\u6269\u6563\u6a21\u578b\u5df2\u6210\u4e3a\u751f\u6210\u5f0f\u4eba\u5de5\u667a\u80fd\u7684\u4e00\u79cd\u5f3a\u5927\u65b9\u6cd5\uff0c\u5728\u56fe\u50cf\u3001\u97f3\u9891\u548c\u89c6\u9891\u751f\u6210\u65b9\u9762\u53d6\u5f97\u4e86\u6700\u5148\u8fdb\u7684\u6210\u679c\u3002\u5728\u8fd9\u7bc7\u6df1\u5165\u6d45\u51fa\u7684\u6280\u672f\u6587\u7ae0\u4e2d\uff0c\u6211\u4eec\u5c06\u63a2\u8ba8\u6269\u6563\u6a21\u5f0f\u7684\u5de5\u4f5c\u539f\u7406\u3001\u4e3b\u8981\u521b\u65b0\u70b9\u4ee5\u53ca\u5b83\u4eec\u5982\u6b64\u6210\u529f\u7684\u539f\u56e0\u3002\u6211\u4eec\u5c06\u4ecb\u7ecd\u8fd9\u9879\u4ee4\u4eba\u5174\u594b\u7684\u65b0\u6280\u672f\u7684\u6570\u5b66\u57fa\u7840\u3001\u8bad\u7ec3\u8fc7\u7a0b\u3001\u91c7\u6837\u7b97\u6cd5\u548c\u524d\u6cbf\u5e94\u7528\u3002<\/p>\n

\u6269\u6563\u6a21\u578b\u7b80\u4ecb<\/h2>\n
\u6269\u6563\u6a21\u578b\u662f\u4e00\u7c7b\u751f\u6210\u6a21\u578b\uff0c\u5b83\u901a\u8fc7\u9006\u8f6c\u6269\u6563\u8fc7\u7a0b\u6765\u5b66\u4e60\u9010\u6b65\u53bb\u566a\u6570\u636e\u3002\u5176\u6838\u5fc3\u7406\u5ff5\u662f\u4ece\u7eaf\u566a\u58f0\u5f00\u59cb\uff0c\u7136\u540e\u8fed\u4ee3\u5c06\u5176\u7ec6\u5316\u4e3a\u76ee\u6807\u5206\u5e03\u7684\u9ad8\u8d28\u91cf\u6837\u672c\u3002<\/p>\n
\u8fd9\u79cd\u65b9\u6cd5\u53d7\u5230\u975e\u5e73\u8861\u70ed\u529b\u5b66\u7684\u542f\u53d1–\u7279\u522b\u662f\u9006\u8f6c\u6269\u6563\u4ee5\u6062\u590d\u7ed3\u6784\u7684\u8fc7\u7a0b\u3002\u5728\u673a\u5668\u5b66\u4e60\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u628a\u5b83\u770b\u4f5c\u662f\u5b66\u4f1a\u9006\u8f6c\u6570\u636e\u4e2d\u9010\u6e10\u589e\u52a0\u7684\u566a\u97f3\u3002<\/p>\n
\u6269\u6563\u6a21\u578b\u7684\u4e00\u4e9b\u4e3b\u8981\u4f18\u52bf\u5305\u62ec<\/p>\n
\n
\u6700\u5148\u8fdb\u7684\u56fe\u50cf\u8d28\u91cf\uff0c\u5728\u8bb8\u591a\u60c5\u51b5\u4e0b\u90fd\u8d85\u8d8a\u4e86\u5e7f\u57df\u7f51\u7edc<\/li>\n
\u65e0\u5bf9\u6297\u52a8\u6001\u7684\u7a33\u5b9a\u8bad\u7ec3<\/li>\n
\u9ad8\u5ea6\u5e76\u884c\u5316<\/li>\n
\u7075\u6d3b\u7684\u67b6\u6784–\u53ef\u4f7f\u7528\u4efb\u4f55\u5c06\u8f93\u5165\u6620\u5c04\u5230\u76f8\u540c\u7ef4\u5ea6\u8f93\u51fa\u7684\u6a21\u578b<\/li>\n
\u575a\u5b9e\u7684\u7406\u8bba\u57fa\u7840<\/li>\n<\/ul>\n
\u8ba9\u6211\u4eec\u6df1\u5165\u4e86\u89e3\u6269\u6563\u6a21\u578b\u7684\u5de5\u4f5c\u539f\u7406\u3002<\/p>\n
$\"\u6765\u6e90\uff1aSong$ <\/a><\/p>\n
(\u8d44\u6599\u6765\u6e90<\/a>)Song et al.<\/a><\/p>\n<\/div>\n
\u968f\u673a\u5fae\u5206\u65b9\u7a0b\u63a7\u5236\u7740\u6269\u6563\u6a21\u578b\u4e2d\u7684\u6b63\u5411\u548c\u53cd\u5411\u8fc7\u7a0b\u3002\u524d\u5411 SDE \u5728\u6570\u636e\u4e2d\u52a0\u5165\u566a\u58f0\uff0c\u9010\u6e10\u5c06\u6570\u636e\u8f6c\u5316\u4e3a\u566a\u58f0\u5206\u5e03\u3002\u53cd\u5411 SDE \u4ee5\u5b66\u4e60\u5230\u7684\u5206\u6570\u51fd\u6570\u4e3a\u6307\u5bfc\uff0c\u9010\u6b65\u53bb\u9664\u566a\u58f0\uff0c\u4ece\u800c\u4ece\u968f\u673a\u566a\u58f0\u4e2d\u751f\u6210\u903c\u771f\u7684\u56fe\u50cf\u3002\u8fd9\u79cd\u65b9\u6cd5\u662f\u5728\u8fde\u7eed\u72b6\u6001\u7a7a\u95f4\u4e2d\u5b9e\u73b0\u9ad8\u8d28\u91cf\u751f\u6210\u6027\u80fd\u7684\u5173\u952e<\/p>\n
\u524d\u5411\u6269\u6563\u8fc7\u7a0b<\/h2>\n
\u524d\u5411\u6269\u6563\u8fc7\u7a0b\u4ece\u4ece\u771f\u5b9e\u6570\u636e\u5206\u5e03\u4e2d\u91c7\u6837\u7684\u6570\u636e\u70b9 x\u2080 \u5f00\u59cb\uff0c\u5728 T \u4e2a\u65f6\u95f4\u6b65\u4e2d\u9010\u6e10\u6dfb\u52a0\u9ad8\u65af\u566a\u58f0\uff0c\u4ea7\u751f\u566a\u58f0\u8d8a\u6765\u8d8a\u5927\u7684\u7248\u672c x\u2081\u3001x\u2082\u3001…\u3001xT\u3002<\/p>\n
\u5728\u6bcf\u4e2a\u65f6\u95f4\u6b65 t\uff0c\u6211\u4eec\u90fd\u4f1a\u6839\u636e\u4ee5\u4e0b\u539f\u5219\u6dfb\u52a0\u5c11\u91cf\u566a\u58f0\uff1a<\/p>\n
`x_t = \u221a(1 - \u03b2_t) * x_{t-1} + \u221a(\u03b2_t) * \u03b5<\/code><\/p>\n`
`\u5728\u54ea\u91cc\uff1f<\/p>\n`
`\n\u03b2_t \u662f\u4e00\u4e2a\u65b9\u5dee\u8868\uff0c\u7528\u4e8e\u63a7\u5236\u6bcf\u4e00\u6b65\u7684\u566a\u58f0\u6dfb\u52a0\u91cf<\/li>\n`
\u03b5\u4e3a\u968f\u673a\u9ad8\u65af\u566a\u58f0<\/li>\n<\/ul>\n
\u8fd9\u4e00\u8fc7\u7a0b\u4e00\u76f4\u6301\u7eed\u5230 xT \u63a5\u8fd1\u7eaf\u9ad8\u65af\u566a\u58f0\u4e3a\u6b62\u3002<\/p>\n
\u5728\u6570\u5b66\u4e0a\uff0c\u6211\u4eec\u53ef\u4ee5\u5c06\u5176\u63cf\u8ff0\u4e3a\u9a6c\u5c14\u79d1\u592b\u94fe\uff1a<\/p>\n
`q(x_t | x_{t-1}) = N(x_t; \u221a(1 - \u03b2_t) * x_{t-1}, \u03b2_t * I)<\/code><\/p>\n`
`\u5176\u4e2d\uff0cN \u8868\u793a\u9ad8\u65af\u5206\u5e03\u3002<\/p>\n`
`\u03b2_t \u8ba1\u5212\u901a\u5e38\u9009\u62e9\u5728\u65e9\u671f\u65f6\u95f4\u6b65\u8f83\u5c0f\uff0c\u968f\u7740\u65f6\u95f4\u63a8\u79fb\u9010\u6e10\u589e\u5927\u3002\u5e38\u89c1\u7684\u9009\u62e9\u5305\u62ec\u7ebf\u6027\u3001\u4f59\u5f26\u6216\u6b63\u4f59\u5f26\u3002<\/p>\n`
