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| import gradio as gr | |
| from src.assets import custom_css | |
| # from src.attention import create_attn_plots | |
| from src.content import ABOUT, CITATION_BUTTON, CITATION_BUTTON_LABEL, LOGO, TITLE | |
| from src.hardware import load_hardware_configs | |
| from src.leaderboard import create_leaderboard_table | |
| from src.llm_perf import get_llm_perf_df | |
| from src.map import create_lat_score_mem_plot | |
| from src.panel import ( | |
| create_control_callback, | |
| create_control_panel, | |
| create_select_callback, | |
| ) | |
| configs = load_hardware_configs("hardware.yml") | |
| demo = gr.Blocks(css=custom_css) | |
| with demo: | |
| gr.HTML(LOGO, elem_classes="logo") | |
| gr.HTML(TITLE, elem_classes="title") | |
| ####################### HARDWARE TABS ####################### | |
| with gr.Tabs(elem_classes="tabs"): | |
| for id, config in enumerate(configs): | |
| with gr.TabItem(config.description, id=id): | |
| ####################### HARDWARE DETAILS ####################### | |
| if config.detail: | |
| gr.Markdown(config.detail, elem_classes="descriptive-text") | |
| # ####################### CONTROL PANEL ####################### | |
| ( | |
| filter_button, | |
| machine_textbox, | |
| subsets_values, | |
| score_slider, | |
| memory_slider, | |
| backend_checkboxes, | |
| datatype_checkboxes, | |
| optimization_checkboxes, | |
| quantization_checkboxes, | |
| kernels_checkboxes, | |
| ) = create_control_panel(machine=config.machine, subsets=config.subsets, hardware_provider=config.hardware_provider) | |
| ####################### HARDWARE SUBTABS ####################### | |
| with gr.Tabs(elem_classes="subtabs"): | |
| open_llm_perf_df = get_llm_perf_df(machine=config.machine, subsets=config.subsets) | |
| ####################### LEADERBOARD TAB ####################### | |
| with gr.TabItem("Leaderboard π ", id=0): | |
| search_bar, columns_checkboxes, leaderboard_table = ( | |
| create_leaderboard_table(open_llm_perf_df) | |
| ) | |
| if config.hardware_provider != "intel": # TODO intel CPU does not measure the memory requirements correctly, so disable the graph feature until we fix the underlying issue | |
| with gr.TabItem("Find Your Best Model π§", id=1): | |
| lat_score_mem_plot = create_lat_score_mem_plot(open_llm_perf_df) | |
| ###################### ATTENTIONS SPEEDUP TAB ####################### | |
| # with gr.TabItem("Attention π", id=2): | |
| # attn_prefill_plot, attn_decode_plot = create_attn_plots( | |
| # open_llm_perf_df | |
| # ) | |
| # ####################### KERNELS SPEEDUP TAB ####################### | |
| # with gr.TabItem("Kernels π", id=4): | |
| # quant_krnl_prefill_plot, quant_krnl_decode_plot = ( | |
| # create_quant_krnl_plots(llm_perf_df) | |
| # ) | |
| ####################### CONTROL CALLBACK ####################### | |
| create_control_callback( | |
| filter_button, | |
| # inputs | |
| machine_textbox, | |
| subsets_values, | |
| score_slider, | |
| memory_slider, | |
| backend_checkboxes, | |
| datatype_checkboxes, | |
| optimization_checkboxes, | |
| quantization_checkboxes, | |
| kernels_checkboxes, | |
| # interactive | |
| columns_checkboxes, | |
| search_bar, | |
| # outputs | |
| leaderboard_table, | |
| lat_score_mem_plot, | |
| # attn_prefill_plot, | |
| # attn_decode_plot, | |
| # quant_krnl_prefill_plot, | |
| # quant_krnl_decode_plot, | |
| ) | |
| create_select_callback( | |
| # inputs | |
| machine_textbox, | |
| subsets_values, | |
| # interactive | |
| columns_checkboxes, | |
| search_bar, | |
| # outputs | |
| leaderboard_table, | |
| ) | |
| ####################### ABOUT TAB ####################### | |
| with gr.TabItem("About π", id=len(configs)): | |
| gr.Markdown(ABOUT, elem_classes="descriptive-text") | |
| ####################### CITATION | |
| with gr.Row(): | |
| with gr.Accordion("π Citation", open=False): | |
| citation_button = gr.Textbox( | |
| value=CITATION_BUTTON, | |
| label=CITATION_BUTTON_LABEL, | |
| elem_id="citation-button", | |
| show_copy_button=True, | |
| ) | |
| if __name__ == "__main__": | |
| # Launch demo | |
| demo.queue().launch() | |