SYMBOL INDEX (27 symbols across 4 files)

FILE: evaluation.py
  function psnr (line 15) | def psnr(x, ref, maxg=2):
  class ImageDataset (line 20) | class ImageDataset(torch.utils.data.Dataset):
    method __init__ (line 21) | def __init__(self, path, size):
    method __len__ (line 39) | def __len__(self):
    method __getitem__ (line 42) | def __getitem__(self, index):
  function collate_fn (line 49) | def collate_fn(images):

FILE: latent_resizer.py
  function normalization (line 8) | def normalization(channels):
  function zero_module (line 12) | def zero_module(module):
  class AttnBlock (line 18) | class AttnBlock(nn.Module):
    method __init__ (line 19) | def __init__(self, in_channels):
    method attention (line 31) | def attention(self, h_: torch.Tensor) -> torch.Tensor:
    method forward (line 47) | def forward(self, x, **kwargs):
  function make_attn (line 54) | def make_attn(in_channels, attn_kwargs=None):
  class ResBlockEmb (line 58) | class ResBlockEmb(nn.Module):
    method __init__ (line 59) | def __init__(
    method forward (line 129) | def forward(self, x, emb):
  class LatentResizer (line 151) | class LatentResizer(nn.Module):
    method __init__ (line 152) | def __init__(self, in_blocks=10, out_blocks=10, channels=128, dropout=...
    method load_model (line 180) | def load_model(cls, filename, device="cpu", dtype=torch.float32, dropo...
    method forward (line 214) | def forward(self, x, scale=None, size=None):

FILE: latent_resizer_train.py
  function init_dataset (line 22) | def init_dataset(dataset_path, size=512):
  function collate_fn (line 68) | def collate_fn(examples):
  function calculate_loss (line 92) | def calculate_loss(

FILE: nn_upscale.py
  class NNLatentUpscale (line 7) | class NNLatentUpscale:
    method __init__ (line 12) | def __init__(self):
    method INPUT_TYPES (line 25) | def INPUT_TYPES(s):
    method upscale (line 49) | def upscale(self, latent, version, upscale):