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// 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
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
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 std::remove_const_t<Scalar> CoeffReturnType;
static constexpr 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_bessel_i0_op<Scalar>, const Derived>
bessel_i0() const {
return unaryExpr(internal::scalar_bessel_i0_op<Scalar>());
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_bessel_i0e_op<Scalar>, const Derived>
bessel_i0e() const {
return unaryExpr(internal::scalar_bessel_i0e_op<Scalar>());
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_bessel_i1_op<Scalar>, const Derived>
bessel_i1() const {
return unaryExpr(internal::scalar_bessel_i1_op<Scalar>());
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_bessel_i1e_op<Scalar>, const Derived>
bessel_i1e() const {
return unaryExpr(internal::scalar_bessel_i1e_op<Scalar>());
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_bessel_j0_op<Scalar>, const Derived>
bessel_j0() const {
return unaryExpr(internal::scalar_bessel_j0_op<Scalar>());
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_bessel_y0_op<Scalar>, const Derived>
bessel_y0() const {
return unaryExpr(internal::scalar_bessel_y0_op<Scalar>());
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_bessel_j1_op<Scalar>, const Derived>
bessel_j1() const {
return unaryExpr(internal::scalar_bessel_j1_op<Scalar>());
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_bessel_y1_op<Scalar>, const Derived>
bessel_y1() const {
return unaryExpr(internal::scalar_bessel_y1_op<Scalar>());
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_bessel_k0_op<Scalar>, const Derived>
bessel_k0() const {
return unaryExpr(internal::scalar_bessel_k0_op<Scalar>());
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_bessel_k0e_op<Scalar>, const Derived>
bessel_k0e() const {
return unaryExpr(internal::scalar_bessel_k0e_op<Scalar>());
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_bessel_k1_op<Scalar>, const Derived>
bessel_k1() const {
return unaryExpr(internal::scalar_bessel_k1_op<Scalar>());
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_bessel_k1e_op<Scalar>, const Derived>
bessel_k1e() const {
return unaryExpr(internal::scalar_bessel_k1e_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_ndtri_op<Scalar>, const Derived>
ndtri() const {
return unaryExpr(internal::scalar_ndtri_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_log2_op<Scalar>, const Derived>
log2() const {
return unaryExpr(internal::scalar_log2_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_arg_op<Scalar>, const Derived>
arg() const {
return unaryExpr(internal::scalar_arg_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 std::conditional_t<NumTraits<CoeffReturnType>::IsComplex,
TensorCwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, const Derived>,
Derived>
conjugate() const {
return choose(Cond<NumTraits<CoeffReturnType>::IsComplex>(), unaryExpr(internal::scalar_conjugate_op<Scalar>()), derived());
}
template<typename ScalarExponent>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const std::enable_if_t<internal::is_arithmetic<typename NumTraits<ScalarExponent>::Real>::value,
TensorCwiseUnaryOp<internal::scalar_unary_pow_op<Scalar, ScalarExponent>, const Derived>>
pow(ScalarExponent exponent) const
{
return unaryExpr(internal::scalar_unary_pow_op<Scalar, ScalarExponent>(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));
}
template <int NanPropagation=PropagateFast>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_max_op<Scalar,Scalar,NanPropagation>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> >
cwiseMax(Scalar threshold) const {
return cwiseMax<NanPropagation>(constant(threshold));
}
template <int NanPropagation=PropagateFast>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_min_op<Scalar,Scalar,NanPropagation>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> >
cwiseMin(Scalar threshold) const {
return cwiseMin<NanPropagation>(constant(threshold));
}
template<typename NewType>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const std::conditional_t<internal::is_same<NewType, CoeffReturnType>::value,
Derived,
TensorConversionOp<NewType, const Derived> >
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_rint_op<Scalar>, const Derived>
rint() const {
return unaryExpr(internal::scalar_rint_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<int NaNPropagation=PropagateFast, typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorCwiseBinaryOp<internal::scalar_max_op<Scalar,Scalar, NaNPropagation>, const Derived, const OtherDerived>
cwiseMax(const OtherDerived& other) const {
return binaryExpr(other.derived(), internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
}
