| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com> |
| // |
| // This Source Code Form is subject to the terms of the Mozilla |
| // Public License v. 2.0. If a copy of the MPL was not distributed |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. |
| |
| #ifndef EIGEN_CXX11_TENSOR_TENSOR_BASE_H |
| #define EIGEN_CXX11_TENSOR_TENSOR_BASE_H |
| |
| // clang-format off |
| |
| namespace Eigen { |
| |
| /** \class TensorBase |
| * \ingroup CXX11_Tensor_Module |
| * |
| * \brief The tensor base class. |
| * |
| * This class is the common parent of the Tensor and TensorMap class, thus |
| * making it possible to use either class interchangeably in expressions. |
| */ |
| #ifndef EIGEN_PARSED_BY_DOXYGEN |
| // FIXME Doxygen does not like the inheritance with different template parameters |
| // Since there is no doxygen documentation inside, we disable it for now |
| template<typename Derived> |
| class TensorBase<Derived, ReadOnlyAccessors> |
| { |
| public: |
| typedef internal::traits<Derived> DerivedTraits; |
| typedef typename DerivedTraits::Scalar Scalar; |
| typedef typename DerivedTraits::Index Index; |
| typedef typename internal::remove_const<Scalar>::type CoeffReturnType; |
| static const int NumDimensions = DerivedTraits::NumDimensions; |
| |
| // Generic nullary operation support. |
| template <typename CustomNullaryOp> EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseNullaryOp<CustomNullaryOp, const Derived> |
| nullaryExpr(const CustomNullaryOp& func) const { |
| return TensorCwiseNullaryOp<CustomNullaryOp, const Derived>(derived(), func); |
| } |
| |
| // Coefficient-wise nullary operators |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> |
| constant(const Scalar& value) const { |
| return nullaryExpr(internal::scalar_constant_op<Scalar>(value)); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseNullaryOp<internal::UniformRandomGenerator<Scalar>, const Derived> |
| random() const { |
| return nullaryExpr(internal::UniformRandomGenerator<Scalar>()); |
| } |
| template <typename RandomGenerator> EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseNullaryOp<RandomGenerator, const Derived> |
| random(const RandomGenerator& gen = RandomGenerator()) const { |
| return nullaryExpr(gen); |
| } |
| |
| // Tensor generation |
| template <typename Generator> EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorGeneratorOp<Generator, const Derived> |
| generate(const Generator& generator) const { |
| return TensorGeneratorOp<Generator, const Derived>(derived(), generator); |
| } |
| |
| // Generic unary operation support. |
| template <typename CustomUnaryOp> EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<CustomUnaryOp, const Derived> |
| unaryExpr(const CustomUnaryOp& func) const { |
| return TensorCwiseUnaryOp<CustomUnaryOp, const Derived>(derived(), func); |
| } |
| |
| // Coefficient-wise unary operators |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const Derived> |
| operator-() const { |
| return unaryExpr(internal::scalar_opposite_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_sqrt_op<Scalar>, const Derived> |
| sqrt() const { |
| return unaryExpr(internal::scalar_sqrt_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_sign_op<Scalar>, const Derived> |
| sign() const { |
| return unaryExpr(internal::scalar_sign_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_rsqrt_op<Scalar>, const Derived> |
| rsqrt() const { |
| return unaryExpr(internal::scalar_rsqrt_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_square_op<Scalar>, const Derived> |
| square() const { |
| return unaryExpr(internal::scalar_square_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_cube_op<Scalar>, const Derived> |
| cube() const { |
| return unaryExpr(internal::scalar_cube_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const Derived> |
| inverse() const { |
| return unaryExpr(internal::scalar_inverse_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_tanh_op<Scalar>, const Derived> |
| tanh() const { |
| return unaryExpr(internal::scalar_tanh_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_lgamma_op<Scalar>, const Derived> |
| lgamma() const { |
| return unaryExpr(internal::scalar_lgamma_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_digamma_op<Scalar>, const Derived> |
| digamma() const { |
| return unaryExpr(internal::scalar_digamma_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_i0e_op<Scalar>, const Derived> |
| i0e() const { |
| return unaryExpr(internal::scalar_i0e_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_i1e_op<Scalar>, const Derived> |
| i1e() const { |
| return unaryExpr(internal::scalar_i1e_op<Scalar>()); |
| } |
| |
| // igamma(a = this, x = other) |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_igamma_op<Scalar>, const Derived, const OtherDerived> |
| igamma(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_igamma_op<Scalar>()); |
| } |
| |
| // igamma_der_a(a = this, x = other) |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_igamma_der_a_op<Scalar>, const Derived, const OtherDerived> |
| igamma_der_a(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_igamma_der_a_op<Scalar>()); |
| } |
| |
| // gamma_sample_der_alpha(alpha = this, sample = other) |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_gamma_sample_der_alpha_op<Scalar>, const Derived, const OtherDerived> |
