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Class ConvTranspose3dImpl#

Inheritance Relationships#

Base Type#

Class Documentation#

class ConvTranspose3dImpl : public torch::nn::ConvTransposeNdImpl<3, ConvTranspose3dImpl>#

Applies the ConvTranspose3d function.

See https://pytorch.org/docs/main/nn.html#torch.nn.ConvTranspose3d to learn about the exact behavior of this module.

See the documentation for torch::nn::ConvTranspose3dOptions class to learn what constructor arguments are supported for this module.

Example:

ConvTranspose3d model(ConvTranspose3dOptions(2, 2,
2).stride(1).bias(false));

Public Functions

inline ConvTranspose3dImpl(int64_t input_channels, int64_t output_channels, ExpandingArray<3> kernel_size)#
explicit ConvTranspose3dImpl(ConvTranspose3dOptions options_)#
Tensor forward(const Tensor &input, const std::optional<at::IntArrayRef> &output_size = std::nullopt)#

Protected Functions

inline virtual bool _forward_has_default_args() override#

The following three functions allow a module with default arguments in its forward method to be used in a Sequential module.

You should NEVER override these functions manually. Instead, you should use the FORWARD_HAS_DEFAULT_ARGS macro.

inline virtual unsigned int _forward_num_required_args() override#
inline std::vector<torch::nn::AnyValue> _forward_populate_default_args(std::vector<torch::nn::AnyValue> &&arguments) override#

Friends

friend struct torch::nn::AnyModuleHolder