Reference¶ dnadiffusion¶ dnadiffusion.utils.train_util ¶ data¶ dnadiffusion.data.dataloader ¶ SequenceDataset ¶ Bases: Dataset __getitem__(index) ¶ Generates one sample of data __init__(seqs, c, transform=T.Compose([T.ToTensor()])) ¶ Initialization __len__() ¶ Denotes the total number of samples models¶ dnadiffusion.models.layers ¶ LearnedSinusoidalPosEmb ¶ Bases: Module following @crowsonkb 's lead with learned sinusoidal pos emb ResBlock ¶ Bases: Module Iniialize a residual block with two convolutions followed by batchnorm layers dnadiffusion.models.diffusion ¶ dnadiffusion.models.unet ¶ LearnedSinusoidalPosEmb ¶ Bases: Module following @crowsonkb 's lead with learned sinusoidal pos emb ResBlock ¶ Bases: Module Iniialize a residual block with two convolutions followed by batchnorm layers