AutoGAN¶
-
class
torchelie.models.
AutoGAN
(arch: List[int], n_skip_max: int = 2, in_noise: int = 256, out_ch: int = 3, batchnorm_in_output: bool = False)¶ Experimental: Generator discovered in AutoGAN: Neural Architecture Search for Generative Adversarial Networks.
- Parameters
arch (list) – architecture specification: a list of output channel for each block. Each block doubles the resolution of the generated image. Example: [512, 256, 128, 64, 32].
n_skip_max (int) – how many blocks far back will be used for the skip connections maximum.
in_noise (int) – dimension of the input noise vector
out_ch (int) – number of channels on the image
batchnorm_in_output (bool) – whether to have a batchnorm just before projecting to RGB. I have found it better on False, but the official AutoGAN repo has it.
Warning
AutoGAN() is experimental, and may change or be deleted soon if not already broken
-
blocks
: torch.nn.modules.container.ModuleList¶
-
make_noise
: torch.nn.modules.module.Module¶
-
n_skip_max
: int¶
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to_rgb
: torch.nn.modules.container.Sequential¶