torch.Tensor.is_leaf¶
- Tensor.is_leaf¶
根据惯例,所有具有
requires_grad
为False
的张量都将是叶子张量。对于具有
requires_grad
为True
的张量,如果它们是由用户创建的,则它们将是叶子张量。这意味着它们不是操作的结果,因此grad_fn
为 None。只有叶子张量的
grad
会在调用backward()
时被填充。要使非叶子张量的grad
被填充,可以使用retain_grad()
。示例
>>> a = torch.rand(10, requires_grad=True) >>> a.is_leaf True >>> b = torch.rand(10, requires_grad=True).cuda() >>> b.is_leaf False # b was created by the operation that cast a cpu Tensor into a cuda Tensor >>> c = torch.rand(10, requires_grad=True) + 2 >>> c.is_leaf False # c was created by the addition operation >>> d = torch.rand(10).cuda() >>> d.is_leaf True # d does not require gradients and so has no operation creating it (that is tracked by the autograd engine) >>> e = torch.rand(10).cuda().requires_grad_() >>> e.is_leaf True # e requires gradients and has no operations creating it >>> f = torch.rand(10, requires_grad=True, device="cuda") >>> f.is_leaf True # f requires grad, has no operation creating it