Class ConvTranspose3dImpl#
Defined in File conv.h
Page Contents
Inheritance Relationships#
Base Type#
public torch::nn::ConvTransposeNdImpl< 3, ConvTranspose3dImpl >(Template Class ConvTransposeNdImpl)
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::ConvTranspose3dOptionsclass 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_ARGSmacro.
- 
inline virtual unsigned int _forward_num_required_args() override#
 
Friends
- friend struct torch::nn::AnyModuleHolder
 
- 
inline ConvTranspose3dImpl(int64_t input_channels, int64_t output_channels, ExpandingArray<3> kernel_size)#