\u53cd\u5411\u6269\u6563\u8fc7\u7a0b<\/h2>\n\u6269\u6563\u6a21\u578b\u7684\u76ee\u6807\u662f\u5b66\u4e60\u8fd9\u4e00\u8fc7\u7a0b\u7684\u53cd\u5411–\u4ece\u7eaf\u566a\u58f0 xT \u5f00\u59cb\uff0c\u9010\u6b65\u53bb\u566a\uff0c\u4ee5\u6062\u590d\u5e72\u51c0\u7684\u6837\u672c x\u2080\u3002<\/p>\n \u6211\u4eec\u5c06\u8fd9\u4e00\u9006\u5411\u8fc7\u7a0b\u6a21\u62df\u4e3a<\/p>\n p_\u03b8(x_{t-1} | x_t) = N(x_{t-1}; \u03bc_\u03b8(x_t, t), \u03c3_\u03b8^2(x_t, t))<\/code><\/p>\n \u5176\u4e2d\uff0c\u03bc_\u03b8 \u548c \u03c3_\u03b8^2 \u662f\u4ee5 \u03b8 \u4e3a\u53c2\u6570\u7684\u5b66\u4e60\u51fd\u6570\uff08\u901a\u5e38\u662f\u795e\u7ecf\u7f51\u7edc\uff09\u3002<\/p>\n \u5173\u952e\u7684\u521b\u65b0\u4e4b\u5904\u5728\u4e8e\uff0c\u6211\u4eec\u4e0d\u9700\u8981\u660e\u786e\u5efa\u7acb\u5b8c\u6574\u7684\u53cd\u5411\u5206\u5e03\u6a21\u578b\u3002\u76f8\u53cd\uff0c\u6211\u4eec\u53ef\u4ee5\u6839\u636e\u5df2\u77e5\u7684\u524d\u5411\u8fc7\u7a0b\u5bf9\u5176\u8fdb\u884c\u53c2\u6570\u5316\u3002<\/p>\n \u5177\u4f53\u6765\u8bf4\uff0c\u6211\u4eec\u53ef\u4ee5\u8bc1\u660e\u6700\u4f18\u53cd\u5411\u8fc7\u7a0b\u5747\u503c \u03bc* \u662f\uff1a<\/p>\n \u03bc* = 1\/\u221a(1 - \u03b2_t) * (x_t - \u03b2_t\/\u221a(1 - \u03b1_t) * \u03b5_\u03b8(x_t, t))<\/code><\/p>\n \u5728\u54ea\u91cc\uff1f<\/p>\n
`\n\u03b1_t = 1 \u2013 \u03b2_t<\/li>\n`\u03b5_\u03b8\u662f\u5b66\u4e60\u5230\u7684\u566a\u58f0\u9884\u6d4b\u7f51\u7edc<\/li>\n<\/ul>\n\u8fd9\u6837\uff0c\u6211\u4eec\u5c31\u6709\u4e86\u4e00\u4e2a\u7b80\u5355\u7684\u76ee\u6807–\u8bad\u7ec3\u795e\u7ecf\u7f51\u7edc \u03b5_\u03b8\uff0c\u4ee5\u9884\u6d4b\u6bcf\u4e00\u6b65\u6240\u6dfb\u52a0\u7684\u566a\u58f0\u3002<\/p>\n\u57f9\u8bad\u76ee\u6807<\/h2>\n\u6269\u6563\u6a21\u578b\u7684\u8bad\u7ec3\u76ee\u6807\u53ef\u4ee5\u901a\u8fc7\u53d8\u5206\u63a8\u7406\u5f97\u51fa\u3002\u7ecf\u8fc7\u7b80\u5316\uff0c\u6211\u4eec\u5f97\u5230\u4e86\u4e00\u4e2a\u7b80\u5355\u7684 L2 \u635f\u5931\uff1a<\/p>\n L = E_t,x\u2080,\u03b5 [ ||\u03b5 - \u03b5_\u03b8(x_t, t)||\u00b2 ]<\/code><\/p>\n \u5728\u54ea\u91cc\uff1f<\/p>\n\nt \u4ece 1 \u5230 T \u4e2d\u5747\u5300\u91c7\u6837<\/li>\n x\u2080 \u4ece\u8bad\u7ec3\u6570\u636e\u4e2d\u91c7\u6837<\/li>\n \u03b5\u4e3a\u91c7\u6837\u9ad8\u65af\u566a\u58f0<\/li>\nx_t \u662f\u6839\u636e\u524d\u5411\u8fc7\u7a0b\u5411 x\u2080 \u4e2d\u6dfb\u52a0\u566a\u58f0\u800c\u751f\u6210\u7684<\/li>\n<\/ul>\n\u6362\u53e5\u8bdd\u8bf4\uff0c\u6211\u4eec\u6b63\u5728\u8bad\u7ec3\u6a21\u578b\u6765\u9884\u6d4b\u6bcf\u4e2a\u65f6\u95f4\u6b65\u6dfb\u52a0\u7684\u566a\u58f0\u3002<\/p>\n \u6a21\u578b\u67b6\u6784<\/h2>\n<\/a><\/p>\n(\u8d44\u6599\u6765\u6e90)\u6717\u5185\u4f2f\u683c\u7b49\u4eba<\/a><\/p>\n<\/div>\n U-Net \u67b6\u6784\u662f\u6269\u6563\u6a21\u578b\u4e2d\u53bb\u566a\u6b65\u9aa4\u7684\u6838\u5fc3\u3002\u5b83\u7684\u7f16\u7801\u5668-\u89e3\u7801\u5668\u7ed3\u6784\u5177\u6709\u8df3\u63a5\u529f\u80fd\uff0c\u6709\u52a9\u4e8e\u5728\u91cd\u5efa\u8fc7\u7a0b\u4e2d\u4fdd\u7559\u7ec6\u7c92\u5ea6\u7ec6\u8282\u3002\u7f16\u7801\u5668\u5728\u6355\u6349\u9ad8\u7ea7\u7279\u5f81\u7684\u540c\u65f6\u9010\u6b65\u5bf9\u8f93\u5165\u56fe\u50cf\u8fdb\u884c\u4f4e\u91c7\u6837\uff0c\u89e3\u7801\u5668\u5219\u5bf9\u7f16\u7801\u7279\u5f81\u8fdb\u884c\u9ad8\u91c7\u6837\uff0c\u4ee5\u91cd\u5efa\u56fe\u50cf\u3002\u8fd9\u79cd\u7ed3\u6784\u5bf9\u4e8e\u9700\u8981\u7cbe\u786e\u5b9a\u4f4d\u7684\u4efb\u52a1\uff08\u5982\u56fe\u50cf\u5206\u5272\uff09\u5c24\u5176\u6709\u6548\u3002<\/p>\n \u566a\u58f0\u9884\u6d4b\u7f51\u7edc \u03b5_\u03b8 \u53ef\u4ee5\u4f7f\u7528\u4efb\u4f55\u80fd\u5c06\u8f93\u5165\u6620\u5c04\u5230\u540c\u7ef4\u5ea6\u8f93\u51fa\u7684\u7ed3\u6784\u3002U-Net \u98ce\u683c\u7684\u67b6\u6784\u662f\u4e00\u79cd\u6d41\u884c\u7684\u9009\u62e9\uff0c\u5c24\u5176\u9002\u7528\u4e8e\u56fe\u50cf\u751f\u6210\u4efb\u52a1\u3002<\/p>\n \u5178\u578b\u7684\u67b6\u6784\u53ef\u80fd\u662f\u8fd9\u6837\u7684<\/p>\n class DiffusionUNet(nn.Module)\uff1a\n def init(self):\n super().init()\n \n # \u4e0b\u91c7\u6837\n self.down1 = UNetBlock(3, 64)\n self.down2 = UNetBlock(64, 128)\n self.down3 = UNetBlock(128, 256)\n \n # \u74f6\u9888\n self.bottleneck = UNetBlock(256, 512)\n \n # \u5347\u91c7\u6837 \n self.up3 = UNetBlock(512, 256)\n self.up2 = UNetBlock(256, 128)\n self.up1 = UNetBlock(128, 64)\n \n # \u8f93\u51fa\n self.out = nn.Conv2d(64, 3, 1)\n \n def forward(self, x, t)\uff1a\n # \u5d4c\u5165\u65f6\u95f4\u6b65\u957f\n t_emb = self.time_embedding(t)\n \n # \u7f29\u5c0f\u6837\u672c\n d1 = self.down1(x, t_emb)\n d2 = self.down2(d1, t_emb)\n d3 = self.down3(d2, t_emb)\n \n # \u74f6\u9888\n bottleneck = self.bottleneck(d3, t_emb)\n \n # \u63d0\u9ad8\u91c7\u6837\u7387\n u3 = self.up3(torch.cat([bottleneck, d3], dim=1), t_emb)\n u2 = self.up2(torch.cat([u3, d2], dim=1), t_emb)\n u1 = self.up1(torch.cat([u2, d1], dim=1), t_emb)\n \n # \u8f93\u51fa\n return self.out(u1)\n<\/pre>\n\n\n\n\n\n\u4e3b\u8981\u5305\u62ec<\/p>\n\n\u5177\u6709\u8df3\u63a5\u529f\u80fd\u7684 U-Net \u67b6\u6784<\/li>\n \u65f6\u95f4\u5d4c\u5165\uff0c\u4ee5\u65f6\u95f4\u6b65\u4e3a\u6761\u4ef6<\/li>\n\u7075\u6d3b\u7684\u6df1\u5ea6\u548c\u5bbd\u5ea6<\/li>\n<\/ul>\n\u91c7\u6837\u7b97\u6cd5<\/h2>\n\u8bad\u7ec3\u597d\u566a\u58f0\u9884\u6d4b\u7f51\u7edc \u03b5_\u03b8 \u540e\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u7528\u5b83\u6765\u751f\u6210\u65b0\u6837\u672c\u3002\u57fa\u672c\u7684\u91c7\u6837\u7b97\u6cd5\u662f<\/p>\n \n\u4ece\u7eaf\u9ad8\u65af\u566a\u58f0 xT \u5f00\u59cb<\/li>\n \u5bf9\u4e8e t = T \u81f3 1\uff1a\n\n\u9884\u6d4b\u566a\u58f0\uff1a\u03b5_\u03b8\uff08x_t\uff0ct\uff09<\/li>\n \u8ba1\u7b97\u5e73\u5747\u503c\uff1a\u03bc = 1\/\u221a(1-\u03b2_t) * (x_t – \u03b2_t\/\u221a(1-\u03b1_t) * \u03b5_\u03b8(x_t, t))<\/li>\n \u6837\u672c\uff1ax_{t-1} ~ N(\u03bc, \u03c3_t^2 * I)<\/li>\n<\/ul>\n<\/li>\n \u8fd4\u56de x\u2080<\/li>\n<\/ol>\n\u5728\u6211\u4eec\u5b66\u4e60\u7684\u566a\u58f0\u9884\u6d4b\u7f51\u7edc\u7684\u5f15\u5bfc\u4e0b\uff0c\u8fd9\u4e00\u8fc7\u7a0b\u4f1a\u9010\u6e10\u5bf9\u6837\u672c\u8fdb\u884c\u53bb\u566a\u5904\u7406\u3002<\/p>\n \u5728\u5b9e\u8df5\u4e2d\uff0c\u6709\u5404\u79cd\u91c7\u6837\u6280\u672f\u53ef\u4ee5\u63d0\u9ad8\u8d28\u91cf\u6216\u901f\u5ea6\uff1a<\/p>\n \nDDIM \u91c7\u6837\uff1a\u53ef\u51cf\u5c11\u91c7\u6837\u6b65\u9aa4\u7684\u786e\u5b9a\u6027\u53d8\u91cf<\/li>\n \u7956\u5148\u91c7\u6837\u7eb3\u5165\u5b66\u4e60\u65b9\u5dee \u03c3_\u03b8^2<\/li>\n \u622a\u65ad\u53d6\u6837\uff1a\u63d0\u524d\u505c\u6b62\uff0c\u52a0\u5feb\u751f\u6210<\/li>\n<\/ul>\n\u4e0b\u9762\u662f\u91c7\u6837\u7b97\u6cd5\u7684\u57fa\u672c\u5b9e\u73b0\uff1a<\/p>\n def sample(model, n_samples, device):\n # \u4ece\u7eaf\u566a\u97f3\u5f00\u59cb\n x = torch.randn(n_samples, 3, 32, 32).to(device)\n \n for t in reversed(range(1000)):\n # \u6dfb\u52a0\u566a\u97f3\u4ee5\u521b\u5efa x_t\n t_batch = torch.full((n_samples,), t, device=device)\n noise = torch.randn_like(x)\n x_t = add_noise(x, noise, t)\n \n # \u9884\u6d4b\u5e76\u6d88\u9664\u566a\u97f3\n pred_noise = model(x_t, t_batch)\n x = remove_noise(x_t, pred_noise, t)\n \n # \u4e3a\u4e0b\u4e00\u6b65\u6dfb\u52a0\u566a\u97f3\uff08t=0 \u65f6\u9664\u5916\uff09\n \u5982\u679c t > 0\uff1a\n noise = torch.randn_like(x)\n x = add_noise(x, noise, t-1)\n \n \u8fd4\u56de x\n<\/pre>\n\n\n\n\u6269\u6563\u6a21\u578b\u80cc\u540e\u7684\u6570\u5b66<\/h2>\n<\/a><\/p>\n \u8981\u771f\u6b63\u7406\u89e3\u6269\u6563\u6a21\u578b\uff0c\u6df1\u5165\u7814\u7a76\u5176\u6570\u5b66\u57fa\u7840\u81f3\u5173\u91cd\u8981\u3002\u8ba9\u6211\u4eec\u6765\u8be6\u7ec6\u63a2\u8ba8\u4e00\u4e9b\u5173\u952e\u6982\u5ff5\uff1a<\/p>\n \u9a6c\u5c14\u53ef\u592b\u94fe\u548c\u968f\u673a\u5fae\u5206\u65b9\u7a0b<\/h3>\n\u6269\u6563\u6a21\u578b\u4e2d\u7684\u524d\u5411\u6269\u6563\u8fc7\u7a0b\u53ef\u4ee5\u770b\u4f5c\u9a6c\u5c14\u53ef\u592b\u94fe\uff0c\u6216\u8005\u5728\u8fde\u7eed\u6781\u9650\u4e2d\u770b\u4f5c\u968f\u673a\u5fae\u5206\u65b9\u7a0b\uff08SDE\uff09\u3002SDE \u516c\u5f0f\u4e3a\u5206\u6790\u548c\u6269\u5c55\u6269\u6563\u6a21\u578b\u63d0\u4f9b\u4e86\u4e00\u4e2a\u5f3a\u5927\u7684\u7406\u8bba\u6846\u67b6\u3002<\/p>\n \u6b63\u5411 SDE \u53ef\u4ee5\u5199\u6210<\/p>\n dx = f(x,t)dt + g(t)dw<\/code><\/p>\n \u5728\u54ea\u91cc\uff1f<\/p>\n\nf(x,t) \u662f\u6f02\u79fb\u9879<\/li>\n g(t) \u662f\u6269\u6563\u7cfb\u6570<\/li>\ndw \u662f\u4e00\u4e2a\u7ef4\u7eb3\u8fc7\u7a0b\uff08\u5e03\u6717\u8fd0\u52a8\uff09<\/li>\n<\/ul>\n\u5bf9 f \u548c g \u7684\u4e0d\u540c\u9009\u62e9\u4f1a\u5bfc\u81f4\u4e0d\u540c\u7c7b\u578b\u7684\u6269\u6563\u8fc7\u7a0b\u3002\u4f8b\u5982\uff1a<\/p>\n\n\u65b9\u5dee\u7206\u70b8 (VE) SDE\uff1adx = \u221a(d\/dt \u03c3\u00b2(t)) dw<\/li>\nVariance Preserving (VP) SDE: dx = -0.5 \u03b2(t)xdt + \u221a(\u03b2(t)) dw<\/code><\/li>\n<\/ul>\n\u4e86\u89e3\u4e86\u8fd9\u4e9b SDE\uff0c\u6211\u4eec\u5c31\u80fd\u63a8\u5bfc\u51fa\u6700\u4f73\u91c7\u6837\u7b56\u7565\uff0c\u5e76\u5c06\u6269\u6563\u6a21\u578b\u6269\u5c55\u5230\u65b0\u7684\u9886\u57df\u3002<\/p>\n \u5f97\u5206\u5339\u914d\u548c\u53bb\u566a\u5f97\u5206\u5339\u914d<\/h3>\n\u6269\u6563\u6a21\u578b\u4e0e\u5206\u6570\u5339\u914d\u4e4b\u95f4\u7684\u8054\u7cfb\u63d0\u4f9b\u4e86\u53e6\u4e00\u4e2a\u6709\u4ef7\u503c\u7684\u89c6\u89d2\u3002\u5f97\u5206\u51fd\u6570\u88ab\u5b9a\u4e49\u4e3a\u5bf9\u6570\u6982\u7387\u5bc6\u5ea6\u7684\u68af\u5ea6\uff1a<\/p>\n