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先说清楚是哪种dlm, dlm不是只有masked diffusion一种。masked diffusion也只是discrete diffusion里最简单的case。注意不要把discrete这个形容词忘了,它和传统的连续空间diffusion model比如用于图像视频生成的那些并不相同。最早的dlm就是就是尝试用连续diffusion在embedding/logit space建模text。 最近热度很高的masked. 首先这种 predict masked patches 的预训练方法之前也有几篇不错的了 (例如 这个回答 总结的),像之前读过的 BEiT,它是把 image patch tokenize 成离散的数值 (VQ-VAE 那套),然后做预测;而这篇 MAE 直接说,不用这样,直接重建 RGB 像素值即可,还做了几个 downstream task 证明. linux.服务器后台启动某个服务时,提示unit is masked,请问该如何解决? 关注者 4 被浏览
2024 年 9 月,Kaiwen 的工作放在 arxiv 上 (Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling )也证明了可以去掉时间 t,并特别指出了 MDM 似然实验中的数值问题。 masked autoencode的思想很简单很通用,也很适合于计算机视觉,尽管随着BERT的成功,人们对这一想法产生了极大的兴趣,但视觉中的自动编码方法的进展却落后于NLP。 是什么使得masked autoencoder在视觉和语言之间有所不同? 何恺明最新论文Masked Autoencoders提出了一种高效的自监督学习方法,通过掩码图像块实现了简单却强大的性能。
Bert 损失函数组成: 第一部分是来自 Mask-LM 的单词级别分类任务; 另一部分是句子级别的分类任务; 优点:通过这两个任务的联合学习,可以使得 BERT 学习到的表征既有 token 级别信息,同时也包含了句子级别的语义信息。 损失函数
BERT需要Mask完全是因为用了Transformer模块的原因,因此想要知道BERT为什么需要mask其实就是在问Transformer为什么需要mask。但是两者有个不同的地方在于,由于BERT只是使用了Transformer中的Encoder部分,没有Decoder部分,因此相较于Transformer中的两种mask(key padding mask和attention mask)BERT中只有key padding mask,也. 当你在R语言中遇到 "the following object is masked from 'xxx'" 的报错信息时,这意味着你的代码中引用到的变量或函数与当前作用域中的其他对象重名了。 为了解决这个问题,你可以采取以下几个步骤: 1. 检查重复定义:首先确认出现重复定义的是哪个具体的变量或. 谢邀。Triton DSL可以通过构造一个以pid为基、递增的arange数组,让这个数组跟一个常数numel去比较,作为mask进行masked load/store。这样当tensor的数据量相比于block和warp的数量是不规整的时候,可以mask掉越界的数组访问,保证程序的正确性。
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