ConvTranspose3d
class torch.ao.nn.quantized.ConvTranspose3d(in_channels, out_channels, kernel_size, stride=1, padding=0, output_padding=0, groups=1, bias=True, dilation=1, padding_mode='zeros', device=None, dtype=None)
Applies a 3D transposed convolution operator over an input image
   composed of several input planes. For details on input arguments,
   parameters, and implementation see "ConvTranspose3d".
Note:
 Currently only the FBGEMM engine is implemented. Please, set the
 *torch.backends.quantized.engine = 'fbgemm'*

For special notes, please, see "Conv3d"
Variables:
      * weight (Tensor) -- packed tensor derived from the
        learnable weight parameter.
  * **scale** (*Tensor*) -- scalar for the output scale

  * **zero_point** (*Tensor*) -- scalar for the output zero point

See "ConvTranspose3d" for other attributes.
Examples:
  >>> torch.backends.quantized.engine = 'fbgemm'
  >>> from torch.nn import quantized as nnq
