CODEWITHSUNDEEP
pythonpython-3.xpytorchpytorch-lightning
user16668992
user16668992

Reputation:

pytorch_lightning.utilities.exceptions.MisconfigurationException when training in pytorch lightning

I am training a sample model with dummy data then i got this error. I have gave everything properly but still i am getting this error: No `configure_optimizers()` method defined. Lightning `Trainer` expects as minimum a `training_step()`, `train_dataloader()` and `configure_optimizers()` to be defined. when i start training. Is the problem because the way i feed the dummy data into network or is their any other reason.

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)

Upvotes: 1

Views: 9078

Answers (2)

Minh Vu
Minh Vu

Reputation: 21

I have a same problem, then I realize that a wrong method name could lead to the error. just make sure you type medthods name or import package and use it appropriately.

Upvotes: 1

Harsh
Harsh

Reputation: 115

In your code, the method name is configure_optimizer(). Therefore, no configure_optimizers() method defined. Seems like an error in name of the function.

Upvotes: 2

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