reagent/ope/estimators/slate_estimators.py [1393:1421]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        return EstimatorSampleResult(
            sample.log_reward,
            sample.log_reward * weight,
            sample.ground_truth_reward,
            weight,
        )

    # pyre-fixme[14]: `evaluate` overrides method defined in `Estimator` inconsistently.
    def evaluate(
        self, input: SlateEstimatorInput, *kwargs
    ) -> Optional[EstimatorResult]:
        input.validate()
        log_avg = RunningAverage()
        tgt_avg = RunningAverage()
        acc_weight = RunningAverage()
        gt_avg = RunningAverage()
        zw = 0
        for sample in input.samples:
            result = self._evaluate_sample(sample)
            if result is None:
                zw += 1
                continue
            log_avg.add(result.log_reward)
            tgt_avg.add(result.target_reward)
            gt_avg.add(result.ground_truth_reward)
            acc_weight.add(result.weight)
            if result.weight == 0.0:
                zw += 1
            if tgt_avg.count % 1000 == 0:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



reagent/ope/estimators/slate_estimators.py [1495:1523]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        return EstimatorSampleResult(
            sample.log_reward,
            sample.log_reward * weight,
            sample.ground_truth_reward,
            weight,
        )

    # pyre-fixme[14]: `evaluate` overrides method defined in `Estimator` inconsistently.
    def evaluate(
        self, input: SlateEstimatorInput, *kwargs
    ) -> Optional[EstimatorResult]:
        input.validate()
        log_avg = RunningAverage()
        tgt_avg = RunningAverage()
        acc_weight = RunningAverage()
        gt_avg = RunningAverage()
        zw = 0
        for sample in input.samples:
            result = self._evaluate_sample(sample)
            if result is None:
                zw += 1
                continue
            log_avg.add(result.log_reward)
            tgt_avg.add(result.target_reward)
            gt_avg.add(result.ground_truth_reward)
            acc_weight.add(result.weight)
            if result.weight == 0.0:
                zw += 1
            if tgt_avg.count % 1000 == 0:
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