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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.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,
)
# from custom_kernels import create_quant_krnl_plots
MACHINE_TO_HARDWARE = {
"1xA10": "A10-24GB-150W π₯οΈ",
"1xA100": "A100-80GB-275W π₯οΈ",
# "1xH100": "H100-80GB-700W π₯οΈ",
}
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, (machine, hardware) in enumerate(MACHINE_TO_HARDWARE.items()):
with gr.TabItem(hardware, id=id):
####################### CONTROL PANEL #######################
(
filter_button,
machine_textbox,
score_slider,
memory_slider,
backend_checkboxes,
datatype_checkboxes,
optimization_checkboxes,
quantization_checkboxes,
kernels_checkboxes,
) = create_control_panel(machine=machine)
####################### HARDWARE SUBTABS #######################
with gr.Tabs(elem_classes="subtabs"):
open_llm_perf_df = get_llm_perf_df(machine=machine)
####################### LEADERBOARD TAB #######################
with gr.TabItem("Leaderboard π
", id=0):
search_bar, columns_checkboxes, leaderboard_table = (
create_leaderboard_table(open_llm_perf_df)
)
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,
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,
# interactive
columns_checkboxes,
search_bar,
# outputs
leaderboard_table,
)
####################### ABOUT TAB #######################
with gr.TabItem("About π", id=3):
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()
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