reagent/reporting/discrete_crr_reporter.py [21:40]:
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    def __init__(
        self,
        actions: List[str],
        report_interval: int = 100,
        target_action_distribution: Optional[List[float]] = None,
        recent_window_size: int = 100,
    ):
        self.value_list_observers = {}
        self.aggregating_observers = {
            **{
                "cpe_results": IntervalAggregatingObserver(
                    1, agg.ListAggregator("cpe_details")
                ),
            },
            **{
                name: IntervalAggregatingObserver(report_interval, aggregator)
                for name, aggregator in itertools.chain(
                    [
                        ("td_loss", agg.MeanAggregator("td_loss")),
                        ("reward_loss", agg.MeanAggregator("reward_loss")),
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reagent/reporting/discrete_dqn_reporter.py [21:40]:
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    def __init__(
        self,
        actions: List[str],
        report_interval: int = 100,
        target_action_distribution: Optional[List[float]] = None,
        recent_window_size: int = 100,
    ):
        self.value_list_observers = {}
        self.aggregating_observers = {
            **{
                "cpe_results": IntervalAggregatingObserver(
                    1, agg.ListAggregator("cpe_details")
                ),
            },
            **{
                name: IntervalAggregatingObserver(report_interval, aggregator)
                for name, aggregator in itertools.chain(
                    [
                        ("td_loss", agg.MeanAggregator("td_loss")),
                        ("reward_loss", agg.MeanAggregator("reward_loss")),
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