SGD' object has no attribute 'zero_grad
时间: 2023-11-13 13:04:59 浏览: 261
这个错误提示表明在代码中使用了SGD优化器的zero_grad()方法,但是SGD优化器并没有这个方法。只有继承自torch.optim.Optimizer的优化器才有zero_grad()方法。因此,如果要使用zero_grad()方法,需要使用继承自Optimizer的优化器,例如Adam、Adagrad等。如果要使用SGD优化器,可以使用以下方式清空梯度:
```
optimizer = torch.optim.SGD(model.parameters(), lr=0.1)
optimizer.zero_grad()
```
相关问题
'ExponentialLR' object has no attribute 'zero_grad'
The error message you are seeing suggests that you are trying to call the `zero_grad()` method on an instance of the `ExponentialLR` class, which does not have this method.
`zero_grad()` is a method defined in the `torch.optim.Optimizer` class, which is used to set the gradients of all the parameters to zero before backpropagation.
You should make sure that you are calling `zero_grad()` on an instance of the `Optimizer` class, not the `ExponentialLR` class. Here is an example of how to use `zero_grad()` properly:
```
import torch
import torch.optim as optim
optimizer = optim.SGD(model.parameters(), lr=0.1)
scheduler = optim.lr_scheduler.ExponentialLR(optimizer, gamma=0.9)
# perform a forward pass and compute loss
loss.backward()
# set gradients to zero
optimizer.zero_grad()
# perform backpropagation
optimizer.step()
# update learning rate
scheduler.step()
```
In this example, `zero_grad()` is called on the `optimizer` instance, not the `scheduler` instance.
AttributeError: 'MultiStepLR' object has no attribute 'zero_grad'
AttributeError: 'MultiStepLR' object has no attribute 'zero_grad'一个错误提示,意味着在使用MultiStepLR对象时,尝试调用了它没有的zero_grad属性。
MultiStepLR是PyTorch中的一个学习率调整器(learning rate scheduler),用于在训练过程中动态地调整学习率。它并不具备zero_grad属性,因为它不是一个优化器(optimizer)。
通常情况下,我们会在训练模型时使用优化器来更新模型的参数,并使用scheduler来调整学习率。常见的优化器包括SGD、Adam等,而不是MultiStepLR。
如果你想对模型的参数进行梯度清零操作,你应该使用优化器对象(如SGD或Adam)来调用zero_grad()方法,而不是MultiStepLR对象。