| gamma_sample_der_alpha(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_gamma_sample_der_alpha_op<Scalar>()); |
| } |
| |
| // igammac(a = this, x = other) |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_igammac_op<Scalar>, const Derived, const OtherDerived> |
| igammac(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_igammac_op<Scalar>()); |
| } |
| |
| // zeta(x = this, q = other) |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_zeta_op<Scalar>, const Derived, const OtherDerived> |
| zeta(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_zeta_op<Scalar>()); |
| } |
| |
| // polygamma(n = this, x = other) |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_polygamma_op<Scalar>, const Derived, const OtherDerived> |
| polygamma(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_polygamma_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_erf_op<Scalar>, const Derived> |
| erf() const { |
| return unaryExpr(internal::scalar_erf_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_erfc_op<Scalar>, const Derived> |
| erfc() const { |
| return unaryExpr(internal::scalar_erfc_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_logistic_op<Scalar>, const Derived> |
| sigmoid() const { |
| return unaryExpr(internal::scalar_logistic_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_exp_op<Scalar>, const Derived> |
| exp() const { |
| return unaryExpr(internal::scalar_exp_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_expm1_op<Scalar>, const Derived> |
| expm1() const { |
| return unaryExpr(internal::scalar_expm1_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_log_op<Scalar>, const Derived> |
| log() const { |
| return unaryExpr(internal::scalar_log_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_log1p_op<Scalar>, const Derived> |
| log1p() const { |
| return unaryExpr(internal::scalar_log1p_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_abs_op<Scalar>, const Derived> |
| abs() const { |
| return unaryExpr(internal::scalar_abs_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_clamp_op<Scalar>, const Derived> |
| clip(Scalar min, Scalar max) const { |
| return unaryExpr(internal::scalar_clamp_op<Scalar>(min, max)); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const typename internal::conditional<NumTraits<CoeffReturnType>::IsComplex, |
| TensorCwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, const Derived>, |
| Derived>::type |
| conjugate() const { |
| return choose(Cond<NumTraits<CoeffReturnType>::IsComplex>(), unaryExpr(internal::scalar_conjugate_op<Scalar>()), derived()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::bind2nd_op<internal::scalar_pow_op<Scalar,Scalar> >, const Derived> |
| pow(Scalar exponent) const { |
| return unaryExpr(internal::bind2nd_op<internal::scalar_pow_op<Scalar,Scalar> >(exponent)); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_real_op<Scalar>, const Derived> |
| real() const { |
| return unaryExpr(internal::scalar_real_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_imag_op<Scalar>, const Derived> |
| imag() const { |
| return unaryExpr(internal::scalar_imag_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::bind2nd_op<internal::scalar_sum_op<Scalar,Scalar> >, const Derived> |
| operator+ (Scalar rhs) const { |
| return unaryExpr(internal::bind2nd_op<internal::scalar_sum_op<Scalar,Scalar> >(rhs)); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE friend |
| const TensorCwiseUnaryOp<internal::bind1st_op<internal::scalar_sum_op<Scalar> >, const Derived> |
| operator+ (Scalar lhs, const Derived& rhs) { |
| return rhs.unaryExpr(internal::bind1st_op<internal::scalar_sum_op<Scalar> >(lhs)); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::bind2nd_op<internal::scalar_difference_op<Scalar,Scalar> >, const Derived> |
| operator- (Scalar rhs) const { |
| EIGEN_STATIC_ASSERT((NumTraits<Scalar>::IsSigned || internal::is_same<Scalar, const std::complex<float> >::value), YOU_MADE_A_PROGRAMMING_MISTAKE); |
| return unaryExpr(internal::bind2nd_op<internal::scalar_difference_op<Scalar,Scalar> >(rhs)); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE friend |
| const TensorCwiseUnaryOp<internal::bind1st_op<internal::scalar_difference_op<Scalar> >, const Derived> |
| operator- (Scalar lhs, const Derived& rhs) { |
| return rhs.unaryExpr(internal::bind1st_op<internal::scalar_difference_op<Scalar> >(lhs)); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::bind2nd_op<internal::scalar_product_op<Scalar,Scalar> >, const Derived> |
| operator* (Scalar rhs) const { |
| return unaryExpr(internal::bind2nd_op<internal::scalar_product_op<Scalar,Scalar> >(rhs)); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE friend |
| const TensorCwiseUnaryOp<internal::bind1st_op<internal::scalar_product_op<Scalar> >, const Derived> |
| operator* (Scalar lhs, const Derived& rhs) { |
| return rhs.unaryExpr(internal::bind1st_op<internal::scalar_product_op<Scalar> >(lhs)); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::bind2nd_op<internal::scalar_quotient_op<Scalar,Scalar> >, const Derived> |
| operator/ (Scalar rhs) const { |
| return unaryExpr(internal::bind2nd_op<internal::scalar_quotient_op<Scalar,Scalar> >(rhs)); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE friend |
| const TensorCwiseUnaryOp<internal::bind1st_op<internal::scalar_quotient_op<Scalar> >, const Derived> |
| operator/ (Scalar lhs, const Derived& rhs) { |
