complex_shift_autoencoder.py [310:330]:
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        train_loss, valid_loss = self.train(
            loss_func, learning_rate, n_epochs, log_frequency
        )

        train_mse = self.compute_mean_loss(loss_func, self.data.train_loader)
        print(f"Train MSE: {train_mse}")
        valid_mse = self.compute_mean_loss(loss_func, self.data.valid_loader)
        print(f"Valid MSE: {valid_mse}")
        test_mse = self.compute_test_loss(loss_func, self.data.test_loader_batch_100)
        print(f"Test MSE: {test_mse}")
        return train_loss, valid_loss, train_mse, valid_mse, test_mse

    def update_state(self, mse, epoch):
        self.best_mse = mse
        self.best_epoch = epoch

    def load_model(self, path_to_checkpoint):
        checkpoint = torch.load(path_to_checkpoint)
        self.best_epoch = checkpoint["best_epoch"]
        self.encoder.load_state_dict(checkpoint["encoder_state_dict"])
        self.decoder.load_state_dict(checkpoint["decoder_state_dict"])
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weakly_complex_shift_autoencoder.py [379:399]:
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        train_loss, valid_loss = self.train(
            loss_func, learning_rate, n_epochs, log_frequency
        )

        train_mse = self.compute_mean_loss(loss_func, self.data.train_loader)
        print(f"Train MSE: {train_mse}")
        valid_mse = self.compute_mean_loss(loss_func, self.data.valid_loader)
        print(f"Valid MSE: {valid_mse}")
        test_mse = self.compute_test_loss(loss_func, self.data.test_loader_batch_100)
        print(f"Test MSE: {test_mse}")
        return train_loss, valid_loss, train_mse, valid_mse, test_mse

    def update_state(self, mse, epoch):
        self.best_mse = mse
        self.best_epoch = epoch

    def load_model(self, path_to_checkpoint):
        checkpoint = torch.load(path_to_checkpoint)
        self.best_epoch = checkpoint["best_epoch"]
        self.encoder.load_state_dict(checkpoint["encoder_state_dict"])
        self.decoder.load_state_dict(checkpoint["decoder_state_dict"])
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