Source code for nvflare.app_opt.xgboost.histogram_based_v2.csv_data_loader

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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#     http://www.apache.org/licenses/LICENSE-2.0
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import xgboost as xgb

from nvflare.app_opt.xgboost.data_loader import XGBDataLoader




class CSVDataLoader(XGBDataLoader):
    def __init__(self, folder: str):
        """Reads CSV dataset and return XGB data matrix.

        Note: if split mode is vertical, we assume the label owner is rank 0.

        Args:
            folder: Folder to find the CSV files
        """
        self.folder = folder



    def load_data(self):

        train_path = f"{self.folder}/{self.client_id}/train.csv"
        valid_path = f"{self.folder}/{self.client_id}/valid.csv"

        if self.rank == 0 or self.data_split_mode == xgb.core.DataSplitMode.ROW:
            label = "&label_column=0"
        else:
            label = ""

        train_data = xgb.DMatrix(train_path + f"?format=csv{label}", data_split_mode=self.data_split_mode)
        valid_data = xgb.DMatrix(valid_path + f"?format=csv{label}", data_split_mode=self.data_split_mode)

        return train_data, valid_data