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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 check_arrays_survival(X, y, **kwargs):
 """Check that all arrays have consistent first dimensions. Parameters X : array-like Data matrix containing feature vectors. y : structured array with two fields A structured array containing the binary event indicator as first field, and time of event or time of censoring as second field. kwargs : dict Additional arguments passed to :func:`sklearn.utils.check_array`. Returns ------- X : array, shape=[n_samples, n_features] Feature vectors. event : array, shape=[n_samples,], dtype=bool Binary event indicator. time : array, shape=[n_samples,], dtype=float Time of event or censoring. """

    event, time = check_y_survival(y)
    kwargs.setdefault("dtype", numpy.float64)
    X = check_array(X, ensure_min_samples=2, **kwargs)
    check_consistent_length(X, event, time)
    return X, event, time