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| import os | |
| import gradio as gr | |
| import pandas as pd | |
| from huggingface_hub import HfApi | |
| from huggingface_hub import Repository | |
| from apscheduler.schedulers.background import BackgroundScheduler | |
| from src.assets.text_content import * | |
| from src.assets.css_html_js import custom_css, get_window_url_params | |
| OPTIMUM_TOKEN = os.environ.get("OPTIMUM_TOKEN", None) | |
| LLM_PERF_LEADERBOARD_REPO = "optimum/llm-perf-leaderboard" | |
| LLM_PERF_DATASET_REPO = "optimum/llm-perf" | |
| api = HfApi() | |
| def restart_space(): | |
| api.restart_space( | |
| repo_id=LLM_PERF_LEADERBOARD_REPO, token=OPTIMUM_TOKEN | |
| ) | |
| def load_all_info_from_hub(): | |
| llm_perf_repo = None | |
| if OPTIMUM_TOKEN: | |
| llm_perf_repo = Repository( | |
| local_dir="./llm-perf/", | |
| clone_from=LLM_PERF_DATASET_REPO, | |
| token=OPTIMUM_TOKEN, | |
| repo_type="dataset", | |
| ) | |
| llm_perf_repo.git_pull() | |
| return llm_perf_repo | |
| llm_perf_repo = load_all_info_from_hub() | |
| def has_no_nan_values(df, columns): | |
| return df[columns].notna().all(axis=1) | |
| def has_nan_values(df, columns): | |
| return df[columns].isna().any(axis=1) | |
| def get_leaderboard_df(): | |
| if llm_perf_repo: | |
| llm_perf_repo.git_pull() | |
| df = pd.read_csv("./llm-perf/reports/cuda_1_100/inference_report.csv") | |
| return df | |
| original_df = get_leaderboard_df() | |
| leaderboard_df = original_df.copy() | |
| def refresh(): | |
| leaderboard_df = get_leaderboard_df() | |
| return leaderboard_df | |
| demo = gr.Blocks(css=custom_css) | |
| with demo: | |
| gr.HTML(TITLE) | |
| gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text") | |
| with gr.Tabs(elem_classes="tab-buttons") as tabs: | |
| with gr.TabItem("🏅 LLM-Perf Benchmark", elem_id="llm-perf-benchmark-tab-table", id=0): | |
| leaderboard_table_lite = gr.components.Dataframe( | |
| value=leaderboard_df, | |
| headers=leaderboard_df.columns.tolist(), | |
| # datatype=TYPES_LITE, | |
| max_rows=None, | |
| elem_id="leaderboard-table-lite", | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| with gr.Accordion("📙 Citation", open=False): | |
| citation_button = gr.Textbox( | |
| value=CITATION_BUTTON_TEXT, | |
| label=CITATION_BUTTON_LABEL, | |
| elem_id="citation-button", | |
| ).style(show_copy_button=True) | |
| with gr.Column(): | |
| with gr.Accordion("✨ CHANGELOG", open=False): | |
| changelog = gr.Markdown( | |
| CHANGELOG_TEXT, elem_id="changelog-text") | |
| dummy = gr.Textbox(visible=False) | |
| demo.load( | |
| dummy, | |
| tabs, | |
| _js=get_window_url_params, | |
| ) | |
| scheduler = BackgroundScheduler() | |
| scheduler.add_job(restart_space, "interval", seconds=3600) | |
| scheduler.start() | |
| demo.queue(concurrency_count=40).launch() | |