| return rhs.unaryExpr(internal::bind1st_op<internal::scalar_quotient_op<Scalar> >(lhs)); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_mod_op<Scalar>, const Derived> |
| operator% (Scalar rhs) const { |
| EIGEN_STATIC_ASSERT(NumTraits<Scalar>::IsInteger, YOU_MADE_A_PROGRAMMING_MISTAKE_TRY_MOD); |
| return unaryExpr(internal::scalar_mod_op<Scalar>(rhs)); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> > |
| cwiseMax(Scalar threshold) const { |
| return cwiseMax(constant(threshold)); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> > |
| cwiseMin(Scalar threshold) const { |
| return cwiseMin(constant(threshold)); |
| } |
| |
| template<typename NewType> |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const typename internal::conditional<internal::is_same<NewType, CoeffReturnType>::value, |
| Derived, |
| TensorConversionOp<NewType, const Derived> >::type |
| cast() const { |
| return choose(Cond<internal::is_same<NewType, CoeffReturnType>::value>(), derived(), TensorConversionOp<NewType, const Derived>(derived())); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_round_op<Scalar>, const Derived> |
| round() const { |
| return unaryExpr(internal::scalar_round_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_ceil_op<Scalar>, const Derived> |
| ceil() const { |
| return unaryExpr(internal::scalar_ceil_op<Scalar>()); |
| } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_floor_op<Scalar>, const Derived> |
| floor() const { |
| return unaryExpr(internal::scalar_floor_op<Scalar>()); |
| } |
| |
| // Generic binary operation support. |
| template <typename CustomBinaryOp, typename OtherDerived> EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<CustomBinaryOp, const Derived, const OtherDerived> |
| binaryExpr(const OtherDerived& other, const CustomBinaryOp& func) const { |
| return TensorCwiseBinaryOp<CustomBinaryOp, const Derived, const OtherDerived>(derived(), other, func); |
| } |
| |
| // Coefficient-wise binary operators. |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_sum_op<Scalar>, const Derived, const OtherDerived> |
| operator+(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_sum_op<Scalar>()); |
| } |
| |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_difference_op<Scalar>, const Derived, const OtherDerived> |
| operator-(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_difference_op<Scalar>()); |
| } |
| |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_product_op<Scalar>, const Derived, const OtherDerived> |
| operator*(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_product_op<Scalar>()); |
| } |
| |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_quotient_op<Scalar>, const Derived, const OtherDerived> |
| operator/(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_quotient_op<Scalar>()); |
| } |
| |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived, const OtherDerived> |
| cwiseMax(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_max_op<Scalar>()); |
| } |
| |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived, const OtherDerived> |
| cwiseMin(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_min_op<Scalar>()); |
| } |
| |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_boolean_and_op, const Derived, const OtherDerived> |
| operator&&(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_boolean_and_op()); |
| } |
| |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_boolean_or_op, const Derived, const OtherDerived> |
| operator||(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_boolean_or_op()); |
| } |
| |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_boolean_xor_op, const Derived, const OtherDerived> |
| operator^(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_boolean_xor_op()); |
| } |
| |
| // Comparisons and tests. |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LT>, const Derived, const OtherDerived> |
| operator<(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LT>()); |
| } |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LE>, const Derived, const OtherDerived> |
| operator<=(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LE>()); |
| } |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GT>, const Derived, const OtherDerived> |
| operator>(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GT>()); |
| } |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GE>, const Derived, const OtherDerived> |
| operator>=(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GE>()); |
| } |
| |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_EQ>, const Derived, const OtherDerived> |
| operator==(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_EQ>()); |
| } |
| |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_NEQ>, const Derived, const OtherDerived> |
| operator!=(const OtherDerived& other) const { |
| return binaryExpr(other.derived(), internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_NEQ>()); |
| } |
| |
| // comparisons and tests for Scalars |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LT>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> > |
| operator<(Scalar threshold) const { |
| return operator<(constant(threshold)); |
| } |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LE>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> > |
| operator<=(Scalar threshold) const { |
| return operator<=(constant(threshold)); |
