fn_sum = MCM[:, 1, 0] # False Negative # 这里加1e-6,防止 0/0的情况计算得到nan,即tp_sum和fn_sum同时为0的情况 Condition_negative = tp_sum + fn_sum + 1e-6 sensitivity = tp_sum / Condition_negative macro_sensitivity = np.average(sensitivity, weights=None) micro_sensitivity = np....
# targets (batch_size,length) (2,100) 或者(sum(target_lengths))即(200,) # 意味着可以将labels摊平为一阶tensor再输入(可以去除ignore_token再摊平,工程一般采用这种方式,这边为方便起见使用第一种) # input_lengths (N,) (2,) [50,50] # target_lengths: (N,) (2,) [100,100] import torch...
float() # use fp32 to avoid nan with torch.no_grad(): num_classes = logits.size(1) label = label.clone().detach() ignore = label == self.lb_ignore n_valid = (ignore == 0).sum() label[ignore] = 0 lb_pos, lb_neg = 1. - self.lb_smooth, self.lb_smooth / num_classes ...
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\text{{out}}_i = \sum_{j=0}^{i} (\frac{1}{\gamma})^{i-j}\text{in}_j.Gamma == 1 is a normal cumsum, gamma < 1 will blow up quickly so is disabled.Args: x (Tensor): N-D Tensor to apply operation dim (int, optional): Dimension to apply discounted cumsum over. Def...
sum(1) r_inv = rowsum.pow(-1).flatten() r_inv[torch.isinf(r_inv)] = 0. r_mat_inv = torch.diag(r_inv) mx = r_mat_inv @ mx return mx Example #17Source File: training.py From TTS with Mozilla Public License 2.0 6 votes def check_update(model, grad_clip, ignore_stopnet=...
torch.nn.CrossEntropyLoss(weight=None, size_average=None, ignore_index=-100, reduce=None, reduction='mean') 1. 功能:计算交叉熵函数 主要参数:ignore_index:忽略某个类的损失函数。 计算公式如下: loss = nn.CrossEntropyLoss() input = torch.randn(3, 5, requires_grad=True) target = torch.empty...
...from pts import Trainer import warnings warnings.filterwarnings("ignore") Github Issues 上看到有几个人讨论,但没有给出满意的答案...这个报错很容易分析:No module named 'gluonts.torch.modules.distribution_output',找不到这个模块,根据经验判断大概率是版本问题,新版本的 api...去 GluonTS 官方文档...
actions = actions[...,None]# If the row of mask matrix is zero ignore everything calculated so far and copy the corresponding left hidden# states from the previous layer (the assumption here is that one adds padding tokens to the right side and# action that uses padding token can't be...
ignore_index (int, optional)– Specifies a target value that is ignored and does not contribute to the input gradient. When size_average is True, the loss is averaged over non-ignored targets. Default: -100 reduce (bool, optional)– Deprecated (see reduction). By default, the losses are ...