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import json | |
import math | |
import pandas as pd | |
from src.assets.symbols import UP_ARROW, DOWN_ARROW | |
from src.tasks import TASKS, TASK_CODES, TASK_TO_METRIC | |
def load_from_hub(fs, repo_path): | |
files = fs.glob(f"{repo_path}/**/*.json") | |
set_organization_models = {} | |
tasks = {} | |
for file in files: | |
organization, model, task = file.split("/")[-3:] | |
organization_model = f"{organization}/{model}" | |
task_code = task.replace(".json", "") | |
if task_code not in TASK_CODES: | |
continue | |
set_organization_models[organization_model] = 1 | |
tasks[task_code] = 1 | |
table = pd.DataFrame( | |
index=list(set_organization_models.keys()), | |
columns=["Organization", "Model"] + list(tasks.keys()), | |
data=None, | |
) | |
for file in files: | |
organization, model, task = file.split("/")[-3:] | |
organization_model = f"{organization}/{model}" | |
task_code = task.replace(".json", "") | |
if task_code not in TASK_CODES: | |
continue | |
data = json.loads(fs.open(file, "r").read()) | |
result = round(data["results"][task_code][TASK_TO_METRIC[task_code]], 4) | |
table.loc[organization_model, task_code] = result | |
table.loc[organization_model, "Organization"] = organization | |
table.loc[organization_model, "Model"] = model | |
table.rename(columns={ | |
task.code: f"{task.name} {UP_ARROW if task.higher_is_better else DOWN_ARROW}" | |
for task in TASKS}, inplace=True) | |
return table |