kl_div = F.kl_div(q_tensor.log(), p_tensor, reduction='batchmean') 1. 2. 3. 其中,q_tensor.log()表示对概率分布 Q 中的每个元素取对数;p_tensor表示概率分布 P 在 PyTorch 中的张量表示;reduction='batchmean'表示将每个样本的 KL散度求平均值,得到整个 batch 的 KL散度。 需要注意的是,KL散...
pytorch实现计算kl散度F.kl_div（）torch.nn.functional.kl_div(input, target, size_average=None, reduce=None, reduction='mean')Parameters input – Tensor of arbitrary shape target – Tensor of the same shape as input size_average (bool, optional) – Deprecated (see reduction). By default, the...
importtorchimporttorch.nnasnnclassTeacherModel(nn.Module):def__init__(self):super(TeacherModel,self).__init__()# 定义教师模型的结构defforward(self,x):# 定义教师模型的前向传播classStudentModel(nn.Module):def__init__(self):super(StudentModel,self).__init__()# 定义学生模型的结构defforward...
torch.nn.KLDivLoss(reduction='mean') 参数: reduction-三个值,none: 不使用约简;mean:返回loss和的平均值;sum:返回loss的和。默认:mean。 5. 二进制交叉熵损失 BCELoss 二分类任务时的交叉熵计算函数。用于测量重构的误差, 例如自动编码机. 注意目标的值 t[i] 的范围为0到...
(alpha).add(k).pow(beta) return input / div # loss def ctc_loss( log_probs: Tensor, targets: Tensor, input_lengths: Tensor, target_lengths: Tensor, blank: int = 0, reduction: str = "mean", zero_infinity: bool = False, ) -> Tensor: r"""Apply the Connectionist Temporal ...
reduction == "mean" else loss.sum() def _compute_epsilon(self, m): """ Computes epsilon for the epsilon modified loss. Args: m (int): The batch size. Returns: float: Computed epsilon value. """ delta = self.delta c_bound = np.exp(1 / self.temperature) - np.exp(-1 / self....
6.KLDivLoss class torch.nn.KLDivLoss(size_average=None, reduce=None, reduction='elementwise_mean') 功能:计算input和target之间的KL散度( Kullback–Leibler divergence) 。 计算公式: (后面有代码手动计算,证明计算公式确实是这个,但是为什么没有...
On the other hand, fumarate was predominantly metabolised through aspartase since the glyoxylate shunt was highly active when glycerol was the carbon source, which leads to a reduction in total flux through TCA cycle. These modelling results explain the higher growth (Fig. 2C) and higher ...
torch.nn.MSELoss(reduction='mean') 1. 2. (五) 交叉熵损失 5.1 二进制交叉熵损失 BCELoss 二分类任务时的交叉熵计算函数。用于测量重构的误差, 例如自动编码机. 注意目标的值 t[i] 的范围为0到1之间。 # weight (Tensor, optional) – 自定义的每个 batch 元素的 loss 的权重. 必须是一个长度为 “...
'mean', 'median', 'memory_format', 'merge_type_from_type_comment', 'meshgrid', 'min', 'minimum', 'miopen_batch_norm', 'miopen_convolution', 'miopen_convolution_add_relu', 'miopen_convolution_relu', 'miopen_convolution_transpose', 'miopen_depthwise_convolution', 'miopen_rnn', 'mkldnn_...