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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 |