4、Stochastic Depth实验效果 从Fig.3.可以看出,常数深度的残差网络训练阶段的loss要比随机深度的残差网络训练阶段的loss少,然而测试阶段随机深度的残差网络错误率更低,由此可见随机深度网络提高了模型的泛化能力,是一种有效的网络正则化方法。 5、参考文献 【1】Huang G, Sun Y, Liu Z, et al. Deep networks w...
这个dpr数组用于存储每个Block层的drop_path_rate(丢弃路径比率)值。 `torch.linspace(0, drop_path_rate, depth)`函数用于从0到`drop_path_rate`(丢弃路径比率)中等间距采样生成长度为`depth`的一维张量,这个张量的元素值表示每个Block层应该使用的丢弃路径比率。而 `x.item()` 则是将这个张量中的每个数值转化...
Keras代码实现:https://github.com/dblN/stochastic_depth_keras
本项目是基于Stochastic Depth的基于cifar10数据集的ResNet110模型在 Paddle 2.x上的开源实现。该模型有3个Layer,每个Layer分别由18个BasicBlock组成,每个BasicBlock由两个conv-bn-relu和skip connection组成,其中按论文在每个mini-batch进行按照论文公式计算出的linear_decay的各block的drop_rate(论文中是保留率,1-dro...
git clone https://github.com/yueatsprograms/Stochastic_DepthcdStochastic_Depth git clone https://github.com/soumith/cifar.torchcdcifar.torch th Cifar10BinToTensor.luacd.. mkdir results th main.lua -dataRoot cifar.torch/ -resultFolder results/ -deathRate 0.5 ...
Rate-distortion analysis is proposed for evaluating the quality of the final reconstruction as a function of the number of frames and the error in the image correspondences. Finally, to demonstrate the effectiveness of the algorithm, examples of depth reconstruction are shown for different video ...
%. However, as seen in Fig.4, it starts to overfit at the beginning of the second phase with learning rate 0.01, and continues to overfit until the end of training. With stochastic depth, the error improves to 1.75 %, the second-best published result on SVHN to our knowledge after [...
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The circuit depth – and number of ancillae qubits – thus scales only linearly with the number of timesteps. However, as complex stochastic processes often exhibit strong temporal correlations, the requisite dimension of the memory system can grow quite large. We here explore the potential to ...
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