code: def _corr_score(y_true, y, multioutput=None):
      assert multioutput == "raw_values"
      for this_y in (y_true, y):
          if this_y.ndim != 2:
              raise ValueError(
                  f"inputs must be shape (samples, outputs), got {this_y.shape}"
              )
      return np.array(
          [
              pearsonr(y_true[:, ii], y[:, ii])[0]
              for ii in range(y.shape[-1])
          ]
      )
  
imports: import numbers
  import numpy
  from scipy.stats import pearsonr
  from ..fixes import pinv
  from ..utils import _validate_type, fill_doc, verbose
  from .base import BaseEstimator, _check_estimator, get_coef
  from .time_delaying_ridge import TimeDelayingRidge
label_desc: Use image node_id 6 for calling a global function with example usage: _corr_score(y_true, y, multioutput) and returns: np