{"author_url":"https://blog.hatena.ne.jp/HTN20190109/","title":"Mixup","categories":["DL"],"published":"2025-11-29 17:17:24","blog_url":"https://htn20190109.hatenablog.com/","image_url":null,"provider_name":"Hatena Blog","blog_title":"HTN20190109\u306e\u65e5\u8a18","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fhtn20190109.hatenablog.com%2Fentry%2F2025%2F11%2F29%2F171724\" title=\"Mixup - 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>","url":"https://htn20190109.hatenablog.com/entry/2025/11/29/171724","description":"import torchimport numpy as npfrom torchvision import datasets, transformsfrom torch.utils.data import DataLoaderimport matplotlib.pyplot as plt # --- Mixup\u95a2\u6570 ---def mixup(X, y, alpha=0.9, num_classes=10): \"\"\"Mixup\u30c7\u30fc\u30bf\u62e1\u5f35\"\"\" batch_size = X.size(0) indices = torch.randperm(batch_size) lam = np.random.b\u2026","author_name":"HTN20190109","height":"190","type":"rich","width":"100%","version":"1.0","provider_url":"https://hatena.blog"}