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AdityaGirishPawate authored Oct 2, 2020
1 parent e57c95c commit 35debde
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1 change: 1 addition & 0 deletions RUN_model.ipynb

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28 changes: 28 additions & 0 deletions paths.py
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from pathlib import Path
MODE_TRAIN = "train"
MODE_DEV = "dev"
MODE_TEST = "test"

def get_path_df_scores(mode: str, clean_trn: bool = False) -> str:
path = f"df_scores_{mode}.csv"
if clean_trn:
path = "unshuffled_undropped_" + path
return path

def get_path_predict(mode: str) -> str:
f = {
MODE_TRAIN: "predict_trn.txt",
MODE_DEV: "predict_dev.txt",
MODE_TEST: "predict.txt",
}[mode]
print(f"Mode: {mode}, predict file will be saved to: {f}")
return f

def get_path_q(path_data: Path, mode: str) -> Path:
file_q = {
MODE_TRAIN: "questions_train.tsv",
MODE_DEV: "questions_dev.tsv",
MODE_TEST: "questions_test.tsv",
}[mode]
return path_data.joinpath("raw/questions", file_q)

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