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import gradio as gr |
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from gradio_leaderboard import Leaderboard, ColumnFilter, SelectColumns |
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import pandas as pd |
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from apscheduler.schedulers.background import BackgroundScheduler |
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from huggingface_hub import snapshot_download |
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from datasets import load_dataset |
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from src.about import ( |
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CITATION_BUTTON_LABEL, |
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CITATION_BUTTON_TEXT, |
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EVALUATION_QUEUE_TEXT, |
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INTRODUCTION_TEXT, |
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TITLE, |
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) |
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from src.display.css_html_js import custom_css |
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from src.display.utils import ( |
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COLS, |
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AutoEvalColumn, |
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fields, |
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) |
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from src.envs import API, EVAL_REQUESTS_PATH, QUEUE_REPO, REPO_ID, TOKEN |
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from src.populate import get_leaderboard_df |
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def restart_space(): |
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API.restart_space(repo_id=REPO_ID) |
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try: |
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print(EVAL_REQUESTS_PATH) |
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snapshot_download( |
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repo_id=QUEUE_REPO, |
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local_dir=EVAL_REQUESTS_PATH, |
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repo_type="dataset", |
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tqdm_class=None, |
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etag_timeout=30, |
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token=TOKEN, |
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) |
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except Exception: |
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restart_space() |
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total_issues = load_dataset("dtcxzyw/llvm-apr-benchmark").num_rows["test"] |
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LEADERBOARD_DF = get_leaderboard_df(EVAL_REQUESTS_PATH, COLS) |
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def init_leaderboard(dataframe): |
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if dataframe is None or dataframe.empty: |
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raise ValueError("Leaderboard DataFrame is empty or None.") |
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return Leaderboard( |
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value=dataframe, |
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datatype=[c.type for c in fields(AutoEvalColumn)], |
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select_columns=SelectColumns( |
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default_selection=[c.name for c in fields(AutoEvalColumn) if c.displayed_by_default], |
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cant_deselect=[c.name for c in fields(AutoEvalColumn) if c.never_hidden], |
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label="Select Columns to Display:", |
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), |
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search_columns=[AutoEvalColumn.method_name.name], |
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hide_columns=[c.name for c in fields(AutoEvalColumn) if c.hidden], |
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filter_columns=[ |
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ColumnFilter(AutoEvalColumn.with_hint.name, type="checkboxgroup", label="Hint"), |
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], |
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bool_checkboxgroup_label="Hide models", |
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interactive=False, |
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) |
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demo = gr.Blocks(css=custom_css) |
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with demo: |
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gr.HTML(TITLE) |
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gr.Markdown(INTRODUCTION_TEXT + f"\nTotal issues: {total_issues}\n", elem_classes="markdown-text") |
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with gr.Tabs(elem_classes="tab-buttons") as tabs: |
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with gr.TabItem("🏅 Leaderboard", elem_id="llm-benchmark-tab-table", id=0): |
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leaderboard = init_leaderboard(LEADERBOARD_DF) |
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with gr.TabItem("🚀 Submission", elem_id="llm-benchmark-tab-table", id=1): |
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gr.Markdown(EVALUATION_QUEUE_TEXT, elem_classes="markdown-text") |
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with gr.Row(): |
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with gr.Accordion("📙 Citation", open=False): |
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citation_button = gr.Textbox( |
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value=CITATION_BUTTON_TEXT, |
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label=CITATION_BUTTON_LABEL, |
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lines=6, |
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elem_id="citation-button", |
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show_copy_button=True, |
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) |
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scheduler = BackgroundScheduler() |
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scheduler.add_job(restart_space, "interval", seconds=1800) |
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scheduler.start() |
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demo.queue(default_concurrency_limit=40).launch() |
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