similarity_search_experiments/correlate_rank_with_invariance_gap.py [47:64]:
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    def load_df(
        self, data_set_type="train", similarity_type="resnet18_no_aug"
    ) -> pd.DataFrame:
        """Loads dataframe of similarity changes"""
        labels_df = pd.read_csv(
            LABELS_PATH,
            sep=" ",
            names=["class_label", "class_num", "class_name"],
        )

        sub_dir = f"similarity_search_{similarity_type}"
        results_dir = Path(SIM_SEARCH_DIR / f"{sub_dir}").expanduser()
        transform_type = "single_transform"
        df = pd.read_csv(
            results_dir / f"{transform_type}_boosts_{data_set_type}.csv", index_col=0
        )
        df = df.merge(labels_df, on="class_label", how="left")
        df["transform"] = df["transform_name"].str.split(" ").apply(lambda x: x[0])
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wordnet_analysis/wordnet_correlation.py [66:83]:
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    def load_df(
        self, data_set_type="train", similarity_type="resnet18_no_aug"
    ) -> pd.DataFrame:
        """Loads dataframe of similarity changes"""
        labels_df = pd.read_csv(
            LABELS_PATH,
            sep=" ",
            names=["class_label", "class_num", "class_name"],
        )

        sub_dir = f"similarity_search_{similarity_type}"
        results_dir = Path(SIM_SEARCH_DIR / f"{sub_dir}").expanduser()
        transform_type = "single_transform"
        df = pd.read_csv(
            results_dir / f"{transform_type}_boosts_{data_set_type}.csv", index_col=0
        )
        df = df.merge(labels_df, on="class_label", how="left")
        df["transform"] = df["transform_name"].str.split(" ").apply(lambda x: x[0])
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