Add freqairl docker build process
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@@ -133,8 +133,7 @@ class BaseReinforcementLearningModel(IFreqaiModel):
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:param data_dictionary: dict = common data dictionary containing train and test
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features/labels/weights.
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:param prices_train/test: DataFrame = dataframe comprised of the prices to be used in the
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environment during training
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or testing
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environment during training or testing
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:param dk: FreqaiDataKitchen = the datakitchen for the current pair
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"""
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train_df = data_dictionary["train_features"]
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@@ -201,7 +200,7 @@ class BaseReinforcementLearningModel(IFreqaiModel):
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) -> Tuple[DataFrame, npt.NDArray[np.int_]]:
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"""
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Filter the prediction features data and predict with it.
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:param: unfiltered_dataframe: Full dataframe for the current backtest period.
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:param unfiltered_dataframe: Full dataframe for the current backtest period.
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:return:
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:pred_df: dataframe containing the predictions
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:do_predict: np.array of 1s and 0s to indicate places where freqai needed to remove
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