s(x) = \u2207x log p(x)<\/code><\/p>\n \u53bb\u566a\u5206\u6570\u5339\u914d\u7684\u76ee\u7684\u662f\u901a\u8fc7\u8bad\u7ec3\u4e00\u4e2a\u6a21\u578b\u6765\u4f30\u8ba1\u8fd9\u4e2a\u5206\u6570\u51fd\u6570\uff0c\u4ece\u800c\u5bf9\u8f7b\u5fae\u6270\u52a8\u7684\u6570\u636e\u70b9\u8fdb\u884c\u53bb\u566a\u3002\u8fd9\u4e00\u76ee\u6807\u7b49\u540c\u4e8e\u8fde\u7eed\u6781\u9650\u7684\u6269\u6563\u6a21\u578b\u8bad\u7ec3\u76ee\u6807\u3002<\/p>\n \u8fd9\u79cd\u8054\u7cfb\u4f7f\u6211\u4eec\u80fd\u591f\u5229\u7528\u57fa\u4e8e\u5206\u6570\u7684\u751f\u6210\u5efa\u6a21\u6280\u672f\uff0c\u5982\u9000\u706b\u6717\u683c\u6587\u52a8\u6001\u91c7\u6837\u6280\u672f\u3002<\/p>\n\u9ad8\u7ea7\u57f9\u8bad\u6280\u672f<\/h2>\n\u91cd\u8981\u6027\u53d6\u6837<\/h3>\n\u6807\u51c6\u6269\u6563\u6a21\u578b\u8bad\u7ec3\u5bf9\u65f6\u95f4\u6b65\u8fdb\u884c\u5747\u5300\u91c7\u6837\u3002\u7136\u800c\uff0c\u5e76\u975e\u6240\u6709\u7684\u65f6\u95f4\u6b65\u9aa4\u5bf9\u5b66\u4e60\u90fd\u540c\u6837\u91cd\u8981\u3002\u91cd\u8981\u5ea6\u62bd\u6837\u6280\u672f\u53ef\u7528\u4e8e\u5c06\u57f9\u8bad\u91cd\u70b9\u653e\u5728\u4fe1\u606f\u91cf\u6700\u5927\u7684\u65f6\u95f4\u6b65\u4e0a\u3002<\/p>\n \u4e00\u79cd\u65b9\u6cd5\u662f\u5728\u65f6\u95f4\u6b65\u4e0a\u4f7f\u7528\u975e\u5747\u5300\u5206\u5e03\uff0c\u5e76\u6839\u636e\u5206\u6570\u7684\u9884\u671f L2 \u51c6\u5219\u8fdb\u884c\u52a0\u6743\uff1a<\/p>\n p(t) \u221d E[||s(x_t, t)||\u00b2]<\/code><\/p>\n \u8fd9\u6837\u53ef\u4ee5\u52a0\u5feb\u57f9\u8bad\u901f\u5ea6\uff0c\u63d0\u9ad8\u6837\u672c\u8d28\u91cf\u3002<\/p>\n\u6e10\u8fdb\u84b8\u998f<\/h3>\n\u6e10\u8fdb\u5f0f\u84b8\u998f\u662f\u4e00\u79cd\u5728\u4e0d\u5f71\u54cd\u8d28\u91cf\u7684\u524d\u63d0\u4e0b\u521b\u5efa\u66f4\u5feb\u91c7\u6837\u6a21\u578b\u7684\u6280\u672f\u3002\u6d41\u7a0b\u5982\u4e0b<\/p>\n\n\u7528\u8bb8\u591a\u65f6\u95f4\u6b65\uff08\u5982 1000 \u6b65\uff09\u8bad\u7ec3\u57fa\u7840\u6269\u6563\u6a21\u578b<\/li>\n \u521b\u5efa\u4e00\u4e2a\u65f6\u95f4\u6b65\u6570\u8f83\u5c11\uff08\u5982 100 \u6b65\uff09\u7684\u5b66\u751f\u6a21\u578b<\/li>\n \u8bad\u7ec3\u5b66\u751f\u5339\u914d\u57fa\u7840\u6a21\u578b\u7684\u53bb\u566a\u8fc7\u7a0b<\/li>\n\u91cd\u590d\u6b65\u9aa4 2-3\uff0c\u9010\u6b65\u7f29\u77ed\u65f6\u95f4\u6b65\u957f<\/li>\n<\/ol>\n\u8fd9\u6837\u5c31\u80fd\u4ee5\u66f4\u5c11\u7684\u53bb\u566a\u6b65\u9aa4\u751f\u6210\u9ad8\u8d28\u91cf\u7684\u56fe\u50cf\u3002<\/p>\n \u5efa\u7b51\u521b\u65b0<\/h2>\n \u57fa\u4e8e\u53d8\u538b\u5668\u7684\u6269\u6563\u6a21\u578b<\/h3>\n\u867d\u7136 U-Net \u67b6\u6784\u5728\u56fe\u50cf\u6269\u6563\u6a21\u578b\u4e2d\u4e00\u76f4\u5f88\u6d41\u884c\uff0c\u4f46\u6700\u8fd1\u7684\u5de5\u4f5c\u4e5f\u5728\u63a2\u7d22\u4f7f\u7528\u53d8\u538b\u5668\u67b6\u6784\u3002\u53d8\u538b\u5668\u5177\u6709\u591a\u79cd\u6f5c\u5728\u4f18\u52bf\uff1a<\/p>\n \n\u66f4\u597d\u5730\u5904\u7406\u8fdc\u7a0b\u4f9d\u8d56\u5173\u7cfb<\/li>\n \u66f4\u7075\u6d3b\u7684\u8c03\u8282\u673a\u5236<\/li>\n \u66f4\u5bb9\u6613\u6269\u5c55\u5230\u66f4\u5927\u7684\u6a21\u578b\u5c3a\u5bf8<\/li>\n<\/ul>\nDiT\uff08\u6269\u6563\u53d8\u538b\u5668\uff09\u7b49\u6a21\u5f0f\u5df2\u663e\u793a\u51fa\u826f\u597d\u7684\u6548\u679c\uff0c\u6709\u53ef\u80fd\u4e3a\u5b9e\u73b0\u66f4\u9ad8\u8d28\u91cf\u7684\u53d1\u7535\u63d0\u4f9b\u4e00\u6761\u9014\u5f84\u3002<\/p>\n \u5206\u5c42\u6269\u6563\u6a21\u578b<\/h3>\n\u5206\u5c42\u6269\u6563\u6a21\u578b\u53ef\u751f\u6210\u591a\u79cd\u5c3a\u5ea6\u7684\u6570\u636e\uff0c\u65e2\u53ef\u5b9e\u73b0\u5168\u5c40\u4e00\u81f4\u6027\uff0c\u4e5f\u53ef\u5b9e\u73b0\u7ec6\u7c92\u5ea6\u7ec6\u8282\u3002\u8fd9\u4e00\u8fc7\u7a0b\u901a\u5e38\u5305\u62ec<\/p>\n \n\u751f\u6210\u4f4e\u5206\u8fa8\u7387\u8f93\u51fa<\/li>\n \u9010\u6b65\u63d0\u9ad8\u91c7\u6837\u7387\u548c\u7cbe\u5ea6<\/li>\n<\/ol>\n\u8fd9\u79cd\u65b9\u6cd5\u5bf9\u4e8e\u751f\u6210\u9ad8\u5206\u8fa8\u7387\u56fe\u50cf\u6216\u957f\u683c\u5f0f\u5185\u5bb9\u5c24\u4e3a\u6709\u6548\u3002<\/p>\n<\/div>\n<\/div>\n \u9ad8\u7ea7\u4e3b\u9898<\/h2>\n \u65e0\u5206\u7c7b\u5668\u5f15\u5bfc<\/h3>\n\u65e0\u5206\u7c7b\u5668\u5f15\u5bfc\u662f\u4e00\u79cd\u63d0\u9ad8\u6837\u54c1\u8d28\u91cf\u548c\u53ef\u63a7\u6027\u7684\u6280\u672f\u3002\u5176\u5173\u952e\u601d\u8def\u662f\u8bad\u7ec3\u4e24\u4e2a\u6269\u6563\u6a21\u578b\uff1a<\/p>\n \nAn unconditional model p(x_t)<\/li>\n \u6761\u4ef6\u6a21\u578b p(x_t | y)\uff0c\u5176\u4e2d y \u662f\u4e00\u4e9b\u6761\u4ef6\u4fe1\u606f\uff08\u5982\u6587\u672c\u63d0\u793a\uff09\u3002<\/li>\n<\/ol>\n\u5728\u91c7\u6837\u8fc7\u7a0b\u4e2d\uff0c\u6211\u4eec\u5728\u8fd9\u4e9b\u6a21\u578b\u4e4b\u95f4\u8fdb\u884c\u63d2\u503c\uff1a<\/p>\n \u03b5_\u03b8 = (1 + w) * \u03b5_\u03b8(x_t | y) - w * \u03b5_\u03b8(x_t)<\/code><\/p>\n \u5176\u4e2d\uff0cw > 0 \u662f\u4e00\u4e2a\u6307\u5bfc\u5c3a\u5ea6\uff0c\u7528\u4e8e\u63a7\u5236\u5bf9\u6761\u4ef6\u6a21\u578b\u7684\u5f3a\u8c03\u7a0b\u5ea6\u3002<\/p>\n \u8fd9\u6837\u5c31\u53ef\u4ee5\u5728\u65e0\u9700\u91cd\u65b0\u8bad\u7ec3\u6a21\u578b\u7684\u60c5\u51b5\u4e0b\u8fdb\u884c\u66f4\u5f3a\u7684\u8c03\u8282\u3002\u5b83\u5bf9\u300aDALL-E 2\u300b\u548c\u300aStable Diffusion\u300b\u7b49\u6587\u672c\u5230\u56fe\u50cf\u6a21\u5f0f\u7684\u6210\u529f\u81f3\u5173\u91cd\u8981\u3002<\/p>\n \u6f5c\u5728\u6269\u6563<\/h3>\n<\/a><\/p>\n(\u8d44\u6599\u6765\u6e90)Rombach et al.<\/a><\/p>\n<\/div>\n \u6f5c\u5728\u6269\u6563\u6a21\u578b\uff08LDM\uff09\u8fc7\u7a0b\u5305\u62ec\u5c06\u8f93\u5165\u6570\u636e\u7f16\u7801\u5230\u53d1\u751f\u6269\u6563\u8fc7\u7a0b\u7684\u6f5c\u5728\u7a7a\u95f4\u3002\u8be5\u6a21\u578b\u5728\u56fe\u50cf\u7684\u6f5c\u5728\u8868\u793a\u4e2d\u9010\u6b65\u6dfb\u52a0\u566a\u58f0\uff0c\u4ece\u800c\u751f\u6210\u566a\u58f0\u7248\u672c\uff0c\u7136\u540e\u4f7f\u7528 U-Net \u67b6\u6784\u5bf9\u566a\u58f0\u7248\u672c\u8fdb\u884c\u53bb\u566a\u5904\u7406\u3002U-Net \u5728\u4ea4\u53c9\u6ce8\u610f\u673a\u5236\u7684\u5f15\u5bfc\u4e0b\uff0c\u6574\u5408\u6765\u81ea\u8bed\u4e49\u56fe\u3001\u6587\u672c\u548c\u56fe\u50cf\u8868\u5f81\u7b49\u5404\u79cd\u8c03\u8282\u6e90\u7684\u4fe1\u606f\uff0c\u6700\u7ec8\u5728\u50cf\u7d20\u7a7a\u95f4\u4e2d\u91cd\u5efa\u56fe\u50cf\u3002\u8fd9\u4e00\u8fc7\u7a0b\u5bf9\u4e8e\u751f\u6210\u5177\u6709\u53ef\u63a7\u7ed3\u6784\u548c\u6240\u9700\u5c5e\u6027\u7684\u9ad8\u8d28\u91cf\u56fe\u50cf\u81f3\u5173\u91cd\u8981\u3002<\/p>\n \u8fd9\u6837\u505a\u6709\u51e0\u4e2a\u597d\u5904\uff1a<\/p>\n \n\u66f4\u5feb\u7684\u57f9\u8bad\u548c\u53d6\u6837<\/li>\n \u66f4\u597d\u5730\u5904\u7406\u9ad8\u5206\u8fa8\u7387\u56fe\u50cf<\/li>\n \u66f4\u5bb9\u6613\u52a0\u5165\u8c03\u8282\u529f\u80fd<\/li>\n<\/ul>\n\u6d41\u7a0b\u5982\u4e0b<\/p>\n \n\u8bad\u7ec3\u81ea\u52a8\u7f16\u7801\u5668\uff0c\u5c06\u56fe\u50cf\u538b\u7f29\u81f3\u6f5c\u5728\u7a7a\u95f4<\/li>\n \u5728\u8be5\u6f5c\u7a7a\u95f4\u4e2d\u8bad\u7ec3\u6269\u6563\u6a21\u578b<\/li>\n \u751f\u6210\u65f6\uff0c\u5728\u6f5c\u7a7a\u95f4\u91c7\u6837\u5e76\u89e3\u7801\u4e3a\u50cf\u7d20<\/li>\n<\/ol>\n\u8fd9\u79cd\u65b9\u6cd5\u975e\u5e38\u6210\u529f\uff0c\u4e3a\u7a33\u5b9a\u6269\u6563\u7b49\u6a21\u578b\u63d0\u4f9b\u4e86\u52a8\u529b\u3002<\/p>\n \u4e00\u81f4\u6027\u6a21\u578b<\/h3>\n\u4e00\u81f4\u6027\u6a21\u578b\u662f\u6700\u8fd1\u7684\u4e00\u9879\u521b\u65b0\uff0c\u65e8\u5728\u63d0\u9ad8\u6269\u6563\u6a21\u578b\u7684\u901f\u5ea6\u548c\u8d28\u91cf\u3002\u5176\u5173\u952e\u601d\u8def\u662f\u8bad\u7ec3\u4e00\u4e2a\u5355\u4e00\u6a21\u578b\uff0c\u8be5\u6a21\u578b\u53ef\u4ee5\u4ece\u4efb\u4f55\u566a\u58f0\u6c34\u5e73\u76f4\u63a5\u6620\u5c04\u5230\u6700\u7ec8\u8f93\u51fa\uff0c\u800c\u4e0d\u9700\u8981\u8fed\u4ee3\u53bb\u566a\u3002<\/p>\n \u8fd9\u662f\u901a\u8fc7\u7cbe\u5fc3\u8bbe\u8ba1\u7684\u635f\u5931\u51fd\u6570\u6765\u5b9e\u73b0\u7684\uff0c\u8be5\u51fd\u6570\u53ef\u786e\u4fdd\u4e0d\u540c\u566a\u58f0\u6c34\u5e73\u4e0b\u9884\u6d4b\u7ed3\u679c\u7684\u4e00\u81f4\u6027\u3002\u56e0\u6b64\uff0c\u8be5\u6a21\u578b\u80fd\u5728\u4e00\u6b21\u524d\u5411\u4f20\u9012\u4e2d\u751f\u6210\u9ad8\u8d28\u91cf\u6837\u672c\uff0c\u5927\u5927\u52a0\u5feb\u4e86\u63a8\u7406\u901f\u5ea6\u3002<\/p>\n \u8bad\u7ec3\u6269\u6563\u6a21\u578b\u7684\u5b9e\u7528\u6280\u5de7<\/h2>\n\u8bad\u7ec3\u9ad8\u8d28\u91cf\u7684\u6269\u6563\u6a21\u578b\u5177\u6709\u6311\u6218\u6027\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u63d0\u9ad8\u8bad\u7ec3\u7a33\u5b9a\u6027\u548c\u6548\u679c\u7684\u5b9e\u7528\u6280\u5de7\uff1a<\/p>\n \n\u6e10\u53d8\u526a\u5207\u4f7f\u7528\u68af\u5ea6\u526a\u5207\u6765\u9632\u6b62\u68af\u5ea6\u7206\u70b8\uff0c\u5c24\u5176\u662f\u5728\u8bad\u7ec3\u521d\u671f\u3002<\/li>\n \u6a21\u578b\u6743\u91cd\u7684 EMA\uff1a\u4fdd\u7559\u6a21\u578b\u6743\u91cd\u7684\u6307\u6570\u79fb\u52a8\u5e73\u5747\u503c\uff08EMA\uff09\u8fdb\u884c\u91c7\u6837\uff0c\u8fd9\u6837\u53ef\u4ee5\u751f\u6210\u66f4\u7a33\u5b9a\u3001\u8d28\u91cf\u66f4\u9ad8\u7684\u6570\u636e\u3002<\/li>\n \u6570\u636e\u6269\u5145\uff1a\u5bf9\u4e8e\u56fe\u50cf\u6a21\u578b\uff0c\u968f\u673a\u6c34\u5e73\u7ffb\u8f6c\u7b49\u7b80\u5355\u7684\u589e\u5f3a\u63aa\u65bd\u53ef\u4ee5\u63d0\u9ad8\u6cdb\u5316\u6548\u679c\u3002<\/li>\n \u566a\u97f3\u8c03\u5ea6\uff1a\u5c1d\u8bd5\u4f7f\u7528\u4e0d\u540c\u7684\u566a\u58f0\u8868\uff08\u7ebf\u6027\u3001\u4f59\u5f26\u3001sigmoid\uff09\uff0c\u627e\u51fa\u6700\u9002\u5408\u60a8\u6570\u636e\u7684\u566a\u58f0\u8868\u3002<\/li>\n \u6df7\u5408\u7cbe\u5ea6\u8bad\u7ec3\uff1a\u4f7f\u7528\u6df7\u5408\u7cbe\u5ea6\u8bad\u7ec3\u6765\u51cf\u5c11\u5185\u5b58\u4f7f\u7528\u5e76\u52a0\u5feb\u8bad\u7ec3\u901f\u5ea6\uff0c\u5c24\u5176\u662f\u5bf9\u4e8e\u5927\u578b\u6a21\u578b\u3002<\/li>\n \u6709\u6761\u4ef6\u751f\u6210\uff1a\u5373\u4f7f\u60a8\u7684\u6700\u7ec8\u76ee\u6807\u662f\u65e0\u6761\u4ef6\u751f\u6210\u6837\u672c\uff0c\u901a\u8fc7\u6761\u4ef6\u8bad\u7ec3\uff08\u5982\u56fe\u50cf\u7c7b\uff09\u4e5f\u80fd\u63d0\u9ad8\u6837\u672c\u7684\u6574\u4f53\u8d28\u91cf\u3002<\/li>\n<\/ol>\n\u8bc4\u4f30\u6269\u6563\u6a21\u578b<\/h2>\n\u6b63\u786e\u8bc4\u4f30\u751f\u6210\u6a21\u578b\u81f3\u5173\u91cd\u8981\uff0c\u4f46\u4e5f\u6781\u5177\u6311\u6218\u6027\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u8861\u91cf\u6807\u51c6\u548c\u65b9\u6cd5\uff1a<\/p>\n \u5f17\u96f7\u8c22\u7279\u8d77\u59cb\u8ddd\u79bb (FID)<\/h3>\nFID \u662f\u4e00\u79cd\u5e7f\u6cdb\u4f7f\u7528\u7684\u6307\u6807\uff0c\u7528\u4e8e\u8bc4\u4f30\u751f\u6210\u56fe\u50cf\u7684\u8d28\u91cf\u548c\u591a\u6837\u6027\u3002\u5b83\u5c06\u751f\u6210\u6837\u672c\u7684\u7edf\u8ba1\u6570\u636e\u4e0e\u9884\u8bad\u7ec3\u5206\u7c7b\u5668\uff08\u901a\u5e38\u4e3a InceptionV3\uff09\u7279\u5f81\u7a7a\u95f4\u4e2d\u7684\u771f\u5b9e\u6570\u636e\u8fdb\u884c\u6bd4\u8f83\u3002<\/p>\n FID \u5206\u6570\u8d8a\u4f4e\uff0c\u8bf4\u660e\u8d28\u91cf\u8d8a\u597d\uff0c\u5206\u5e03\u8d8a\u771f\u5b9e\u3002\u4e0d\u8fc7\uff0cFID \u6709\u5176\u5c40\u9650\u6027\uff0c\u4e0d\u5e94\u4f5c\u4e3a\u552f\u4e00\u7684\u8861\u91cf\u6807\u51c6\u3002<\/p>\n \u521d\u59cb\u5206\u6570 (IS)<\/h3>\n\u521d\u521b\u5f97\u5206\u53ef\u8861\u91cf\u751f\u6210\u56fe\u50cf\u7684\u8d28\u91cf\u548c\u591a\u6837\u6027\u3002\u5b83\u4f7f\u7528\u9884\u5148\u8bad\u7ec3\u597d\u7684 Inception \u7f51\u7edc\u8fdb\u884c\u8ba1\u7b97\uff1a<\/p>\n IS = exp(E[KL(p(y|x) || p(y))])<\/code><\/p>\n \u5176\u4e2d\uff0cp(y|x) \u662f\u751f\u6210\u56fe\u50cf x \u7684\u6761\u4ef6\u7c7b\u522b\u5206\u5e03\u3002<\/p>\n IS \u8d8a\u9ad8\uff0c\u8868\u793a\u8d28\u91cf\u548c\u591a\u6837\u6027\u8d8a\u597d\uff0c\u4f46\u5b83\u4e5f\u6709\u5df2\u77e5\u7684\u5c40\u9650\u6027\uff0c\u5c24\u5176\u662f\u5bf9\u4e8e\u4e0e ImageNet \u622a\u7136\u4e0d\u540c\u7684\u6570\u636e\u96c6\u800c\u8a00\u3002<\/p>\n \u8d1f\u5bf9\u6570\u4f3c\u7136\u6cd5 (NLL)<\/h3>\n\u5bf9\u4e8e\u6269\u6563\u6a21\u578b\uff0c\u6211\u4eec\u53ef\u4ee5\u8ba1\u7b97\u4fdd\u7559\u6570\u636e\u7684\u8d1f\u5bf9\u6570\u4f3c\u7136\u3002\u8fd9\u53ef\u4ee5\u76f4\u63a5\u8861\u91cf\u6a21\u578b\u4e0e\u771f\u5b9e\u6570\u636e\u5206\u5e03\u7684\u62df\u5408\u7a0b\u5ea6\u3002<\/p>\n \u4e0d\u8fc7\uff0c\u8981\u5bf9\u9ad8\u7ef4\u6570\u636e\u8fdb\u884c\u7cbe\u786e\u4f30\u7b97\uff0cNLL \u7684\u8ba1\u7b97\u6210\u672c\u53ef\u80fd\u4f1a\u5f88\u9ad8\u3002<\/p>\n \u4eba\u7c7b\u8bc4\u4ef7<\/h3>\n\u5bf9\u4e8e\u8bb8\u591a\u5e94\u7528\uff0c\u5c24\u5176\u662f\u521b\u9020\u6027\u5e94\u7528\uff0c\u4eba\u5de5\u8bc4\u4f30\u4ecd\u7136\u81f3\u5173\u91cd\u8981\u3002\u8fd9\u53ef\u80fd\u5305\u62ec<\/p>\n \n\u4e0e\u5176\u4ed6\u673a\u578b\u5e76\u6392\u6bd4\u8f83<\/li>\n \u56fe\u7075\u6d4b\u8bd5\u5f0f\u8bc4\u4f30<\/li>\n \u9488\u5bf9\u7279\u5b9a\u4efb\u52a1\u7684\u8bc4\u4f30\uff08\u5982\u6587\u672c\u5230\u56fe\u50cf\u6a21\u578b\u7684\u56fe\u50cf\u5b57\u5e55\uff09<\/li>\n<\/ul>\n\u867d\u7136\u4e3b\u89c2\u6027\u5f88\u5f3a\uff0c\u4f46\u4eba\u5de5\u8bc4\u4f30\u53ef\u4ee5\u6355\u6349\u5230\u81ea\u52a8\u6307\u6807\u6240\u5ffd\u7565\u7684\u8d28\u91cf\u65b9\u9762\u3002<\/p>\n \u751f\u4ea7\u4e2d\u7684\u6269\u6563\u6a21\u578b<\/h2>\n\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u90e8\u7f72\u6269\u6563\u6a21\u578b\u9762\u4e34\u7740\u72ec\u7279\u7684\u6311\u6218\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u6ce8\u610f\u4e8b\u9879\u548c\u6700\u4f73\u505a\u6cd5\uff1a<\/p>\n \u4f18\u5316\u63a8\u7406<\/h3>\n\nONNX \u51fa\u53e3\uff1a\u5c06\u6a21\u578b\u8f6c\u6362\u4e3a ONNX \u683c\u5f0f\uff0c\u4ee5\u4fbf\u5728\u4e0d\u540c\u786c\u4ef6\u4e0a\u66f4\u5feb\u5730\u8fdb\u884c\u63a8\u7406\u3002<\/li>\n \u91cf\u5316\uff1a\u4f7f\u7528 INT8 \u91cf\u5316\u7b49\u6280\u672f\u7f29\u5c0f\u6a21\u578b\u5927\u5c0f\uff0c\u63d0\u9ad8\u63a8\u7406\u901f\u5ea6\u3002<\/li>\n \u7f13\u5b58\uff1a\u5bf9\u4e8e\u6761\u4ef6\u6a21\u578b\uff0c\u7f13\u5b58\u65e0\u6761\u4ef6\u6a21\u578b\u7684\u4e2d\u95f4\u7ed3\u679c\uff0c\u4ee5\u52a0\u5feb\u65e0\u5206\u7c7b\u5668\u5f15\u5bfc\u7684\u901f\u5ea6\u3002<\/li>\n \u6279\u91cf\u5904\u7406\uff1a\u5229\u7528\u6279\u5904\u7406\u9ad8\u6548\u5229\u7528 