| } |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GT>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> > |
| operator>(Scalar threshold) const { |
| return operator>(constant(threshold)); |
| } |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GE>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> > |
| operator>=(Scalar threshold) const { |
| return operator>=(constant(threshold)); |
| } |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_EQ>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> > |
| operator==(Scalar threshold) const { |
| return operator==(constant(threshold)); |
| } |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_NEQ>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> > |
| operator!=(Scalar threshold) const { |
| return operator!=(constant(threshold)); |
| } |
| |
| // Checks |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_isnan_op<Scalar>, const Derived> |
| (isnan)() const { |
| return unaryExpr(internal::scalar_isnan_op<Scalar>()); |
| } |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_isinf_op<Scalar>, const Derived> |
| (isinf)() const { |
| return unaryExpr(internal::scalar_isinf_op<Scalar>()); |
| } |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_isfinite_op<Scalar>, const Derived> |
| (isfinite)() const { |
| return unaryExpr(internal::scalar_isfinite_op<Scalar>()); |
| } |
| |
| // Coefficient-wise ternary operators. |
| template<typename ThenDerived, typename ElseDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorSelectOp<const Derived, const ThenDerived, const ElseDerived> |
| select(const ThenDerived& thenTensor, const ElseDerived& elseTensor) const { |
| return TensorSelectOp<const Derived, const ThenDerived, const ElseDerived>(derived(), thenTensor.derived(), elseTensor.derived()); |
| } |
| |
| // Contractions. |
| typedef Eigen::IndexPair<Index> DimensionPair; |
| |
| template<typename OtherDerived, typename Dimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorContractionOp<const Dimensions, const Derived, const OtherDerived, const NoOpOutputKernel> |
| contract(const OtherDerived& other, const Dimensions& dims) const { |
| return TensorContractionOp<const Dimensions, const Derived, const OtherDerived, const NoOpOutputKernel>(derived(), other.derived(), dims); |
| } |
| |
| template<typename OtherDerived, typename Dimensions, typename OutputKernel> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorContractionOp<const Dimensions, const Derived, const OtherDerived, const OutputKernel> |
| contract(const OtherDerived& other, const Dimensions& dims, const OutputKernel& output_kernel) const { |
| return TensorContractionOp<const Dimensions, const Derived, const OtherDerived, const OutputKernel>(derived(), other.derived(), dims, output_kernel); |
| } |
| |
| // Convolutions. |
| template<typename KernelDerived, typename Dimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorConvolutionOp<const Dimensions, const Derived, const KernelDerived> |
| convolve(const KernelDerived& kernel, const Dimensions& dims) const { |
| return TensorConvolutionOp<const Dimensions, const Derived, const KernelDerived>(derived(), kernel.derived(), dims); |
| } |
| |
| // Fourier transforms |
| template <int FFTDataType, int FFTDirection, typename FFT> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorFFTOp<const FFT, const Derived, FFTDataType, FFTDirection> |
| fft(const FFT& dims) const { |
| return TensorFFTOp<const FFT, const Derived, FFTDataType, FFTDirection>(derived(), dims); |
| } |
| |
| // Scan. |
| typedef TensorScanOp<internal::SumReducer<CoeffReturnType>, const Derived> TensorScanSumOp; |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorScanSumOp |
| cumsum(const Index& axis, bool exclusive = false) const { |
| return TensorScanSumOp(derived(), axis, exclusive); |
| } |
| |
| typedef TensorScanOp<internal::ProdReducer<CoeffReturnType>, const Derived> TensorScanProdOp; |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorScanProdOp |
| cumprod(const Index& axis, bool exclusive = false) const { |
| return TensorScanProdOp(derived(), axis, exclusive); |
| } |
| |
| template <typename Reducer> |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorScanOp<Reducer, const Derived> |
| scan(const Index& axis, const Reducer& reducer, bool exclusive = false) const { |
| return TensorScanOp<Reducer, const Derived>(derived(), axis, exclusive, reducer); |
| } |
| |
| // Reductions. |
| template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorReductionOp<internal::SumReducer<CoeffReturnType>, const Dims, const Derived> |
| sum(const Dims& dims) const { |
| return TensorReductionOp<internal::SumReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::SumReducer<CoeffReturnType>()); |
| } |
| |
| const TensorReductionOp<internal::SumReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived> |
| sum() const { |
| DimensionList<Index, NumDimensions> in_dims; |
| return TensorReductionOp<internal::SumReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::SumReducer<CoeffReturnType>()); |
| } |
| |
| template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorReductionOp<internal::MeanReducer<CoeffReturnType>, const Dims, const Derived> |
| mean(const Dims& dims) const { |
| return TensorReductionOp<internal::MeanReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::MeanReducer<CoeffReturnType>()); |
| } |
| |
