在 pytorch Lightning 中训练时出现 pytorch_lightning.utilities.exceptions.MisconfigurationException

Question

我正在使用虚拟数据训练样本模型，然后出现此错误。我已经正确提供了所有内容，但仍然收到此错误：没有定义`configure_optimizers()`方法。当我开始训练时，Lightning“Trainer”至少需要定义“training_step()”、“train_dataloader()”和“configure_optimizers()”。问题是因为我将虚拟数据输入网络的方式还是其他原因。

import torch
from torch import nn, optim
import pytorch_lightning as pl 
from torch.utils.data import DataLoader
class ImageClassifier(pl.LightningModule):
    def __init__(self, learning_rate=0.001):
        super().__init__()
        self.learning_rate = learning_rate
        self.conv_layer1 = nn.Conv2d(in_channels=3, out_channels=3, kernel_size=3, stride=1, padding=1) 
    
    def forward(self,x):
        output = self.conv_layer1(x)
        print(output.shape)
        return output
    
    def training_step(self,batch, batch_idx):
        inputs, targets = batch
        output = self(inputs)
        accuracy = self.binary_accuracy(output, targets)
        loss = self.loss(output, targets)
        self.log('train_accuracy', accuracy, prog_bar=True)
        self.log('train_loss', loss)
        return {'loss':loss,"training_accuracy": accuracy}
    
    def test_step(self, batch, batch_idx):
        inputs, targets = batch
        outputs = self.inputs(inputs)
        accuracy = self.binary_accuracy(outputs, targets)
        loss = self.loss(outputs, targets)
        self.log('test_accuracy', accuracy)
        return {"test_loss":loss, "test_accuracy":accuracy}

    def configure_optimizer(self):
        params = self.parameters()
        optimizer = optim.Adam(params=params, lr=self.learning_rate)
        return optimizer

    def binary_accuracy(self, outputs, inputs):
        _, outputs = torch.max(outputs,1)
        correct_results_sum = (outputs == targets).sum().float()
        acc = correct_results_sum/targets.shape[0]
        return acc

model = ImageClassifier()
Input = DataLoader(torch.randn(1,3,28,28))

trainer = pl.Trainer(max_epochs=10, progress_bar_refresh_rate=1)
trainer.fit(model, train_dataloader = Input)

Answer 1

在您的代码中，方法名称为 configure_optimizer()。因此，没有定义 configure_optimizers() 方法。似乎函数名称有错误。

Answer 2

我有同样的问题，然后我意识到错误的方法名称可能会导致错误。只需确保您输入方法名称或导入包并正确使用它即可。