{"width":"100%","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fhtn20190109.hatenablog.com%2Fentry%2F2026%2F10%2F18%2F111401\" title=\"DDIM\u306e\u5b9f\u88c5 - HTN20190109\u306e\u65e5\u8a18\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","blog_url":"https://htn20190109.hatenablog.com/","author_url":"https://blog.hatena.ne.jp/HTN20190109/","image_url":null,"categories":["DL"],"height":"190","version":"1.0","author_name":"HTN20190109","blog_title":"HTN20190109\u306e\u65e5\u8a18","description":"import math import matplotlib.pyplot as pltimport torchimport torch.nn as nnimport torch.nn.functional as Fimport torchvisionimport torchvision.transforms as transforms from torch.utils.data import DataLoader class SinusoidalTimeEmbedding(nn.Module): def __init__(self, dim): super().__init__() self.\u2026","type":"rich","published":"2026-10-18 11:14:01","url":"https://htn20190109.hatenablog.com/entry/2026/10/18/111401","provider_name":"Hatena Blog","provider_url":"https://hatena.blog","title":"DDIM\u306e\u5b9f\u88c5"}