6. N-pair-mc Loss 代码 代码语言:javascript 复制 // N-pair lossimporttorchimporttorch.nn.functionalasFclassNPairMCLoss(torch.nn.Module):def__init__(self,margin=0.1):super(NPairMCLoss,self).__init__()self.margin=margin defforward(self,anchors,positives,negatives):# 计算anchor和positive之间...
N-pair loss for efficient deep metric learning 论文提出了一种高效的批构造方法,以降低额外的计算开销。方法的名字叫multi-classN-pair loss(N-pair-mc),其构造方式如上图(c)所示。来个说文解字,道一道作者的解决方法。方法名中有个N-pair,就从这入手。假若我们有N个pair: \{(x_1, x_1^+), \cdo...
n-pair loss是基于一对样本的损失函数,它通过对正负样本进行比较,来评估模型的预测结果。具体来说,对于每个样本对(x, y),其中x是输入特征,y是对应的标签,n-pair loss的计算过程如下: 1. 计算模型预测概率分布P(y|x)与真实标签分布P(y)之间的KL散度; 2. 根据正负样本的标签差异,设定一个阈值δ; 3. 对于...
contrastive loss 和triplet loss 收敛慢 部分原因是它们仅使用一个负样本而不与每个batch中的其他负类别交互,导致model training的过程中见过的正负样本的情况不充足,特别是对于hard sample pair,本来就不多,可能training的过程中就mining的少很多了,往往需要复杂的hard negative sample mining的方法来辅助。
Loss functions We implemented loss functions to train the network for image retrieval. Batch sampler for the loss function borrowed fromhere. N-pair Loss (NIPS 2016): Sohn, Kihyuk. "Improved Deep Metric Learning with Multi-class N-pair Loss Objective," Advances in Neural Information Processing ...
Improved Deep Metric Learning with Multi-class N-pair Loss Objective - ChaofWang/Npair_loss_pytorch
In this paper, we propose to address this problem with a new metric learning objective called multi-class N-pair loss. The proposed objective function firstly generalizes triplet loss by allowing joint comparison among more than one negative examples - more specifically, N -1 negative examples - ...
在下文中一共展示了v1.add_n方法的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。 示例1: loss_function ▲点赞 6▼ # 需要导入模块: from tensorflow.compat import v1 [as 别名]# 或者: from tensorflow.compat.v...
核心代码解析如下: // 参数读取 程序 // 读取字符串格式的 参数文件 int ParamDict::load_param(FILE* fp) { clear(); // 0=100 1=1.250000 -23303=5,0.1,0.2,0.4,0.8,1.0 // parse each key=value pair int id = 0; while (fscanf(fp, "%d=", &id) == 1)// 读取 等号前面的 key===...
// 参数读取 程序 // 读取字符串格式的 参数文件 int ParamDict::load_param(FILE* fp) { clear(); // 0=100 1=1.250000 -23303=5,0.1,0.2,0.4,0.8,1.0 // parse each key=value pair int id = 0; while (fscanf(fp, "%d=", &id) == 1)// 读取 等号前面的 key=== { bool is_array ...