class_docstr: From https://github.com/toshas/torch-fidelity/blob/master/examples/sngan_cifar10.py.
class_docstr_tok: ["From","https",":","\/\/github.com\/toshas\/torch-fidelity\/blob\/master\/examples\/sngan_cifar10.py","."]
code: def __init__(self, z_size) -> None:
      super().__init__()
      self.z_size = z_size
      self.model = torch.nn.Sequential(
          torch.nn.ConvTranspose2d(z_size, 512, 4, stride=1),
          torch.nn.BatchNorm2d(512),
          torch.nn.ReLU(),
          torch.nn.ConvTranspose2d(
              512, 256, 4, stride=2, padding=(1, 1)
          ),
          torch.nn.BatchNorm2d(256),
          torch.nn.ReLU(),
          torch.nn.ConvTranspose2d(
              256, 128, 4, stride=2, padding=(1, 1)
          ),
          torch.nn.BatchNorm2d(128),
          torch.nn.ReLU(),
          torch.nn.ConvTranspose2d(
              128, 64, 4, stride=2, padding=(1, 1)
          ),
          torch.nn.BatchNorm2d(64),
          torch.nn.ReLU(),
          torch.nn.ConvTranspose2d(64, 3, 3, stride=1, padding=(1, 1)),
          torch.nn.Tanh(),
      )
  
imports: from operator import attrgetter
  import pytest
  import torch
  import torch_fidelity
  from torch import nn
  from torch_fidelity.sample_similarity_lpips import SampleSimilarityLPIPS
  from torch_fidelity.utils import batch_interp
  from torchmetrics.functional.image.lpips import _LPIPS
  from torchmetrics.functional.image.perceptual_path_length import _interpolate, perceptual_path_length
  from torchmetrics.image.perceptual_path_length import PerceptualPathLength
  from torchmetrics.utilities.imports import _TORCH_FIDELITY_AVAILABLE
  from unittests import skip_on_running_out_of_memory
  from unittests.helpers import seed_all
label_desc: Use image node_id 1 to create a new DummyGenerator object from inherited base classes: torch.nn with example: obj = DummyGenerator(z_size)