| const TensorReductionOp<internal::MeanReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived> |
| mean() const { |
| DimensionList<Index, NumDimensions> in_dims; |
| return TensorReductionOp<internal::MeanReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::MeanReducer<CoeffReturnType>()); |
| } |
| |
| template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorReductionOp<internal::ProdReducer<CoeffReturnType>, const Dims, const Derived> |
| prod(const Dims& dims) const { |
| return TensorReductionOp<internal::ProdReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::ProdReducer<CoeffReturnType>()); |
| } |
| |
| const TensorReductionOp<internal::ProdReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived> |
| prod() const { |
| DimensionList<Index, NumDimensions> in_dims; |
| return TensorReductionOp<internal::ProdReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::ProdReducer<CoeffReturnType>()); |
| } |
| |
| template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const Dims, const Derived> |
| maximum(const Dims& dims) const { |
| return TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::MaxReducer<CoeffReturnType>()); |
| } |
| |
| const TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived> |
| maximum() const { |
| DimensionList<Index, NumDimensions> in_dims; |
| return TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::MaxReducer<CoeffReturnType>()); |
| } |
| |
| template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorReductionOp<internal::MinReducer<CoeffReturnType>, const Dims, const Derived> |
| minimum(const Dims& dims) const { |
| return TensorReductionOp<internal::MinReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::MinReducer<CoeffReturnType>()); |
| } |
| |
| const TensorReductionOp<internal::MinReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived> |
| minimum() const { |
| DimensionList<Index, NumDimensions> in_dims; |
| return TensorReductionOp<internal::MinReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::MinReducer<CoeffReturnType>()); |
| } |
| |
| template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorReductionOp<internal::AndReducer, const Dims, const typename internal::conditional<internal::is_same<bool, CoeffReturnType>::value, Derived, TensorConversionOp<bool, const Derived> >::type > |
| all(const Dims& dims) const { |
| return cast<bool>().reduce(dims, internal::AndReducer()); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorReductionOp<internal::AndReducer, const DimensionList<Index, NumDimensions>, const typename internal::conditional<internal::is_same<bool, CoeffReturnType>::value, Derived, TensorConversionOp<bool, const Derived> >::type > |
| all() const { |
| DimensionList<Index, NumDimensions> in_dims; |
| return cast<bool>().reduce(in_dims, internal::AndReducer()); |
| } |
| |
| template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorReductionOp<internal::OrReducer, const Dims, const typename internal::conditional<internal::is_same<bool, CoeffReturnType>::value, Derived, TensorConversionOp<bool, const Derived> >::type > |
| any(const Dims& dims) const { |
| return cast<bool>().reduce(dims, internal::OrReducer()); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorReductionOp<internal::OrReducer, const DimensionList<Index, NumDimensions>, const typename internal::conditional<internal::is_same<bool, CoeffReturnType>::value, Derived, TensorConversionOp<bool, const Derived> >::type > |
| any() const { |
| DimensionList<Index, NumDimensions> in_dims; |
| return cast<bool>().reduce(in_dims, internal::OrReducer()); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorTupleReducerOp< |
| internal::ArgMaxTupleReducer<Tuple<Index, CoeffReturnType> >, |
| const array<Index, NumDimensions>, const Derived> |
| argmax() const { |
| array<Index, NumDimensions> in_dims; |
| for (Index d = 0; d < NumDimensions; ++d) in_dims[d] = d; |
| return TensorTupleReducerOp< |
| internal::ArgMaxTupleReducer<Tuple<Index, CoeffReturnType> >, |
| const array<Index, NumDimensions>, |
| const Derived>(derived(), internal::ArgMaxTupleReducer<Tuple<Index, CoeffReturnType> >(), -1, in_dims); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorTupleReducerOp< |
| internal::ArgMinTupleReducer<Tuple<Index, CoeffReturnType> >, |
| const array<Index, NumDimensions>, const Derived> |
| argmin() const { |
| array<Index, NumDimensions> in_dims; |
| for (Index d = 0; d < NumDimensions; ++d) in_dims[d] = d; |
| return TensorTupleReducerOp< |
| internal::ArgMinTupleReducer<Tuple<Index, CoeffReturnType> >, |
| const array<Index, NumDimensions>, |
| const Derived>(derived(), internal::ArgMinTupleReducer<Tuple<Index, CoeffReturnType> >(), -1, in_dims); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorTupleReducerOp< |
| internal::ArgMaxTupleReducer<Tuple<Index, CoeffReturnType> >, |
| const array<Index, 1>, const Derived> |
| argmax(const Index return_dim) const { |
| array<Index, 1> in_dims; |
| in_dims[0] = return_dim; |
| return TensorTupleReducerOp< |
| internal::ArgMaxTupleReducer<Tuple<Index, CoeffReturnType> >, |
| const array<Index, 1>, |
| const Derived>(derived(), internal::ArgMaxTupleReducer<Tuple<Index, CoeffReturnType> >(), return_dim, in_dims); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorTupleReducerOp< |
| internal::ArgMinTupleReducer<Tuple<Index, CoeffReturnType> >, |
| const array<Index, 1>, const Derived> |
| argmin(const Index return_dim) const { |
