class_docstr: LogSigmoidLoss.
      
class_docstr_tok: ["LogSigmoidLoss","."]
code: def __call__(self, score, label, weights):
      if weights is not None:
          if len(score.shape) > len(weights.shape):
              weights = weights.unsqueeze(1)
          return (
              -(weights * log_sigmoid(label * score)).sum()
              / weights.sum()
          )
      else:
          return -log_sigmoid(label * score)
  
file_path: PGL/apps/Graph4KG/models/loss_func.py
imports: import paddle
  from paddle.nn import BCELoss, MarginRankingLoss
  from paddle.nn.functional import log_sigmoid, softmax, softplus
label_desc: Use image node_id 2 for calling the LogSigmoidLoss obj's underlying member method code with example usage: obj.__call__(score, label, weights) and returns: unknown, unknown