class_docstr: Cox Partial Likelihood
class_docstr_tok: ["Cox","Partial","Likelihood"]
docstr: Compute the partial likelihood of prediction ``y_pred`` and ``y``.
docstr_tok: ["Compute","the","partial","likelihood","of","prediction","``","y_pred","``","and","``","y","``","."]
code: def __call__(
      self, y, raw_predictions, sample_weight=None
  ):  # pylint: disable=unused-argument
      """Compute the partial likelihood of prediction ``y_pred`` and ``y``."""
      # TODO add support for sample weights
      return coxph_loss(
          y["event"].astype(np.uint8),
          y["time"],
          raw_predictions.ravel(),
      )
  
imports: from abc import ABCMeta
  import numpy
  from sklearn.dummy import DummyRegressor
  from sklearn.ensemble._gb_losses import RegressionLossFunction
  from sklearn.utils.extmath import squared_norm
  from ..nonparametric import ipc_weights
  from ._coxph_loss import coxph_loss, coxph_negative_gradient
label_desc: Use image node_id 1 for calling the CoxPH obj's underlying member method code with example usage: obj.__call__(y, raw_predictions, sample_weight) and returns: coxph_loss