{"author_name":"HTN20190109","type":"rich","title":"GoogLeNet\u306e\u5b9f\u88c5","version":"1.0","provider_url":"https://hatena.blog","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fhtn20190109.hatenablog.com%2Fentry%2F2026%2F10%2F13%2F210457\" title=\"GoogLeNet\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>","height":"190","published":"2026-10-13 21:04:57","image_url":null,"categories":["DL"],"blog_url":"https://htn20190109.hatenablog.com/","blog_title":"HTN20190109\u306e\u65e5\u8a18","description":"https://pystyle.info/pytorch-googlenet/ import random import matplotlib.pyplot as pltimport torchimport torch.nn as nnimport torch.nn.functional as Fimport torchvisionimport torchvision.transforms as transforms device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\") batch_size = 128epo\u2026","width":"100%","author_url":"https://blog.hatena.ne.jp/HTN20190109/","url":"https://htn20190109.hatenablog.com/entry/2026/10/13/210457","provider_name":"Hatena Blog"}