看扩散模型中的Noise Scheduler - 知乎 (zhihu.com)这篇文章中的这一段可以理解, noise_schedule可以理解为 αt ,这个是训练前固定好的参数,它的值原本在DDPM中是linear的,到了iddpm中提出了cosine的方式。 提出的动机 启发来自于图4,在linear调度下减小20%(即0.2)的步长相比于减少10%也没有太大影响。 而co...
= 0.05seed = 1378mixed_precision = "bf16"xformers = truelowram = falsecache_latents = truecache_latents_to_disk = truepersistent_data_loader_workers = truelr_scheduler_num_cycles = 3optimizer_args = [ "decouple=True", "weight_decay=0.01", "use_bias_correction=True", "d_coef=2.0"...