| array<Index, 1> in_dims; |
| in_dims[0] = return_dim; |
| return TensorTupleReducerOp< |
| internal::ArgMinTupleReducer<Tuple<Index, CoeffReturnType> >, |
| const array<Index, 1>, |
| const Derived>(derived(), internal::ArgMinTupleReducer<Tuple<Index, CoeffReturnType> >(), return_dim, in_dims); |
| } |
| |
| template <typename Reducer, typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorReductionOp<Reducer, const Dims, const Derived> |
| reduce(const Dims& dims, const Reducer& reducer) const { |
| return TensorReductionOp<Reducer, const Dims, const Derived>(derived(), dims, reducer); |
| } |
| |
| template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorTraceOp<const Dims, const Derived> |
| trace(const Dims& dims) const { |
| return TensorTraceOp<const Dims, const Derived>(derived(), dims); |
| } |
| |
| const TensorTraceOp<const DimensionList<Index, NumDimensions>, const Derived> |
| trace() const { |
| DimensionList<Index, NumDimensions> in_dims; |
| return TensorTraceOp<const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims); |
| } |
| |
| template <typename Broadcast> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorBroadcastingOp<const Broadcast, const Derived> |
| broadcast(const Broadcast& bcast) const { |
| return TensorBroadcastingOp<const Broadcast, const Derived>(derived(), bcast); |
| } |
| |
| template <typename Axis, typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorConcatenationOp<Axis, const Derived, const OtherDerived> |
| concatenate(const OtherDerived& other, Axis axis) const { |
| return TensorConcatenationOp<Axis, const Derived, const OtherDerived>(derived(), other.derived(), axis); |
| } |
| |
| template <typename PatchDims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorPatchOp<const PatchDims, const Derived> |
| extract_patches(const PatchDims& patch_dims) const { |
| return TensorPatchOp<const PatchDims, const Derived>(derived(), patch_dims); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorImagePatchOp<Dynamic, Dynamic, const Derived> |
| extract_image_patches(const Index patch_rows = 1, const Index patch_cols = 1, |
| const Index row_stride = 1, const Index col_stride = 1, |
| const Index in_row_stride = 1, const Index in_col_stride = 1, |
| const PaddingType padding_type = PADDING_SAME, const Scalar padding_value = Scalar(0)) const { |
| return TensorImagePatchOp<Dynamic, Dynamic, const Derived>(derived(), patch_rows, patch_cols, row_stride, col_stride, |
| in_row_stride, in_col_stride, 1, 1, padding_type, padding_value); |
| } |
| |
| 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 Index in_row_stride, const Index in_col_stride, |
| const Index row_inflate_stride, const Index col_inflate_stride, |
| const Index padding_top, const Index padding_bottom, |
| const Index padding_left,const Index padding_right, |
| const Scalar padding_value) const { |
| return TensorImagePatchOp<Dynamic, Dynamic, const Derived>(derived(), patch_rows, patch_cols, row_stride, col_stride, |
| in_row_stride, in_col_stride, row_inflate_stride, col_inflate_stride, |
| padding_top, padding_bottom, padding_left, padding_right, padding_value); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorVolumePatchOp<Dynamic, Dynamic, Dynamic, const Derived> |
| extract_volume_patches(const Index patch_planes, const Index patch_rows, const Index patch_cols, |
| const Index plane_stride = 1, const Index row_stride = 1, const Index col_stride = 1, |
| const PaddingType padding_type = PADDING_SAME, const Scalar padding_value = Scalar(0)) const { |
| return TensorVolumePatchOp<Dynamic, Dynamic, Dynamic, const Derived>(derived(), patch_planes, patch_rows, patch_cols, plane_stride, row_stride, col_stride, 1, 1, 1, 1, 1, 1, padding_type, padding_value); |
| } |
| |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorVolumePatchOp<Dynamic, Dynamic, Dynamic, const Derived> |
| extract_volume_patches(const Index patch_planes, const Index patch_rows, const Index patch_cols, |
| const Index plane_stride, const Index row_stride, const Index col_stride, |
| const Index plane_inflate_stride, const Index row_inflate_stride, const Index col_inflate_stride, |
| const Index padding_top_z, const Index padding_bottom_z, |
| const Index padding_top, const Index padding_bottom, |
| const Index padding_left, const Index padding_right, const Scalar padding_value = Scalar(0)) const { |
| return TensorVolumePatchOp<Dynamic, Dynamic, Dynamic, const Derived>(derived(), patch_planes, patch_rows, patch_cols, plane_stride, row_stride, col_stride, 1, 1, 1, plane_inflate_stride, row_inflate_stride, col_inflate_stride, padding_top_z, padding_bottom_z, padding_top, padding_bottom, padding_left, padding_right, padding_value); |
| } |
| |
| // 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 { |
| return TensorReshapingOp<const NewDimensions, const Derived>(derived(), newDimensions); |
| } |
| template <typename StartIndices, typename Sizes> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorSlicingOp<const StartIndices, const Sizes, const Derived> |
| slice(const StartIndices& startIndices, const Sizes& sizes) const { |
| return TensorSlicingOp<const StartIndices, const Sizes, const Derived>(derived(), startIndices, sizes); |
| } |
| template <typename StartIndices, typename StopIndices, typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorStridingSlicingOp<const StartIndices, const StopIndices, const Strides, const Derived> |
