fi 表示对任意一个 token ,路由到该 expert i 的可能性。如果 Nr 个experts 负载均衡,则每一个 expert i 的fi 得分应为 1Nr 求和函数中,对这一组输入 T 个tokens ,如果在选择 Top Kr 个experts 的时候,选择了该 expert i ,则累加 1 ,否则累加 0 。求和函数的结果代表,一组 T 个tokens ,每个 tok...
他们们就是Gating network(或做路由器)以及auxiliary loss(辅助损失)。 当我们训练MOE模型时,每个专家都有自己擅长处理的语义信息。这时Gating network就像一个分类器,他把每个Token分配给最擅长处理这种语义的专家。在实际的应用上,通常用Softmax以及一个分类网络来实现,可以表示成: G(x)=softmax(Wgx+bg) 。有...
In Google's implementation, the final loss is not divided by t o p k https://github.com/google/flaxformer/blob/main/flaxformer/architectures/moe/routing.py#L744. expert_mask = jax.nn.one_hot(expert_indices, num_experts, dtype=jnp.int32) # For a given token, determine if it was ...
More importantly, an innovative way of complementing the loss function using the auxiliary task from the row-wise similarities of the Amharic alphabet was tested to show a significant recognition improvement over a baseline method. The findings of this study promote innovative problem-specific solutions...
U: negativity, loss, death, darkness, depth O: neutrality, awareness, wholeness A: life, comfort, goodness, health E: stillness, uniformity, slowness I: energy, change, sharpness, difference M: comfort, flow, goodness L: flow, motion, pleasantness ...
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Alzheimer’s disease, commonly refers to the senile dementia, is a degenerative neurological disease that manifests as the progressive loss of cognition and memory. After cardiovascular disease, cancer and stroke, Alzheimer’s disease is the fourth leading cause of death in the world. AD is one ...
Examining the insect TipE gene family reveals several key evolutionary events that characterize the evolution of genes within their genomic contexts: intronic nesting, escape from nesting, overlapping exons, retrotransposition, translocation, gene loss, coordinated regulation, and conserved synteny. ...
如图1,我们的做法是引入了一个辅助decoder,并设计L1 loss来监督它。 OneChart的模型结构如上图,主要包括vision encoder、OPT-125M、Auxiliary decoder三部分。Auxiliary decoder由3层MLP组成,以 Auxiliary token <Chart>的embedding作为输入,输出min-max归一化后的chart数值结果。数值结果部分会计算L1 loss,文本部分计算...
除了初一没有写,其他时间都在写那些核心代码,跑实验,重要把addloss的代码搞好了。可以稳定提升效果。年后第一天上班就跟团队伙伴们对齐了效果。然后就轰轰烈烈的开始写paper了。 同时搞两篇论文真的很累的。投稿前一天,我和小伙伴吃了顿羊肉锅仔。勉强支撑到了AOE时间的截稿时刻。当天6点就下班回家了。实在太累...