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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def predict(self, sequences, y=None):
 """Predict the closest cluster each sample in each sequence in sequences belongs to. In the vector quantization literature, `cluster_centers_` is called the code book and each value returned by `predict` is the index of the closest code in the code book. Parameters sequences : list of array-like, each of shape [sequence_length, n_features] A list of multivariate timeseries. Each sequence may have a different length, but they all must have the same number of features. Returns ------- Y : list of arrays, each of shape [sequence_length,] Index of the closest center each sample belongs to. """

        predictions = []
        check_iter_of_sequences(sequences, allow_trajectory=self._allow_trajectory)
        for X in sequences:
            predictions.append(self.partial_predict(X))
        return predictions