def check_X_y(X, y, accept_sparse=False, dtype='numeric', order=None, copy=False, force_all_finite=True, ensure_2d=True, allow_nd=False, multi_output=False, ensure_min_samples=1, ensure_min_features=1, y_numeric=False, warn_on_dtype=False, estimator=None):
 X = check_array(X, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)
 if multi_output:
  y = check_array(y, 'csr', force_all_finite=True, ensure_2d=False, dtype=None)
 else:
  y = column_or_1d(y, warn=True)
  _assert_all_finite(y)
 if (y_numeric and (y.dtype.kind == 'O')):
  y = y.astype(np.float64)
 check_consistent_length(X, y)
 return (X, y)

def check_X_y ( X , y , accept_sparse = False , dtype = 'numeric' , order = None , copy = False , force_all_finite = True , ensure_2d = True , allow_nd = False , multi_output = False , ensure_min_samples = 1 , ensure_min_features = 1 , y_numeric = False , warn_on_dtype = False , estimator = None ) : X = check_array ( X , accept_sparse , dtype , order , copy , force_all_finite , ensure_2d , allow_nd , ensure_min_samples , ensure_min_features , warn_on_dtype , estimator ) if multi_output : y = check_array ( y , 'csr' , force_all_finite = True , ensure_2d = False , dtype = None ) else : y = column_or_1d ( y , warn = True ) _assert_all_finite ( y ) if ( y_numeric and ( y . dtype . kind == 'O' ) ) : y = y . astype ( np . float64 ) check_consistent_length ( X , y ) return ( X , y )
input validation for standard estimators .