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Create constant.py

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constant.py ADDED
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+ LEADERBOARD_INTRODUCTION = """
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+ # DD-Ranking Leaderboard
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+
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+ 🏆 Welcome to the leaderboard of the **DD-Ranking**! [![Code](https://img.shields.io/github/stars/NUS-HPC-AI-Lab/DD-Ranking.svg?style=social&label=Official)](https://github.com/NUS-HPC-AI-Lab/DD-Ranking)
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+
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+ **Join Leaderboard**: Please see the [instructions]() to participate.
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+ """
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+
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+ CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
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+ CITATION_BUTTON_TEXT = r"""
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+
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+ """
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+
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+ IPC_INFO = """
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+ Images Per Class
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+ """
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+
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+ LABEL_TYPE_INFO = """
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+ Hard labels are categorical, having the same format of the real dataset. Soft labels are distributions, typically generated by a pre-trained teacher model.
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+ """
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+
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+ DATASET_LIST = ["CIFAR-10", "CIFAR-100", "Tiny-ImageNet"]
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+ IPC_LIST = ["IPC-1", "IPC-10", "IPC-50"]
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+ LABEL_TYPE_LIST = ["Hard Label", "Soft Label"]
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+
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+ COLUMN_NAMES = ["Method", "Verified", "Date", "Recovery", "Improvement", "Score"]
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+ DATA_TITLE_TYPE = ['markdown', 'markdown', 'markdown', 'number', 'number', 'number']
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+
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+ DATASET_MAPPING = {
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+ "CIFAR-10": 0,
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+ "CIFAR-100": 1,
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+ "Tiny-ImageNet": 2,
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+ }
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+
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+ IPC_MAPPING = {
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+ "IPC-1": 0,
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+ "IPC-10": 1,
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+ "IPC-50": 2,
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+ }
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+
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+ LABEL_MAPPING = {
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+ "Hard Label": 0,
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+ "Soft Label": 1,
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+ }