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from omegaconf import DictConfig
import torch.nn as nn
import torch.nn.functional as F
from lightning import LightningModule
from utils import instantiate
class BaseModule(LightningModule):
def __init__(self, config: DictConfig):
super().__init__()
self.config = config
self.model = self.configure_model()
def forward(self, x):
return self.model(x)
def training_step(self, batch, batch_idx):
raise NotImplementedError
def configure_optimizers(self):
raise NotImplementedError |