<Index, NumDimensions>, const Derived>
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minimum() const {
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array<Index, NumDimensions> in_dims;
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for (int i = 0; i < NumDimensions; ++i) in_dims[i] = i;
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return TensorReductionOp<internal::MinReducer<CoeffReturnType>, const array<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::MinReducer<CoeffReturnType>());
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}
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template <typename Reducer, typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorReductionOp<Reducer, const Dims, const Derived>
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reduce(const Dims& dims, const Reducer& reducer) const {
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@@ -258,17 +362,44 @@ class TensorBase<Derived, ReadOnlyAccessors>
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template <Index Rows, Index Cols> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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||||
const TensorImagePatchOp<Rows, Cols, const Derived>
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extract_image_patches() const {
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return TensorImagePatchOp<Rows, Cols, const Derived>(derived(), Rows, Cols, 1, 1);
|
||||
return TensorImagePatchOp<Rows, Cols, const Derived>(derived(), Rows, Cols, 1, 1, PADDING_SAME);
|
||||
}
|
||||
|
||||
template <Index Rows, Index Cols> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
const TensorImagePatchOp<Rows, Cols, const Derived>
|
||||
extract_image_patches(const PaddingType padding_type) const {
|
||||
return TensorImagePatchOp<Rows, Cols, const Derived>(derived(), Rows, Cols, 1, 1, padding_type);
|
||||
}
|
||||
|
||||
template <Index Rows, Index Cols> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
const TensorImagePatchOp<Rows, Cols, const Derived>
|
||||
extract_image_patches(const Index stride, const PaddingType padding_type) const {
|
||||
return TensorImagePatchOp<Rows, Cols, const Derived>(derived(), Rows, Cols, stride, stride, padding_type);
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
const TensorImagePatchOp<Dynamic, Dynamic, const Derived>
|
||||
extract_image_patches(const Index patch_rows, const Index patch_cols,
|
||||
const Index row_stride = 1, const Index col_stride = 1) const {
|
||||
return TensorImagePatchOp<Dynamic, Dynamic, const Derived>(derived(), patch_rows, patch_cols, row_stride, col_stride);
|
||||
return TensorImagePatchOp<Dynamic, Dynamic, const Derived>(derived(), patch_rows, patch_cols, row_stride, col_stride,
|
||||
PADDING_SAME);
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
const TensorImagePatchOp<Dynamic, Dynamic, const Derived>
|
||||
extract_image_patches(const Index patch_rows, const Index patch_cols,
|
||||
const Index row_stride, const Index col_stride,
|
||||
const PaddingType padding_type) const {
|
||||
return TensorImagePatchOp<Dynamic, Dynamic, const Derived>(derived(), patch_rows, patch_cols, row_stride, col_stride,
|
||||
padding_type);
|
||||
}
|
||||
|
||||
// Morphing operators.
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
const TensorLayoutSwapOp<const Derived>
|
||||
swap_layout() const {
|
||||
return TensorLayoutSwapOp<const Derived>(derived());
|
||||
}
|
||||
template <typename NewDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
const TensorReshapingOp<const NewDimensions, const Derived>
|
||||
reshape(const NewDimensions& newDimensions) const {
|
||||
@@ -279,10 +410,20 @@ class TensorBase<Derived, ReadOnlyAccessors>
|
||||
slice(const StartIndices& startIndices, const Sizes& sizes) const {
|
||||
return TensorSlicingOp<const StartIndices, const Sizes, const Derived>(derived(), startIndices, sizes);
|
||||
}
|
||||
template <std::size_t DimId> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
template <Index DimId> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
const TensorChippingOp<DimId, const Derived>
|
||||
chip(const Index offset) const {
|
||||
return TensorChippingOp<DimId, const Derived>(derived(), offset);
|
||||
return TensorChippingOp<DimId, const Derived>(derived(), offset, DimId);
|
||||
}
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
const TensorChippingOp<Dynamic, const Derived>
|
||||
chip(const Index offset, const Index dim) const {
|
||||
return TensorChippingOp<Dynamic, const Derived>(derived(), offset, dim);
|
||||
}
|
||||
template <typename ReverseDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
const TensorReverseOp<const ReverseDimensions, const Derived>
|
||||
reverse(const ReverseDimensions& rev) const {
|
||||
return TensorReverseOp<const ReverseDimensions, const Derived>(derived(), rev);
|
||||
}
|
||||
template <typename PaddingDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
const TensorPaddingOp<const PaddingDimensions, const Derived>
|
||||
@@ -308,21 +449,24 @@ class TensorBase<Derived, ReadOnlyAccessors>
|
||||
|
||||
protected:
|
||||
template <typename Scalar, std::size_t NumIndices, int Options> friend class Tensor;
|
