segnet.py 文件源码

def __call__(self, x, t):
        self.y = self.predictor(x, self.train_depth)
        if hasattr(self, 'class_weight'):
            if isinstance(x.data, cuda.cupy.ndarray) \
                    and not isinstance(self.class_weight, cuda.cupy.ndarray):
                self.class_weight = cuda.to_gpu(
                    self.class_weight, device=x.data.device)
            self.loss = softmax_cross_entropy(
                self.y, t, class_weight=self.class_weight)
        else:
            self.loss = F.softmax_cross_entropy(self.y, t)
        reporter.report({'loss': self.loss}, self)
        return self.loss