{"url":"https://htn20190109.hatenablog.com/entry/2026/10/04/113429","blog_url":"https://htn20190109.hatenablog.com/","image_url":null,"type":"rich","author_url":"https://blog.hatena.ne.jp/HTN20190109/","author_name":"HTN20190109","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fhtn20190109.hatenablog.com%2Fentry%2F2026%2F10%2F04%2F113429\" title=\"MobileNet\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>","version":"1.0","width":"100%","height":"190","published":"2026-10-04 11:34:29","blog_title":"HTN20190109\u306e\u65e5\u8a18","provider_name":"Hatena Blog","provider_url":"https://hatena.blog","description":"https://qiita.com/tanaka_benkyo/items/37aadc03c4cee2e55c9e import torchimport torch.nn as nnimport torch.optim as optimimport torchvisionimport torchvision.transforms as transformsimport matplotlib.pyplot as plt class DepthwiseSeparableConv( nn.Module ): def __init__( self, in_channels, out_channels\u2026","categories":["DL"],"title":"MobileNet\u306e\u5b9f\u88c5"}