def train()

in sing/fondation/trainer.py [0:0]

• 18 lines of code
• 6 McCabe index (conditional complexity)

    def train(self):
        """
        Train :attr:`model` for :attr:`epochs`
        """
        last_epoch, state = utils.load_checkpoint(self.checkpoint_path)
        if state is not None:
            self.model.load_state_dict(state, strict=False)
        start_epoch = last_epoch + 1
        if start_epoch > self.epochs:
            raise ValueError(("Checkpoint has been trained for {} "
                              "epochs but we aim for {} epochs").format(
                                  start_epoch, self.epochs))
        if start_epoch > 0:
            print("Resuming training at epoch {}".format(start_epoch))
        for epoch in range(start_epoch, self.epochs):
            self._train_epoch(self.train_dataset, epoch)
            utils.save_checkpoint(self.checkpoint_path, epoch,
                                  self.model.state_dict())
            with torch.no_grad():
                for name, dataset in self.eval_datasets.items():
                    self._eval_dataset(name, dataset, epoch)