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import gradio as gr
import src.dependency # noqa
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.yaml")
demo = gr.Blocks(
css=custom_css,
theme=gr.themes.Default(primary_hue="indigo", secondary_hue="indigo"),
)
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_value,
# subsets_value,
# backends_value,
# hardware_type_value,
# score_slider,
# memory_slider,
# backend_checkboxes,
# datatype_checkboxes,
# optimization_checkboxes,
# quantization_checkboxes,
# kernels_checkboxes,
# ) = create_control_panel(
# machine=config.machine,
# subsets=config.subsets,
# backends=config.backends,
# hardware_type=config.hardware_type,
# 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,
# backends=config.backends,
# hardware_type=config.hardware_type,
# )
# ####################### LEADERBOARD TAB #######################
# with gr.TabItem("Leaderboard 🏅", id=0):
# search_bar, columns_checkboxes, leaderboard_table = (
# create_leaderboard_table(open_llm_perf_df)
# )
# with gr.TabItem("Find Your Best Model 🧭", id=1):
# lat_score_mem_plot = create_lat_score_mem_plot(
# open_llm_perf_df
# )
# ###################### ATTENTIONS SPEEDUP TAB #######################
# # with gr.TabItem("Attention 📈", id=2):
# # attn_prefill_plot, attn_decode_plot = create_attn_plots(
# # open_llm_perf_df
# # )
# # ####################### KERNELS SPEEDUP TAB #######################
# # with gr.TabItem("Kernels 📈", 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_value,
# subsets_value,
# backends_value,
# hardware_type_value,
# 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_value,
# subsets_value,
# backends_value,
# hardware_type_value,
# # interactive
# columns_checkboxes,
# search_bar,
# # outputs
# leaderboard_table,
# )
# ####################### ABOUT TAB #######################
# with gr.TabItem("About 📖", id=len(configs)):
# gr.Markdown(ABOUT, elem_classes="descriptive-text")
# ####################### CITATION
# with gr.Row():
# with gr.Accordion("📙 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__":
demo.queue().launch(ssr_mode=False)
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