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Diffstat (limited to 'third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h')
| -rw-r--r-- | third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h | 294 |
1 files changed, 294 insertions, 0 deletions
diff --git a/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h b/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h new file mode 100644 index 0000000000..b8c1eadfc3 --- /dev/null +++ b/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h @@ -0,0 +1,294 @@ +// 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_TRAITS_H +#define EIGEN_CXX11_TENSOR_TENSOR_TRAITS_H + +namespace Eigen { +namespace internal { + + +template<typename Scalar, int Options> +class compute_tensor_flags +{ + enum { + is_dynamic_size_storage = 1, + + aligned_bit = + ( + ((Options&DontAlign)==0) && ( +#if EIGEN_ALIGN_STATICALLY + (!is_dynamic_size_storage) +#else + 0 +#endif + || +#if EIGEN_ALIGN + is_dynamic_size_storage +#else + 0 +#endif + ) + ) ? AlignedBit : 0, + packet_access_bit = packet_traits<Scalar>::Vectorizable && aligned_bit ? PacketAccessBit : 0 + }; + + public: + enum { ret = packet_access_bit | aligned_bit}; +}; + + +template<typename Scalar_, std::size_t NumIndices_, int Options_, typename IndexType_> +struct traits<Tensor<Scalar_, NumIndices_, Options_, IndexType_> > +{ + typedef Scalar_ Scalar; + typedef Dense StorageKind; + typedef IndexType_ Index; + static const int NumDimensions = NumIndices_; + static const int Layout = Options_ & RowMajor ? RowMajor : ColMajor; + enum { + Options = Options_, + Flags = compute_tensor_flags<Scalar_, Options_>::ret | (is_const<Scalar_>::value ? 0 : LvalueBit), + }; +}; + + +template<typename Scalar_, typename Dimensions, int Options_, typename IndexType_> +struct traits<TensorFixedSize<Scalar_, Dimensions, Options_, IndexType_> > +{ + typedef Scalar_ Scalar; + typedef Dense StorageKind; + typedef IndexType_ Index; + static const int NumDimensions = array_size<Dimensions>::value; + static const int Layout = Options_ & RowMajor ? RowMajor : ColMajor; + enum { + Options = Options_, + Flags = compute_tensor_flags<Scalar_, Options_>::ret | (is_const<Scalar_>::value ? 0: LvalueBit), + }; +}; + + +template<typename Scalar_, int Options_, typename IndexType_> +struct traits<TensorVarDim<Scalar_, Options_, IndexType_> > +{ + typedef Scalar_ Scalar; + typedef Dense StorageKind; + typedef IndexType_ Index; + static const int NumDimensions = -1; + static const int Layout = Options_ & RowMajor ? RowMajor : ColMajor; + enum { + Options = Options_, + Flags = compute_tensor_flags<Scalar_, Options_>::ret | (is_const<Scalar_>::value ? 0 : LvalueBit), + }; +}; + +template<typename PlainObjectType, int Options_> +struct traits<TensorMap<PlainObjectType, Options_> > + : public traits<PlainObjectType> +{ + typedef traits<PlainObjectType> BaseTraits; + typedef typename BaseTraits::Scalar Scalar; + typedef typename BaseTraits::StorageKind StorageKind; + typedef typename BaseTraits::Index Index; + static const int NumDimensions = BaseTraits::NumDimensions; + static const int Layout = BaseTraits::Layout; + enum { + Options = Options_, + Flags = (BaseTraits::Flags & ~AlignedBit) | (Options&Aligned ? AlignedBit : 0), + }; +}; + +template<typename PlainObjectType> +struct traits<TensorRef<PlainObjectType> > + : public traits<PlainObjectType> +{ + typedef traits<PlainObjectType> BaseTraits; + typedef typename BaseTraits::Scalar Scalar; + typedef typename BaseTraits::StorageKind StorageKind; + typedef typename BaseTraits::Index Index; + static const int NumDimensions = BaseTraits::NumDimensions; + static const int Layout = BaseTraits::Layout; + enum { + Options = BaseTraits::Options, + Flags = (BaseTraits::Flags & ~AlignedBit) | (Options&Aligned ? AlignedBit : 0), + }; +}; + + +template<typename _Scalar, std::size_t NumIndices_, int Options, typename IndexType_> +struct eval<Tensor<_Scalar, NumIndices_, Options, IndexType_>, Eigen::Dense> +{ + typedef const Tensor<_Scalar, NumIndices_, Options, IndexType_>& type; +}; + +template<typename _Scalar, std::size_t NumIndices_, int Options, typename IndexType_> +struct eval<const Tensor<_Scalar, NumIndices_, Options, IndexType_>, Eigen::Dense> +{ + typedef const Tensor<_Scalar, NumIndices_, Options, IndexType_>& type; +}; + +template<typename Scalar_, typename Dimensions, int Options, typename IndexType_> +struct eval<TensorFixedSize<Scalar_, Dimensions, Options, IndexType_>, Eigen::Dense> +{ + typedef const TensorFixedSize<Scalar_, Dimensions, Options, IndexType_>& type; +}; + +template<typename Scalar_, typename Dimensions, int Options, typename IndexType_> +struct eval<const TensorFixedSize<Scalar_, Dimensions, Options, IndexType_>, Eigen::Dense> +{ + typedef const TensorFixedSize<Scalar_, Dimensions, Options, IndexType_>& type; +}; + +template<typename Scalar_, int Options, typename IndexType_> +struct eval<TensorVarDim<Scalar_, Options, IndexType_>, Eigen::Dense> +{ + typedef const TensorVarDim<Scalar_, Options, IndexType_>& type; +}; + +template<typename Scalar_, int Options, typename IndexType_> +struct eval<const TensorVarDim<Scalar_, Options, IndexType_>, Eigen::Dense> +{ + typedef const TensorVarDim<Scalar_, Options, IndexType_>& type; +}; + +template<typename PlainObjectType, int Options> +struct eval<TensorMap<PlainObjectType, Options>, Eigen::Dense> +{ + typedef const TensorMap<PlainObjectType, Options>& type; +}; + +template<typename PlainObjectType, int Options> +struct eval<const TensorMap<PlainObjectType, Options>, Eigen::Dense> +{ + typedef const TensorMap<PlainObjectType, Options>& type; +}; + +template<typename PlainObjectType> +struct eval<TensorRef<PlainObjectType>, Eigen::Dense> +{ + typedef const TensorRef<PlainObjectType>& type; +}; + +template<typename PlainObjectType> +struct eval<const TensorRef<PlainObjectType>, Eigen::Dense> +{ + typedef const TensorRef<PlainObjectType>& type; +}; + + +template <typename Scalar_, std::size_t NumIndices_, int Options_, typename IndexType_> +struct nested<Tensor<Scalar_, NumIndices_, Options_, IndexType_>, 1, typename eval<Tensor<Scalar_, NumIndices_, Options_, IndexType_> >::type> +{ + typedef const Tensor<Scalar_, NumIndices_, Options_, IndexType_>& type; +}; + +template <typename Scalar_, std::size_t NumIndices_, int Options_, typename IndexType_> +struct nested<const Tensor<Scalar_, NumIndices_, Options_, IndexType_>, 1, typename eval<const Tensor<Scalar_, NumIndices_, Options_, IndexType_> >::type> +{ + typedef const Tensor<Scalar_, NumIndices_, Options_, IndexType_>& type; +}; + +template <typename Scalar_, typename Dimensions, int Options, typename IndexType_> +struct nested<TensorFixedSize<Scalar_, Dimensions, Options, IndexType_>, 1, typename eval<TensorFixedSize<Scalar_, Dimensions, Options, IndexType_> >::type> +{ + typedef const TensorFixedSize<Scalar_, Dimensions, Options, IndexType_>& type; +}; + +template <typename Scalar_, typename Dimensions, int Options, typename IndexType_> +struct nested<const TensorFixedSize<Scalar_, Dimensions, Options, IndexType_>, 1, typename eval<const TensorFixedSize<Scalar_, Dimensions, Options, IndexType_> >::type> +{ + typedef const