Hello folks,
I want to retrain a custom model with my data. I can load the pretrained weights (.pth file) into the model in Pytorch and it runs but I want more functionality and refactored the code into Pytorch Lightning. I am having trouble loading the pretrained weight into the Pytorch Lightning model. The Pytorch Lightning code works but I have limited data and don’t have enough data to train from scratch.
Pytorch Model:
class BDRAR(nn.Module):
      def __init__(self, stat=1):
          super(BDRAR, self).__init__()
          resnext = ResNeXt101()
          self.layer0 = resnext.layer0
          self.layer1 = resnext.layer1
          self.layer2 = resnext.layer2
          self.layer3 = resnext.layer3
          self.layer4 = resnext.layer4

My Lightning model looks like this:
 class liteBDRAR(pl.LightningModule):
         def __init__(self):
              super(liteBDRAR, self).__init__()
              self.model = BDRAR()
              print('Model Created!')

         def forward(self, x):
              return self.model(x)

My run:
KeyError: 'state_dict 
path = './ckpt/BDRAR/3000.pth'
bdrar = liteBDRAR.load_from_checkpoint(path,  strict=False)
trainer = pl.Trainer(fast_dev_run=True, gpus=1)
trainer.fit(bdrar)

I get the following error:
    "keys = model.load_state_dict(checkpoint["state_dict"], strict=strict) **KeyError: 'state_dict**'"

I will appreciate any help. Thank you so much.
@williamFalcon