| stridedSlice(const StartIndices& startIndices, const StopIndices& stopIndices, const Strides& strides) const { |
| return TensorStridingSlicingOp<const StartIndices, const StopIndices, const Strides, |
| const Derived>(derived(), startIndices, stopIndices, strides); |
| } |
| 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, 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> |
| pad(const PaddingDimensions& padding) const { |
| return TensorPaddingOp<const PaddingDimensions, const Derived>(derived(), padding, internal::scalar_cast_op<int, Scalar>()(0)); |
| } |
| template <typename PaddingDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorPaddingOp<const PaddingDimensions, const Derived> |
| pad(const PaddingDimensions& padding, const Scalar padding_value) const { |
| return TensorPaddingOp<const PaddingDimensions, const Derived>(derived(), padding, padding_value); |
| } |
| template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorShufflingOp<const Shuffle, const Derived> |
| shuffle(const Shuffle& shfl) const { |
| return TensorShufflingOp<const Shuffle, const Derived>(derived(), shfl); |
| } |
| template <typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorStridingOp<const Strides, const Derived> |
| stride(const Strides& strides) const { |
| return TensorStridingOp<const Strides, const Derived>(derived(), strides); |
| } |
| template <typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorInflationOp<const Strides, const Derived> |
| inflate(const Strides& strides) const { |
| return TensorInflationOp<const Strides, const Derived>(derived(), strides); |
| } |
| |
| // Returns a tensor containing index/value tuples |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorIndexTupleOp<const Derived> |
| index_tuples() const { |
| return TensorIndexTupleOp<const Derived>(derived()); |
| } |
| |
| // Support for custom unary and binary operations |
| template <typename CustomUnaryFunc> |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCustomUnaryOp<const CustomUnaryFunc, const Derived> customOp(const CustomUnaryFunc& op) const { |
| return TensorCustomUnaryOp<const CustomUnaryFunc, const Derived>(derived(), op); |
| } |
| template <typename OtherDerived, typename CustomBinaryFunc> |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorCustomBinaryOp<const CustomBinaryFunc, const Derived, const OtherDerived> customOp(const OtherDerived& other, const CustomBinaryFunc& op) const { |
| return TensorCustomBinaryOp<const CustomBinaryFunc, const Derived, const OtherDerived>(derived(), other, op); |
| } |
| |
| // Force the evaluation of the expression. |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorForcedEvalOp<const Derived> eval() const { |
| return TensorForcedEvalOp<const Derived>(derived()); |
| } |
| |
| protected: |
| template <typename Scalar, int NumIndices, int Options, typename IndexType> friend class Tensor; |
| template <typename Scalar, typename Dimensions, int Option, typename IndexTypes> friend class TensorFixedSize; |
| // the Eigen:: prefix is required to workaround a compilation issue with nvcc 9.0 |
| template <typename OtherDerived, int AccessLevel> friend class Eigen::TensorBase; |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const Derived& derived() const { return *static_cast<const Derived*>(this); } |
| }; |
| |
| template<typename Derived, int AccessLevel = internal::accessors_level<Derived>::value> |
| class TensorBase : public TensorBase<Derived, ReadOnlyAccessors> { |
| public: |
| typedef internal::traits<Derived> DerivedTraits; |
| typedef typename DerivedTraits::Scalar Scalar; |
| typedef typename DerivedTraits::Index Index; |
| typedef Scalar CoeffReturnType; |
| static const int NumDimensions = DerivedTraits::NumDimensions; |
| |
| template <typename Scalar, int NumIndices, int Options, typename IndexType> friend class Tensor; |
| template <typename Scalar, typename Dimensions, int Option, typename IndexTypes> friend class TensorFixedSize; |
| // the Eigen:: prefix is required to workaround a compilation issue with nvcc 9.0 |
| template <typename OtherDerived, int OtherAccessLevel> friend class Eigen::TensorBase; |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE Derived& setZero() { |
| return setConstant(Scalar(0)); |
| } |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE Derived& setConstant(const Scalar& val) { |
| return derived() = this->constant(val); |
| } |
| EIGEN_DEVICE_FUNC |
| 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>(); |
| } |
| |
| #if 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() = derived() + other.derived(); |
| } |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| Derived& operator-=(const OtherDerived& other) { |
| return derived() = derived() - other.derived(); |
| } |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| Derived& operator*=(const OtherDerived& other) { |
| return derived() = derived() * other.derived(); |
| } |
| template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| Derived& operator/=(const OtherDerived& other) { |
| return derived() = derived() / other.derived(); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorLayoutSwapOp<const Derived> |
| swap_layout() const { |
| return TensorLayoutSwapOp<const Derived>(derived()); |
| } |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| TensorLayoutSwapOp<Derived> |
| swap_layout() { |
