Template Struct ConvFuncOptions

• Defined in File conv.h

Struct Documentation

template<size_t D>
struct ConvFuncOptions

Options for a D-dimensional convolution functional.

Public Types

using padding_t = torch::nn::detail::conv_padding_t<D>

Public Functions

inline auto bias(const torch::Tensor &new_bias) -> decltype(*this)

optional bias of shape (out_channels). Default: None

inline auto bias(torch::Tensor &&new_bias) -> decltype(*this)

inline const torch::Tensor &bias() const noexcept

inline torch::Tensor &bias() noexcept

inline auto stride(const ExpandingArray<D> &new_stride) -> decltype(*this)

The stride of the convolving kernel.

For a D-dim convolution, must be a single number or a list of D numbers.

inline auto stride(ExpandingArray<D> &&new_stride) -> decltype(*this)

inline const ExpandingArray<D> &stride() const noexcept

inline ExpandingArray<D> &stride() noexcept

inline auto padding(const padding_t &new_padding) -> decltype(*this)

Implicit paddings on both sides of the input.

For a D-dim convolution, must be a single number or a list of D numbers.

inline auto padding(padding_t &&new_padding) -> decltype(*this)

inline const padding_t &padding() const noexcept

inline padding_t &padding() noexcept

inline decltype(auto) padding(std::initializer_list<int64_t> il)

inline auto dilation(const ExpandingArray<D> &new_dilation) -> decltype(*this)

The spacing between kernel elements.

For a D-dim convolution, must be a single number or a list of D numbers.

inline auto dilation(ExpandingArray<D> &&new_dilation) -> decltype(*this)

inline const ExpandingArray<D> &dilation() const noexcept

inline ExpandingArray<D> &dilation() noexcept

inline auto groups(const int64_t &new_groups) -> decltype(*this)

Split input into groups, in_channels should be divisible by the number of groups.

inline auto groups(int64_t &&new_groups) -> decltype(*this)

inline const int64_t &groups() const noexcept

inline int64_t &groups() noexcept