GPU \u8d44\u6e90\u3002<\/li>\n<\/ol>\n\u7f29\u653e<\/h3>\n\n\u5206\u5e03\u5f0f\u63a8\u7406\u5bf9\u4e8e\u9ad8\u541e\u5410\u91cf\u5e94\u7528\uff0c\u53ef\u5728\u591a\u4e2a GPU \u6216\u673a\u5668\u4e0a\u5b9e\u65bd\u5206\u5e03\u5f0f\u63a8\u7406\u3002<\/li>\n \u81ea\u9002\u5e94\u91c7\u6837\uff1a\u6839\u636e\u6240\u9700\u7684\u8d28\u91cf-\u901f\u5ea6\u6743\u8861\uff0c\u52a8\u6001\u8c03\u6574\u91c7\u6837\u6b65\u6570\u3002<\/li>\n \u8fdb\u6b65\u7684\u4e00\u4ee3\u5bf9\u4e8e\u5927\u578b\u8f93\u51fa\uff08\u5982\u9ad8\u5206\u8fa8\u7387\u56fe\u50cf\uff09\uff0c\u4ece\u4f4e\u5206\u8fa8\u7387\u5230\u9ad8\u5206\u8fa8\u7387\u9010\u6b65\u751f\u6210\uff0c\u4ee5\u63d0\u4f9b\u66f4\u5feb\u7684\u521d\u59cb\u7ed3\u679c\u3002<\/li>\n<\/ol>\n\u5b89\u5168\u548c\u8fc7\u6ee4<\/h3>\n\n\u5185\u5bb9\u8fc7\u6ee4\uff1a\u5b9e\u65bd\u5f3a\u5927\u7684\u5185\u5bb9\u8fc7\u6ee4\u7cfb\u7edf\uff0c\u9632\u6b62\u751f\u6210\u6709\u5bb3\u6216\u4e0d\u9002\u5f53\u7684\u5185\u5bb9\u3002<\/li>\n \u6c34\u5370\u8003\u8651\u5728\u751f\u6210\u7684\u5185\u5bb9\u4e2d\u52a0\u5165\u9690\u5f62\u6c34\u5370\uff0c\u4ee5\u5b9e\u73b0\u53ef\u8ffd\u6eaf\u6027\u3002<\/li>\n<\/ol>\n\u5e94\u7528<\/h2>\n\u6269\u6563\u6a21\u578b\u5728\u5404\u79cd\u751f\u6210\u4efb\u52a1\u4e2d\u90fd\u53d6\u5f97\u4e86\u6210\u529f\uff1a<\/p>\n \u56fe\u50cf\u751f\u6210<\/h3>\n\u56fe\u50cf\u751f\u6210\u662f\u6269\u6563\u6a21\u578b\u9996\u6b21\u53d7\u5230\u91cd\u89c6\u7684\u5730\u65b9\u3002\u4e00\u4e9b\u8457\u540d\u7684\u4f8b\u5b50\u5305\u62ec<\/p>\n \n\u8fbe\u5229 3\uff1aOpenAI \u7684\u6587\u672c\u5230\u56fe\u50cf\u6a21\u578b\uff0c\u7ed3\u5408\u4e86 CLIP \u6587\u672c\u7f16\u7801\u5668\u548c\u6269\u6563\u56fe\u50cf\u89e3\u7801\u5668<\/li>\n \u7a33\u5b9a\u6269\u6563\uff1a\u7528\u4e8e\u6587\u672c\u5230\u56fe\u50cf\u751f\u6210\u7684\u5f00\u6e90\u6f5c\u5728\u6269\u6563\u6a21\u578b<\/li>\n Imagen\uff1a\u8c37\u6b4c\u7684\u6587\u672c\u5230\u56fe\u50cf\u6269\u6563\u6a21\u578b<\/li>\n<\/ul>\n\u8fd9\u4e9b\u6a21\u578b\u53ef\u4ee5\u6839\u636e\u6587\u672c\u63cf\u8ff0\u751f\u6210\u9ad8\u5ea6\u903c\u771f\u548c\u5bcc\u6709\u521b\u610f\u7684\u56fe\u50cf\uff0c\u5176\u6027\u80fd\u4f18\u4e8e\u4ee5\u5f80\u57fa\u4e8e GAN \u7684\u65b9\u6cd5\u3002<\/p>\n \u89c6\u9891\u751f\u6210<\/h3>\n\u6269\u6563\u6a21\u578b\u4e5f\u88ab\u5e94\u7528\u4e8e\u89c6\u9891\u751f\u6210\uff1a<\/p>\n \n\u89c6\u9891\u6269\u6563\u6a21\u578b\u5c06\u65f6\u95f4\u4f5c\u4e3a\u6269\u6563\u8fc7\u7a0b\u4e2d\u7684\u989d\u5916\u7ef4\u5ea6\u6765\u751f\u6210\u89c6\u9891<\/li>\n \u5236\u4f5c\u89c6\u9891Meta \u7684\u6587\u672c\u5230\u89c6\u9891\u6269\u6563\u6a21\u578b<\/li>\n Imagen Video\uff1a\u8c37\u6b4c\u7684\u6587\u672c\u5230\u89c6\u9891\u4f20\u64ad\u6a21\u578b<\/li>\n<\/ul>\n\u8fd9\u4e9b\u6a21\u578b\u53ef\u4ee5\u6839\u636e\u6587\u5b57\u63cf\u8ff0\u751f\u6210\u89c6\u9891\u77ed\u7247\uff0c\u4e3a\u5185\u5bb9\u521b\u4f5c\u63d0\u4f9b\u4e86\u65b0\u7684\u53ef\u80fd\u6027\u3002<\/p>\n \u4e09\u7ef4\u751f\u6210<\/h3>\n\u6700\u8fd1\u7684\u5de5\u4f5c\u5df2\u5c06\u6269\u6563\u6a21\u578b\u6269\u5c55\u5230\u4e09\u7ef4\u751f\u6210\uff1a<\/p>\n \n\u68a6\u60f3\u878d\u5408\u5229\u7528\u4e8c\u7ef4\u6269\u6563\u6a21\u578b\u751f\u6210\u6587\u672c\u5230\u4e09\u7ef4\u56fe\u50cf<\/li>\n E\u70b9OpenAI \u7528\u4e8e\u751f\u6210 3D \u7269\u4f53\u7684\u70b9\u4e91\u6269\u6563\u6a21\u578b<\/li>\n<\/ul>\n\u8fd9\u4e9b\u65b9\u6cd5\u53ef\u4ee5\u6839\u636e\u6587\u5b57\u63cf\u8ff0\u521b\u5efa 3D \u8d44\u4ea7\uff0c\u5e94\u7528\u4e8e\u6e38\u620f\u3001VR\/AR \u548c\u4ea7\u54c1\u8bbe\u8ba1\u3002<\/p>\n \u6311\u6218\u4e0e\u672a\u6765\u65b9\u5411<\/h2>\n\u867d\u7136\u4f20\u64ad\u6a21\u578b\u5df2\u53d6\u5f97\u4e86\u663e\u8457\u7684\u6210\u529f\uff0c\u4f46\u4ecd\u5b58\u5728\u4e00\u4e9b\u6311\u6218\u548c\u672a\u6765\u7814\u7a76\u7684\u9886\u57df\uff1a<\/p>\n \u8ba1\u7b97\u6548\u7387<\/h3>\n\u6269\u6563\u6a21\u578b\u7684\u8fed\u4ee3\u91c7\u6837\u8fc7\u7a0b\u53ef\u80fd\u5f88\u6162\uff0c\u5c24\u5176\u662f\u5728\u9ad8\u5206\u8fa8\u7387\u8f93\u51fa\u65f6\u3002\u6f5c\u5728\u6269\u6563\u548c\u4e00\u81f4\u6027\u6a21\u578b\u7b49\u65b9\u6cd5\u65e8\u5728\u89e3\u51b3\u8fd9\u4e00\u95ee\u9898\uff0c\u4f46\u8fdb\u4e00\u6b65\u63d0\u9ad8\u6548\u7387\u662f\u4e00\u4e2a\u6d3b\u8dc3\u7684\u7814\u7a76\u9886\u57df\u3002<\/p>\n \u53ef\u63a7\u6027<\/h3>\n\u867d\u7136\u65e0\u5206\u7c7b\u5668\u5f15\u5bfc\u7b49\u6280\u672f\u63d0\u9ad8\u4e86\u53ef\u63a7\u6027\uff0c\u4f46\u5728\u5bf9\u751f\u6210\u7684\u8f93\u51fa\u8fdb\u884c\u66f4\u7cbe\u7ec6\u7684\u63a7\u5236\u65b9\u9762\u4ecd\u6709\u8bb8\u591a\u5de5\u4f5c\u8981\u505a\u3002\u8fd9\u5bf9\u521b\u610f\u5e94\u7528\u5c24\u4e3a\u91cd\u8981\u3002<\/p>\n \u591a\u6a21\u5f0f\u751f\u6210<\/h3>\n\u5f53\u524d\u7684\u6269\u6563\u6a21\u578b\u64c5\u957f\u4e8e\u5355\u4e00\u6a21\u5f0f\u751f\u6210\uff08\u5982\u56fe\u50cf\u6216\u97f3\u9891\uff09\u3002\u5f00\u53d1\u80fd\u591f\u65e0\u7f1d\u751f\u6210\u8de8\u6a21\u6001\u7684\u771f\u6b63\u591a\u6a21\u6001\u6269\u6563\u6a21\u578b\u662f\u672a\u6765\u5de5\u4f5c\u7684\u4e00\u4e2a\u4ee4\u4eba\u5174\u594b\u7684\u65b9\u5411\u3002<\/p>\n \u7406\u8bba\u8ba4\u8bc6<\/h3>\n\u867d\u7136\u6269\u6563\u6a21\u578b\u6709\u5f88\u5f3a\u7684\u5b9e\u8bc1\u7ed3\u679c\uff0c\u4f46\u6211\u4eec\u4ecd\u9700\u8fdb\u4e00\u6b65\u4e86\u89e3\u5b83\u4eec\u4e3a\u4f55\u5982\u6b64\u6709\u6548\u3002\u52a0\u6df1\u5bf9\u7406\u8bba\u7684\u7406\u89e3\uff0c\u53ef\u4ee5\u8fdb\u4e00\u6b65\u6539\u8fdb\u5de5\u4f5c\u548c\u5f00\u53d1\u65b0\u7684\u5e94\u7528\u3002<\/p>\n \u7ed3\u8bba\uff1a<\/h2>\n\u6269\u6563\u6a21\u578b\u662f\u751f\u6210\u5f0f\u4eba\u5de5\u667a\u80fd\u7684\u4e00\u5927\u8fdb\u6b65\uff0c\u53ef\u5728\u5404\u79cd\u6a21\u5f0f\u4e0b\u63d0\u4f9b\u9ad8\u8d28\u91cf\u7684\u7ed3\u679c\u3002\u901a\u8fc7\u5b66\u4e60\u9006\u8f6c\u566a\u58f0\u6dfb\u52a0\u8fc7\u7a0b\uff0c\u5b83\u4eec\u63d0\u4f9b\u4e86\u4e00\u79cd\u7075\u6d3b\u7684\u3001\u6709\u7406\u8bba\u4f9d\u636e\u7684\u751f\u6210\u65b9\u6cd5\u3002<\/p>\n \u4ece\u521b\u610f\u5de5\u5177\u5230\u79d1\u5b66\u6a21\u62df\uff0c\u751f\u6210\u590d\u6742\u3001\u9ad8\u7ef4\u6570\u636e\u7684\u80fd\u529b\u6709\u53ef\u80fd\u6539\u53d8\u8bb8\u591a\u9886\u57df\u3002\u4e0d\u8fc7\uff0c\u91cd\u8981\u7684\u662f\u8981\u6df1\u601d\u719f\u8651\u5730\u5bf9\u5f85\u8fd9\u4e9b\u5f3a\u5927\u7684\u6280\u672f\uff0c\u65e2\u8981\u8003\u8651\u5230\u5b83\u4eec\u7684\u5de8\u5927\u6f5c\u529b\uff0c\u4e5f\u8981\u8003\u8651\u5230\u5b83\u4eec\u5e26\u6765\u7684\u4f26\u7406\u6311\u6218\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":" \u6269\u6563\u6a21\u578b\u5df2\u6210\u4e3a\u751f\u6210\u5f0f\u4eba\u5de5\u667a\u80fd\u7684\u4e00\u79cd\u5f3a\u5927\u65b9\u6cd5\uff0c\u5728\u56fe\u50cf\u3001\u97f3\u9891\u548c\u89c6\u9891\u751f\u6210\u65b9\u9762\u53d6\u5f97\u4e86\u6700\u5148\u8fdb\u7684\u6210\u679c\u3002\u5728\u8fd9\u7bc7\u6df1\u5165\u6d45\u51fa\u7684\u6280\u672f […]<\/p>\n","protected":false},"author":1,"featured_media":34176,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[391],"tags":[],"class_list":["post-33933","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-391"],"_links":{"self":[{"href":"https:\/\/linguaresources.com\/index.php?rest_route=\/wp\/v2\/posts\/33933","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/linguaresources.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/linguaresources.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/linguaresources.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/linguaresources.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=33933"}],"version-history":[{"count":0,"href":"https:\/\/linguaresources.com\/index.php?rest_route=\/wp\/v2\/posts\/33933\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/linguaresources.com\/index.php?rest_route=\/wp\/v2\/media\/34176"}],"wp:attachment":[{"href":"https:\/\/linguaresources.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=33933"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/linguaresources.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=33933"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/linguaresources.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=33933"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}

\u5efa\u7b51\u521b\u65b0<\/h2>\n

\u9ad8\u7ea7\u4e3b\u9898<\/h2>\n

\u8bc4\u4f30\u6269\u6563\u6a21\u578b<\/h2>\n
\u6b63\u786e\u8bc4\u4f30\u751f\u6210\u6a21\u578b\u81f3\u5173\u91cd\u8981\uff0c\u4f46\u4e5f\u6781\u5177\u6311\u6218\u6027\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u8861\u91cf\u6807\u51c6\u548c\u65b9\u6cd5\uff1a<\/p>\n

\u751f\u4ea7\u4e2d\u7684\u6269\u6563\u6a21\u578b<\/h2>\n
\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u90e8\u7f72\u6269\u6563\u6a21\u578b\u9762\u4e34\u7740\u72ec\u7279\u7684\u6311\u6218\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u6ce8\u610f\u4e8b\u9879\u548c\u6700\u4f73\u505a\u6cd5\uff1a<\/p>\n

\u5e94\u7528<\/h2>\n
\u6269\u6563\u6a21\u578b\u5728\u5404\u79cd\u751f\u6210\u4efb\u52a1\u4e2d\u90fd\u53d6\u5f97\u4e86\u6210\u529f\uff1a<\/p>\n

\u6311\u6218\u4e0e\u672a\u6765\u65b9\u5411<\/h2>\n
\u867d\u7136\u4f20\u64ad\u6a21\u578b\u5df2\u53d6\u5f97\u4e86\u663e\u8457\u7684\u6210\u529f\uff0c\u4f46\u4ecd\u5b58\u5728\u4e00\u4e9b\u6311\u6218\u548c\u672a\u6765\u7814\u7a76\u7684\u9886\u57df\uff1a<\/p>\n