| return TensorLayoutSwapOp<Derived>(derived()); |
| } |
| |
| template <typename Axis, typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorConcatenationOp<const Axis, const Derived, const OtherDerived> |
| concatenate(const OtherDerived& other, const Axis& axis) const { |
| return TensorConcatenationOp<const Axis, const Derived, const OtherDerived>(derived(), other, axis); |
| } |
| template <typename Axis, typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| TensorConcatenationOp<const Axis, Derived, OtherDerived> |
| concatenate(const OtherDerived& other, const Axis& axis) { |
| return TensorConcatenationOp<const Axis, Derived, OtherDerived>(derived(), other, axis); |
| } |
| |
| template <typename NewDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorReshapingOp<const NewDimensions, const Derived> |
| reshape(const NewDimensions& newDimensions) const { |
| return TensorReshapingOp<const NewDimensions, const Derived>(derived(), newDimensions); |
| } |
| template <typename NewDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| TensorReshapingOp<const NewDimensions, Derived> |
| reshape(const NewDimensions& newDimensions) { |
| return TensorReshapingOp<const NewDimensions, Derived>(derived(), newDimensions); |
| } |
| |
| template <typename StartIndices, typename Sizes> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorSlicingOp<const StartIndices, const Sizes, const Derived> |
| slice(const StartIndices& startIndices, const Sizes& sizes) const { |
| return TensorSlicingOp<const StartIndices, const Sizes, const Derived>(derived(), startIndices, sizes); |
| } |
| template <typename StartIndices, typename Sizes> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| TensorSlicingOp<const StartIndices, const Sizes, Derived> |
| slice(const StartIndices& startIndices, const Sizes& sizes) { |
| return TensorSlicingOp<const StartIndices, const Sizes, Derived>(derived(), startIndices, sizes); |
| } |
| |
| template <typename StartIndices, typename StopIndices, typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorStridingSlicingOp<const StartIndices, const StopIndices, const Strides, const Derived> |
| stridedSlice(const StartIndices& startIndices, const StopIndices& stopIndices, const Strides& strides) const { |
| return TensorStridingSlicingOp<const StartIndices, const StopIndices, const Strides, |
| const Derived>(derived(), startIndices, stopIndices, strides); |
| } |
| template <typename StartIndices, typename StopIndices, typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| TensorStridingSlicingOp<const StartIndices, const StopIndices, const Strides, Derived> |
| stridedSlice(const StartIndices& startIndices, const StopIndices& stopIndices, const Strides& strides) { |
| return TensorStridingSlicingOp<const StartIndices, const StopIndices, const Strides, |
| Derived>(derived(), startIndices, stopIndices, strides); |
| } |
| |
| template <DenseIndex DimId> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorChippingOp<DimId, const Derived> |
| chip(const Index offset) const { |
| return TensorChippingOp<DimId, const Derived>(derived(), offset, DimId); |
| } |
| template <Index DimId> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| TensorChippingOp<DimId, Derived> |
| chip(const Index offset) { |
| return TensorChippingOp<DimId, 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); |
| } |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| TensorChippingOp<Dynamic, Derived> |
| chip(const Index offset, const Index dim) { |
| return TensorChippingOp<Dynamic, 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 ReverseDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| TensorReverseOp<const ReverseDimensions, Derived> |
| reverse(const ReverseDimensions& rev) { |
| return TensorReverseOp<const ReverseDimensions, Derived>(derived(), rev); |
| } |
| |
| template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorShufflingOp<const Shuffle, const Derived> |
| shuffle(const Shuffle& shfl) const { |
| return TensorShufflingOp<const Shuffle, const Derived>(derived(), shfl); |
| } |
| template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| TensorShufflingOp<const Shuffle, Derived> |
| shuffle(const Shuffle& shfl) { |
| return TensorShufflingOp<const Shuffle, Derived>(derived(), shfl); |
| } |
| |
| template <typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const TensorStridingOp<const Strides, const Derived> |
| stride(const Strides& strides) const { |
| return TensorStridingOp<const Strides, const Derived>(derived(), strides); |
| } |
| template <typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| TensorStridingOp<const Strides, Derived> |
| stride(const Strides& strides) { |
| return TensorStridingOp<const Strides, Derived>(derived(), strides); |
| } |
| |
| // Select the device on which to evaluate the expression. |
| template <typename DeviceType> |
| TensorDevice<Derived, DeviceType> device(const DeviceType& dev) { |
| return TensorDevice<Derived, DeviceType>(dev, derived()); |
| } |
| |
| protected: |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE Derived& derived() { return *static_cast<Derived*>(this); } |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE const Derived& derived() const { return *static_cast<const Derived*>(this); } |
| }; |
| #endif // EIGEN_PARSED_BY_DOXYGEN |
| } // end namespace Eigen |
| |
| #endif // EIGEN_CXX11_TENSOR_TENSOR_BASE_H |
