LazyConvTranspose1d

class torch.nn.LazyConvTranspose1d(out_channels, kernel_size, stride=1, padding=0, output_padding=0, groups=1, bias=True, dilation=1, padding_mode='zeros') [source]

A torch.nn.ConvTranspose1d module with lazy initialization of the in_channels argument of the ConvTranspose1d that is inferred from the input.size(1).

Parameters
  • out_channels (int) – Number of channels produced by the convolution
  • kernel_size (int or tuple) – Size of the convolving kernel
  • stride (int or tuple, optional) – Stride of the convolution. Default: 1
  • padding (int or tuple, optional) – dilation * (kernel_size - 1) - padding zero-padding will be added to both sides of the input. Default: 0
  • output_padding (int or tuple, optional) – Additional size added to one side of the output shape. Default: 0
  • groups (int, optional) – Number of blocked connections from input channels to output channels. Default: 1
  • bias (bool, optional) – If True, adds a learnable bias to the output. Default: True
  • dilation (int or tuple, optional) – Spacing between kernel elements. Default: 1
cls_to_become

alias of ConvTranspose1d

© 2019 Torch Contributors
Licensed under the 3-clause BSD License.
https://pytorch.org/docs/1.8.0/generated/torch.nn.LazyConvTranspose1d.html