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import os |
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import matplotlib as mpl |
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import matplotlib.pyplot as plt |
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import pandas as pd |
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from random import shuffle, seed |
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model_size = { |
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"T5\textsubscript{SMALL}": [60, "T5"], |
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"T5\textsubscript{BASE}": [200, "T5"], |
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"T5\textsubscript{LARGE}": [770, "T5"], |
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"T5\textsubscript{XL}": [3000, "T5"], |
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"T5\textsubscript{XXL}": [11000, "T5"], |
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"Flan-T5\textsubscript{SMALL}": [60, "Flan-T5"], |
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"Flan-T5\textsubscript{BASE}": [200, "Flan-T5"], |
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"Flan-T5\textsubscript{LARGE}": [770, "Flan-T5"], |
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"Flan-T5\textsubscript{XL}": [3000, "Flan-T5"], |
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"Flan-T5\textsubscript{XXL}": [11000, "Flan-T5"], |
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"OPT\textsubscript{125M}": [125, "OPT"], |
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"OPT\textsubscript{350M}": [350, "OPT"], |
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"OPT\textsubscript{1.3B}": [1300, "OPT"], |
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"OPT\textsubscript{2.7B}": [2700, "OPT"], |
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"OPT\textsubscript{6.7B}": [6700, "OPT"], |
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"OPT\textsubscript{13B}": [13000, "OPT"], |
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"OPT\textsubscript{30B}": [30000, "OPT"], |
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"OPT\textsubscript{66B}": [66000, "OPT"], |
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"OPT-IML\textsubscript{1.3B}": [1300, "OPT-IML"], |
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"OPT-IML\textsubscript{30B}": [30000, "OPT-IML"], |
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} |
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lm_list = ['T5', 'Flan-T5', 'OPT', 'OPT-IML'] |
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df_oracle = pd.read_csv("results/oracle.csv", index_col=0) |
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os.makedirs('figures/main', exist_ok=True) |
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plt.rcParams.update({'font.size': 16}) |
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def main(target_relation: str = "average", prompt_type: str = "lc"): |
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df = pd.read_csv(f"results/lm_{prompt_type}/lm.csv") |
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df.index = df.pop("model") |
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df = (df * 100).round(1) |
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df = df[[i in model_size for i in df.index]] |
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df["size"] = [model_size[i][0] * 1000000 for i in df.index] |
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df["lm"] = [model_size[i][1] for i in df.index] |
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df_target = df[[target_relation, "size", "lm"]] |
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out = df_target.pivot_table(index='size', columns='lm', aggfunc='mean') |
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out.columns = [i[1] for i in out.columns] |
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out = out.reset_index() |
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out = out[['size'] + lm_list] |
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styles = ['o-', '^--', 'X:', "P:"] |
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seed(1) |
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colors = list(mpl.colormaps['tab20b'].colors) |
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shuffle(colors) |
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ax = None |
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for n, c in enumerate(lm_list): |
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tmp = out[['size', c]].dropna().reset_index() |
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ax = tmp.plot.line(y=c, x='size', xlabel='Model Size', ylabel="Correlation", ax=ax, color=colors[n], |
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style=styles[n], label=c, logx=True, grid=True) |
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plt.tight_layout() |
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plt.savefig(f"figures/main/{prompt_type}.{target_relation.replace(' ', '_').replace('/', '-')}.landscape.png", bbox_inches="tight", dpi=600) |
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if __name__ == '__main__': |
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for p in ['lc', 'qa']: |
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main('average', p) |
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main("competitor/rival of", p) |
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main("friend/ally of", p) |
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main("influenced by", p) |
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main("known for", p) |
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main("similar to", p) |
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