{"html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fhtn20190109.hatenablog.com%2Fentry%2F2025%2F10%2F19%2F000243\" title=\"Neural Networks - 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>","published":"2025-10-19 00:02:43","height":"190","type":"rich","author_url":"https://blog.hatena.ne.jp/HTN20190109/","image_url":null,"blog_title":"HTN20190109\u306e\u65e5\u8a18","provider_url":"https://hatena.blog","title":"Neural Networks","provider_name":"Hatena Blog","author_name":"HTN20190109","width":"100%","version":"1.0","description":"https://docs.pytorch.org/tutorials/beginner/blitz/neural_networks_tutorial.html python3.11 import torchimport torch.nn as nnimport torch.nn.functional as Fimport torch.optim as optim class Net(nn.Module): def __init__(self): super(Net, self).__init__() # 1 input image channel, 6 output channels, 5x5\u2026","blog_url":"https://htn20190109.hatenablog.com/","categories":["DL"],"url":"https://htn20190109.hatenablog.com/entry/2025/10/19/000243"}