template<int NaNPropagation=PropagateFast, typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorCwiseBinaryOp<internal::scalar_min_op<Scalar,Scalar, NaNPropagation>, const Derived, const OtherDerived>
cwiseMin(const OtherDerived& other) const {
return binaryExpr(other.derived(), internal::scalar_min_op<Scalar,Scalar, NaNPropagation>());
}
// logical operators
template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorCwiseBinaryOp<internal::scalar_boolean_and_op<Scalar>, const Derived, const OtherDerived>
operator&&(const OtherDerived& other) const {
return binaryExpr(other.derived(), internal::scalar_boolean_and_op<Scalar>());
}
template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorCwiseBinaryOp<internal::scalar_boolean_or_op<Scalar>, const Derived, const OtherDerived>
operator||(const OtherDerived& other) const {
return binaryExpr(other.derived(), internal::scalar_boolean_or_op<Scalar>());
}
template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorCwiseBinaryOp<internal::scalar_bitwise_and_op<Scalar>, const Derived, const OtherDerived>
operator&(const OtherDerived& other) const {
return binaryExpr(other.derived(), internal::scalar_bitwise_and_op<Scalar>());
}
template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorCwiseBinaryOp<internal::scalar_bitwise_or_op<Scalar>, const Derived, const OtherDerived>
operator|(const OtherDerived& other) const {
return binaryExpr(other.derived(), internal::scalar_bitwise_or_op<Scalar>());
}
template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorCwiseBinaryOp<internal::scalar_bitwise_xor_op<Scalar>, const Derived, const OtherDerived>
operator^(const OtherDerived& other) const {
return binaryExpr(other.derived(), internal::scalar_bitwise_xor_op<Scalar>());
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorCwiseUnaryOp<internal::scalar_boolean_not_op<Scalar>, const Derived>
operator!() const {
return unaryExpr(internal::scalar_boolean_not_op<Scalar>());
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorCwiseUnaryOp<internal::scalar_bitwise_not_op<Scalar>, const Derived>
operator~() const {
return unaryExpr(internal::scalar_bitwise_not_op<Scalar>());
}
// 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 TensorBase<OtherDerived, ReadOnlyAccessors>& 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 TensorBase<OtherDerived, ReadOnlyAccessors>& 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 TensorBase<OtherDerived, ReadOnlyAccessors>& 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 TensorBase<OtherDerived, ReadOnlyAccessors>& 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 TensorBase<OtherDerived, ReadOnlyAccessors>& 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 TensorBase<OtherDerived, ReadOnlyAccessors>& 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));
}
// Predicates.
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorConversionOp<bool, const TensorCwiseUnaryOp<internal::scalar_isnan_op<Scalar, true>, const Derived>>
(isnan)() const {
return unaryExpr(internal::scalar_isnan_op<Scalar, true>()).template cast<bool>();
}
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,int NanPropagation=PropagateFast> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorReductionOp<internal::MaxReducer<CoeffReturnType,NanPropagation>, const Dims, const Derived>
maximum(const Dims& dims) const {
return TensorReductionOp<internal::MaxReducer<CoeffReturnType,NanPropagation>, const Dims, const Derived>(derived(), dims, internal::MaxReducer<CoeffReturnType,NanPropagation>());
}
template <int NanPropagation=PropagateFast>
const TensorReductionOp<internal::MaxReducer<CoeffReturnType,NanPropagation>, const DimensionList<Index, NumDimensions>, const Derived>
maximum() const {
DimensionList<Index, NumDimensions> in_dims;
return TensorReductionOp<internal::MaxReducer<CoeffReturnType,NanPropagation>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::MaxReducer<CoeffReturnType,NanPropagation>());
}
template <typename Dims,int NanPropagation=PropagateFast> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorReductionOp<internal::MinReducer<CoeffReturnType,NanPropagation>, const Dims, const Derived>
minimum(const Dims& dims) const {
return TensorReductionOp<internal::MinReducer<CoeffReturnType,NanPropagation>, const Dims, const Derived>(derived(), dims, internal::MinReducer<CoeffReturnType,NanPropagation>());
}
template <int NanPropagation=PropagateFast>
const TensorReductionOp<internal::MinReducer<CoeffReturnType,NanPropagation>, const DimensionList<Index, NumDimensions>, const Derived>
minimum() const {
DimensionList<Index, NumDimensions> in_dims;
return TensorReductionOp<internal::MinReducer<CoeffReturnType,NanPropagation>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::MinReducer<CoeffReturnType,NanPropagation>());
}