||||
template <typename Scalar, int Options> friend class TensorVarDim;
|
||||
template <typename OtherDerived, int AccessLevel> friend class TensorBase;
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE const Derived& derived() const { return *static_cast<const Derived*>(this); }
|
||||
};
|
||||
|
||||
|
||||
template<typename Derived>
|
||||
class TensorBase<Derived, WriteAccessors> : public TensorBase<Derived, ReadOnlyAccessors> {
|
||||
public:
|
||||
typedef typename internal::traits<Derived>::Scalar Scalar;
|
||||
typedef typename internal::traits<Derived>::Index Index;
|
||||
typedef internal::traits<Derived> DerivedTraits;
|
||||
typedef typename DerivedTraits::Scalar Scalar;
|
||||
typedef typename DerivedTraits::Index Index;
|
||||
typedef Scalar CoeffReturnType;
|
||||
typedef typename internal::packet_traits<Scalar>::type PacketReturnType;
|
||||
static const int NumDimensions = DerivedTraits::NumDimensions;
|
||||
|
||||
template <typename Scalar, std::size_t NumIndices, int Options> friend class Tensor;
|
||||
template <typename Scalar, int Options> friend class TensorVarDim;
|
||||
template <typename OtherDerived, int AccessLevel> friend class TensorBase;
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
@@ -337,24 +481,43 @@ class TensorBase<Derived, WriteAccessors> : public TensorBase<Derived, ReadOnlyA
|
||||
EIGEN_STRONG_INLINE Derived& setRandom() {
|
||||
return derived() = this->random();
|
||||
}
|
||||
template <typename RandomGenerator> EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Derived& setRandom() {
|
||||
return derived() = this->template random<RandomGenerator>();
|
||||
}
|
||||
|
||||
#ifdef EIGEN_HAS_VARIADIC_TEMPLATES
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Derived& setValues(
|
||||
const typename internal::Initializer<Derived, NumDimensions>::InitList& vals) {
|
||||
TensorEvaluator<Derived, DefaultDevice> eval(derived(), DefaultDevice());
|
||||
internal::initialize_tensor<Derived, NumDimensions>(eval, vals);
|
||||
return derived();
|
||||
}
|
||||
#endif // EIGEN_HAS_VARIADIC_TEMPLATES
|
||||
|
||||
template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
Derived& operator+=(const OtherDerived& other) {
|
||||
return derived() = TensorCwiseBinaryOp<internal::scalar_sum_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
|
||||
return derived() = derived() + other.derived();
|
||||
}
|
||||
template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
Derived& operator-=(const OtherDerived& other) {
|
||||
return derived() = TensorCwiseBinaryOp<internal::scalar_difference_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
|
||||
return derived() = derived() - other.derived();
|
||||
}
|
||||
template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
Derived& operator*=(const OtherDerived& other) {
|
||||
return derived() = TensorCwiseBinaryOp<internal::scalar_product_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
|
||||
return derived() = derived() * other.derived();
|
||||
}
|
||||
template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
Derived& operator/=(const OtherDerived& other) {
|
||||
return derived() = TensorCwiseBinaryOp<internal::scalar_quotient_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
|
||||
return derived() = derived() / other.derived();
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
TensorLayoutSwapOp<Derived>
|
||||
swap_layout() const {
|
||||
return TensorLayoutSwapOp<Derived>(derived());
|
||||
}
|
||||
template <typename NewDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
TensorReshapingOp<const NewDimensions, Derived>
|
||||
reshape(const NewDimensions& newDimensions) const {
|
||||
@@ -365,16 +528,26 @@ class TensorBase<Derived, WriteAccessors> : public TensorBase<Derived, ReadOnlyA
|
||||
slice(const StartIndices& startIndices, const Sizes& sizes) const {
|
||||
return TensorSlicingOp<const StartIndices, const Sizes, Derived>(derived(), startIndices, sizes);
|
||||
}
|
||||
template <std::size_t DimId> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
template <DenseIndex DimId> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
TensorChippingOp<DimId, Derived>
|
||||
chip(const Index offset) const {
|
||||
return TensorChippingOp<DimId, Derived>(derived(), offset);
|
||||
return TensorChippingOp<DimId, Derived>(derived(), offset, DimId);
|
||||
}
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
TensorChippingOp<Dynamic, Derived>
|
||||
chip(const Index offset, const Index dim) const {
|
||||
return TensorChippingOp<Dynamic, Derived>(derived(), offset, dim);
|
||||
}
|
||||
template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
TensorShufflingOp<const Shuffle, Derived>
|
||||
shuffle(const Shuffle& shuffle) const {
|
||||
return TensorShufflingOp<const Shuffle, Derived>(derived(), shuffle);
|
||||
}
|
||||
template <typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
TensorStridingOp<const Strides, Derived>
|
||||
stride(const Strides& strides) const {
|
||||
return TensorStridingOp<const Strides, Derived>(derived(), strides);
|
||||
}
|
||||
|
||||
// Select the device on which to evaluate the expression.
|
||||
template <typename DeviceType>
|
||||
|
||||
Reference in New Issue
Block a user