code: def score(
      self, x: Tensor, y: Tensor, weight: Optional[Tensor] = None
  ) -> float:
      y_pred = self._model.predict(x)
      w = weight.numpy() if weight is not None else None
      return self._score(y.numpy(), y_pred, weight=w)
  
imports: import logging
  import math
  import time
  from typing import Optional
  import numpy
  import torch
  from reagent.ope.estimators.types import PredictResults, Trainer, TrainingData
  from sklearn.linear_model import Lasso, LogisticRegression, SGDClassifier
  from sklearn.metrics import accuracy_score, mean_squared_error
  from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
  from torch import Tensor
label_desc: Use image node_id 4 for calling the LinearTrainer obj's underlying member method code with example usage: obj.score(x, y, weight) and returns: self