template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorReductionOp<internal::AndReducer, const Dims, const std::conditional_t<internal::is_same<bool, CoeffReturnType>::value, Derived, TensorConversionOp<bool, const Derived> > >
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 std::conditional_t<internal::is_same<bool, CoeffReturnType>::value, Derived, TensorConversionOp<bool, const Derived> > >
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 std::conditional_t<internal::is_same<bool, CoeffReturnType>::value, Derived, TensorConversionOp<bool, const Derived> > >
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 std::conditional_t<internal::is_same<bool, CoeffReturnType>::value, Derived, TensorConversionOp<bool, const Derived> > >
any() const {
DimensionList<Index, NumDimensions> in_dims;
return cast<bool>().reduce(in_dims, internal::OrReducer());
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorPairReducerOp<
internal::ArgMaxPairReducer<Pair<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 TensorPairReducerOp<
internal::ArgMaxPairReducer<Pair<Index, CoeffReturnType> >,
const array<Index, NumDimensions>,
const Derived>(derived(), internal::ArgMaxPairReducer<Pair<Index, CoeffReturnType> >(), -1, in_dims);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorPairReducerOp<
internal::ArgMinPairReducer<Pair<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 TensorPairReducerOp<
internal::ArgMinPairReducer<Pair<Index, CoeffReturnType> >,
const array<Index, NumDimensions>,
const Derived>(derived(), internal::ArgMinPairReducer<Pair<Index, CoeffReturnType> >(), -1, in_dims);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorPairReducerOp<
internal::ArgMaxPairReducer<Pair<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 TensorPairReducerOp<
internal::ArgMaxPairReducer<Pair<Index, CoeffReturnType> >,
const array<Index, 1>,
const Derived>(derived(), internal::ArgMaxPairReducer<Pair<Index, CoeffReturnType> >(), return_dim, in_dims);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorPairReducerOp<
internal::ArgMinPairReducer<Pair<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 TensorPairReducerOp<
internal::ArgMinPairReducer<Pair<Index, CoeffReturnType> >,
const array<Index, 1>,
const Derived>(derived(), internal::ArgMinPairReducer<Pair<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 {
EIGEN_STATIC_ASSERT(DimId < Derived::NumDimensions && DimId >= 0, Chip_Dim_out_of_range)
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 pairs
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorIndexPairOp<const Derived>
index_pairs() const {
return TensorIndexPairOp<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());
}
// Returns a formatted tensor ready for printing to a stream
inline const TensorWithFormat<Derived,DerivedTraits::Layout,DerivedTraits::NumDimensions> format(const TensorIOFormat& fmt) const {
return TensorWithFormat<Derived,DerivedTraits::Layout,DerivedTraits::NumDimensions>(derived(), fmt);
}
#ifdef EIGEN_READONLY_TENSORBASE_PLUGIN
#include EIGEN_READONLY_TENSORBASE_PLUGIN
#endif
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 TensorBase<Derived, ReadOnlyAccessors> Base;
typedef internal::traits<Derived> DerivedTraits;
typedef typename DerivedTraits::Scalar Scalar;
typedef typename DerivedTraits::Index Index;
typedef Scalar CoeffReturnType;
static constexpr 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>();
}
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();
}
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 {
EIGEN_STATIC_ASSERT(DimId < Derived::NumDimensions && DimId >= 0, Chip_Dim_out_of_range)
return TensorChippingOp<DimId, const Derived>(derived(), offset, DimId);
}
template <Index DimId> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
TensorChippingOp<DimId, Derived>
chip(const Index offset) {
EIGEN_STATIC_ASSERT(DimId < Derived::NumDimensions && DimId >= 0, Chip_Dim_out_of_range)
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());
}
// Select the async device on which to evaluate the expression.
template <typename DeviceType, typename DoneCallback>
TensorAsyncDevice<Derived, DeviceType, DoneCallback> device(const DeviceType& dev, DoneCallback done) {
return TensorAsyncDevice<Derived, DeviceType, DoneCallback>(dev, derived(), std::move(done));
}
#ifdef EIGEN_TENSORBASE_PLUGIN
#include EIGEN_TENSORBASE_PLUGIN
#endif
protected:
EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(TensorBase)
EIGEN_DEFAULT_COPY_CONSTRUCTOR(TensorBase)
template<typename OtherDerived> EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& operator=(const OtherDerived& other)
{
typedef TensorAssignOp<Derived, const OtherDerived> Assign;
Assign assign(derived(), other.derived());
internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
return derived();
}
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