src/rime/models/rnn.py [35:43]:
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        if load_from_checkpoint is not None:
            self.model.load_state_dict(
                torch.load(load_from_checkpoint)['state_dict'])

        self.trainer = Trainer(
            max_epochs=max_epochs, gpus=gpus,
            callbacks=[self.model._checkpoint, LearningRateMonitor()])
        print("trainer log at:", self.trainer.logger.log_dir)
        self.batch_size = batch_size
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src/rime/models/transformer.py [55:63]:
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        if load_from_checkpoint is not None:
            self.model.load_state_dict(
                torch.load(load_from_checkpoint)['state_dict'])

        self.trainer = Trainer(
            max_epochs=max_epochs, gpus=gpus,
            callbacks=[self.model._checkpoint, LearningRateMonitor()])
        print("trainer log at:", self.trainer.logger.log_dir)
        self.batch_size = batch_size
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