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Running
on
CPU Upgrade
| import json | |
| import gradio as gr | |
| import pandas as pd | |
| from huggingface_hub import HfFileSystem | |
| from src.constants import RESULTS_DATASET_ID, TASKS | |
| def fetch_result_paths(): | |
| fs = HfFileSystem() | |
| paths = fs.glob(f"{RESULTS_DATASET_ID}/**/**/*.json") | |
| return paths | |
| def filter_latest_result_path_per_model(paths): | |
| from collections import defaultdict | |
| d = defaultdict(list) | |
| for path in paths: | |
| model_id, _ = path[len(RESULTS_DATASET_ID) + 1:].rsplit("/", 1) | |
| d[model_id].append(path) | |
| return {model_id: max(paths) for model_id, paths in d.items()} | |
| def update_load_results_component(): | |
| return gr.Button("Load Results", interactive=True) | |
| def load_results_dataframe(model_id, result_path_per_model=None): | |
| if not model_id or not result_path_per_model: | |
| return | |
| result_path = result_path_per_model[model_id] | |
| fs = HfFileSystem() | |
| with fs.open(result_path, "r") as f: | |
| data = json.load(f) | |
| model_name = data.get("model_name", "Model") | |
| df = pd.json_normalize([{key: value for key, value in data.items()}]) | |
| # df.columns = df.columns.str.split(".") # .split return a list instead of a tuple | |
| return df.set_index(pd.Index([model_name])).reset_index() | |
| def load_results_dataframes(*model_ids, result_path_per_model=None): | |
| return [load_results_dataframe(model_id, result_path_per_model=result_path_per_model) for model_id in model_ids] | |
| def display_results(task, *dfs): | |
| dfs = [df.set_index("index") for df in dfs if "index" in df.columns] | |
| if not dfs: | |
| return None, None | |
| df = pd.concat(dfs) | |
| df = df.T.rename_axis(columns=None) | |
| return display_tab("results", df, task), display_tab("configs", df, task) | |
| def display_tab(tab, df, task): | |
| df = df.style.format(na_rep="") | |
| df.hide( | |
| [ | |
| row | |
| for row in df.index | |
| if ( | |
| not row.startswith(f"{tab}.") | |
| or row.startswith(f"{tab}.leaderboard.") | |
| or row.endswith(".alias") | |
| or (not row.startswith(f"{tab}.{task}") if task != "All" else False) | |
| ) | |
| ], | |
| axis="index", | |
| ) | |
| start = len(f"{tab}.leaderboard_") if task == "All" else len(f"{tab}.{task} ") | |
| df.format_index(lambda idx: idx[start:].removesuffix(",none"), axis="index") | |
| return df.to_html() | |
| def update_tasks_component(): | |
| return gr.Radio( | |
| ["All"] + list(TASKS.values()), | |
| label="Tasks", | |
| info="Evaluation tasks to be displayed", | |
| value="All", | |
| interactive=True, | |
| ) | |
| def clear_results(): | |
| # model_id_1, model_id_2, dataframe_1, dataframe_2, task | |
| return ( | |
| None, None, None, None, | |
| gr.Radio( | |
| ["All"] + list(TASKS.values()), | |
| label="Tasks", | |
| info="Evaluation tasks to be displayed", | |
| value="All", | |
| interactive=False, | |
| ), | |
| ) | |