TensorFixedSize<Scalar_, Dimensions, Options, IndexType_>& type; +}; + +template <typename Scalar_, int Options> +struct nested<TensorVarDim<Scalar_, Options>, 1, typename eval<TensorVarDim<Scalar_, Options> >::type> +{ + typedef const TensorVarDim<Scalar_, Options>& type; +}; + +template <typename Scalar_, int Options> +struct nested<const TensorVarDim<Scalar_, Options>, 1, typename eval<const TensorVarDim<Scalar_, Options> >::type> +{ + typedef const TensorVarDim<Scalar_, Options>& type; +}; + + +template <typename PlainObjectType, int Options> +struct nested<TensorMap<PlainObjectType, Options>, 1, typename eval<TensorMap<PlainObjectType, Options> >::type> +{ + typedef const TensorMap<PlainObjectType, Options>& type; +}; + +template <typename PlainObjectType, int Options> +struct nested<const TensorMap<PlainObjectType, Options>, 1, typename eval<TensorMap<PlainObjectType, Options> >::type> +{ + typedef const TensorMap<PlainObjectType, Options>& type; +}; + +template <typename PlainObjectType> +struct nested<TensorRef<PlainObjectType>, 1, typename eval<TensorRef<PlainObjectType> >::type> +{ + typedef const TensorRef<PlainObjectType>& type; +}; + +template <typename PlainObjectType> +struct nested<const TensorRef<PlainObjectType>, 1, typename eval<TensorRef<PlainObjectType> >::type> +{ + typedef const TensorRef<PlainObjectType>& type; +}; + +} // end namespace internal + +// Convolutional layers take in an input tensor of shape (D, R, C, B), or (D, C, +// R, B), and convolve it with a set of filters, which can also be presented as +// a tensor (D, K, K, M), where M is the number of filters, K is the filter +// size, and each 3-dimensional tensor of size (D, K, K) is a filter. For +// simplicity we assume that we always use square filters (which is usually the +// case in images), hence the two Ks in the tensor dimension. It also takes in +// a few additional parameters: +// Stride (S): The convolution stride is the offset between locations where we +// apply the filters. A larger stride means that the output will be +// spatially smaller. +// Padding (P): The padding we apply to the input tensor along the R and C +// dimensions. This is usually used to make sure that the spatial +// dimensions of the output matches our intention. +// +// Two types of padding are often used: +// SAME: The pad value is computed so that the output will have size +// R/S and C/S. +// VALID: no padding is carried out. +// When we do padding, the padded values at the padded locations are usually +// zero. +// +// The output dimensions for convolution, when given all the parameters above, +// are as follows: +// When Padding = SAME: the output size is (B, R', C', M), where +// R' = ceil(float(R) / float(S)) +// C' = ceil(float(C) / float(S)) +// where ceil is the ceiling function. The input tensor is padded with 0 as +// needed. The number of padded rows and columns are computed as: +// Pr = ((R' - 1) * S + K - R) / 2 +// Pc = ((C' - 1) * S + K - C) / 2 +// when the stride is 1, we have the simplified case R'=R, C'=C, Pr=Pc=(K-1)/2. +// This is where SAME comes from - the output has the same size as the input has. +// When Padding = VALID: the output size is computed as +// R' = ceil(float(R - K + 1) / float(S)) +// C' = ceil(float(C - K + 1) / float(S)) +// and the number of padded rows and columns are computed in the same way as in +// the SAME case. +// When the stride is 1, we have the simplified case R'=R-K+1, C'=C-K+1, Pr=0, +// Pc=0. +typedef enum { + PADDING_VALID = 1, + PADDING_SAME = 2, +} PaddingType; + +} // end namespace Eigen + +#endif // EIGEN_CXX11_TENSOR_TENSOR_TRAITS_H |