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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 fit(self, X, y, random_state=np.random):
 """Create constraints from labels and learn the RCA model. Needs num_constraints specified in constructor. Parameters X : (n x d) data matrix each row corresponds to a single instance y : (n) data labels random_state : a random.seed object to fix the random_state if needed. """

    X, y = self._prepare_inputs(X, y, ensure_min_samples=2)
    chunks = Constraints(y).chunks(num_chunks=self.num_chunks,
                                   chunk_size=self.chunk_size,
                                   random_state=random_state)
    return RCA.fit(self, X, chunks)