import json import gradio as gr import pandas as pd from app import fs from src.constants import SUBTASKS, DETAILS_DATASET_ID, DETAILS_FILENAME def update_subtasks_component(task): return gr.Radio( SUBTASKS.get(task), info="Evaluation subtasks to be displayed", value=None, ) def update_load_details_component(model_id_1, model_id_2, subtask): if (model_id_1 or model_id_2) and subtask: return gr.Button("Load Details", interactive=True) else: return gr.Button("Load Details", interactive=False) def load_details_dataframe(model_id, subtask): if not model_id or not subtask: return model_name_sanitized = model_id.replace("/", "__") paths = fs.glob( f"{DETAILS_DATASET_ID}/**/{DETAILS_FILENAME}".format( model_name_sanitized=model_name_sanitized, subtask=subtask ) ) if not paths: return path = max(paths) with fs.open(path, "r") as f: data = [json.loads(line) for line in f] df = pd.json_normalize(data) # df = df.rename_axis("Parameters", axis="columns") df["model_name"] = model_id # Keep model_name return df # return df.set_index(pd.Index([model_id])).reset_index() def load_details_dataframes(subtask, *model_ids): return [load_details_dataframe(model_id, subtask) for model_id in model_ids] def display_details(sample_idx, *dfs): rows = [df.iloc[sample_idx] for df in dfs if "model_name" in df.columns and sample_idx < len(df)] if not rows: return # Pop model_name and add it to the column name df = pd.concat([row.rename(row.pop("model_name")) for row in rows], axis="columns") return ( df.style .format(na_rep="") # .hide(axis="index") .to_html() ) def update_sample_idx_component(*dfs): maximum = max([len(df) - 1 for df in dfs]) return gr.Number( label="Sample Index", info="Index of the sample to be displayed", value=0, minimum=0, maximum=maximum, visible=True, ) def clear_details(): # model_id_1, model_id_2, details_dataframe_1, details_dataframe_2, details_task, subtask, sample_idx return ( None, None, None, None, None, None, gr.Number(label="Sample Index", info="Index of the sample to be displayed", value=0, minimum=0,visible=False), )