本文整理汇总了Python中torch.Tensor.new_full方法的典型用法代码示例。如果您正苦于以下问题：Python Tensor.new_full方法的具体用法？Python Tensor.new_full怎么用？Python Tensor.new_full使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类torch.Tensor的用法示例。
在下文中一共展示了Tensor.new_full方法的1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: forward
# 需要导入模块: from torch import Tensor [as 别名]
# 或者: from torch.Tensor import new_full [as 别名]
def forward(self, tokens: torch.Tensor, mask: torch.Tensor = None): #pylint: disable=arguments-differ
if mask is not None:
tokens = tokens * mask.unsqueeze(-1).float()
# Our input has shape `(batch_size, num_tokens, embedding_dim)`, so we sum out the `num_tokens`
# dimension.
summed = tokens.sum(1)
if self._averaged:
if mask is not None:
lengths = get_lengths_from_binary_sequence_mask(mask)
length_mask = (lengths > 0)
# Set any length 0 to 1, to avoid dividing by zero.
lengths = torch.max(lengths, lengths.new_ones(1))
else:
lengths = tokens.new_full((1,), fill_value=tokens.size(1))
length_mask = None
summed = summed / lengths.unsqueeze(-1).float()
if length_mask is not None:
summed = summed * (length_mask > 0).float().unsqueeze(-1)
return summed