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import os
import regex as re
import gradio as gr
import pandas as pd
from gradio.themes.utils.sizes import text_md
from gradio_modal import Modal
from content import (
HEADER_MARKDOWN,
LEADERBOARD_TAB_TITLE_MARKDOWN,
SUBMISSION_TAB_TITLE_MARKDOWN,
MODAL_SUBMIT_MARKDOWN,
SUBMISSION_DETAILS_MARKDOWN,
RANKING_AFTER_SUBMISSION_MARKDOWN,
MORE_DETAILS_MARKDOWN,
)
from server import LeaderboardServer
leaderboard_server = LeaderboardServer()
SUBMISSION_INPUTS = dict.fromkeys((
"team_name",
"model_name",
"model_type",
"parameters",
"input_length",
"precision",
"description",
"link_to_model",
"submission_file",
)).keys()
def on_submit_pressed():
return gr.update(value='Processing submission...', interactive=False)
def validate_submission_inputs(**inputs):
if any(key for key, value in inputs.items() if key != "description" and value in (None, "")):
raise ValueError('Please fill in all fields (only the description field is optional)')
if not os.path.exists(inputs["submission_file"]):
raise ValueError('File does not exist')
if not (inputs["link_to_model"].startswith("http://") or inputs["link_to_model"].startswith("https://")):
raise ValueError('Link does not starts with "http://" or "https://"')
if not inputs["parameters"] > 0:
raise ValueError('Attribute `Parameters (B)` should be greater than zero')
if not (inputs["input_length"] > 0 and inputs["input_length"] == int(inputs["input_length"])):
raise ValueError('Attribute `Input length (# tokens)` should be greater than zero and integer type')
def process_submission(*inputs):
try:
inputs = dict(zip(SUBMISSION_INPUTS, inputs))
for key in inputs:
if key in ("team_name", "model_name"):
inputs[key] = re.sub(r"""\s+""", " ", inputs[key]).strip()
elif key in ("description", "link_to_model"):
inputs[key] = inputs[key].strip()
validate_submission_inputs(**inputs)
metadata = SUBMISSION_INPUTS - {"submission_file"}
metadata = {key: inputs[key] for key in metadata}
gr.Info('Submission valid, running tournament...')
pre_submit = leaderboard_server.prepare_model_for_submission(inputs["submission_file"], metadata)
except ValueError as err:
gr.Warning(str(err))
return (
gr.update(value='Pre-submit model', visible=True, interactive=True),
gr.update(visible=False),
gr.update(visible=False),
gr.update(visible=False),
gr.update(visible=False),
gr.update(visible=False),
)
except Exception as err:
gr.Warning(str(err), duration=None)
return (
gr.update(value='Pre-submit model', visible=True, interactive=True),
gr.update(visible=False),
gr.update(visible=False),
gr.update(visible=False),
gr.update(visible=False),
gr.update(visible=False),
)
return (
gr.update(visible=False),
gr.update(visible=True),
gr.update(interactive=True, visible=True),
gr.update(interactive=True, visible=True),
gr.update(visible=True),
gr.update(
value=leaderboard_server.get_leaderboard(pre_submit),
visible=True,
datatype="markdown",
elem_classes="leaderboard-table",
),
)
def submit_results():
leaderboard_server.save_pre_submit()
leaderboard_server.update_leaderboard()
gr.Info('Submission successful!')
return (
gr.update(value='Pre-submit model', visible=True, interactive=True),
gr.update(visible=False),
gr.update(visible=False),
gr.update(visible=False),
gr.update(visible=False),
gr.update(visible=False),
gr.DataFrame(value=leaderboard_server.get_leaderboard(category=leaderboard_server.tasks_category_overall), visible=True),
gr.update(visible=False),
gr.update(choices=leaderboard_server.submission_ids),
gr.update(value=leaderboard_server.tasks_category_overall),
)
def erase_pre_submit():
with leaderboard_server.pre_submit_lock:
if leaderboard_server.pre_submit:
leaderboard_server.pre_submit = None # NOTE: Is it safe? How to confirm that `submission_id` is equal?
return (
gr.update(value='Pre-submit model', visible=True, interactive=True),
gr.update(visible=False),
gr.update(visible=False),
gr.update(visible=False),
gr.update(visible=False),
gr.update(visible=False),
gr.update(visible=False),
)
def fetch_model_detail(submission_id):
metadata = leaderboard_server.get_model_detail(submission_id)
return (
gr.update(value=metadata['description'], visible=True),
gr.update(value=metadata['link_to_model'], visible=True)
)
def change_leaderboard_category(category):
return gr.update(
value=leaderboard_server.get_leaderboard(category=category),
visible=True,
datatype="markdown",
)
def show_modal():
return gr.update(visible=True)
def hide_modal():
return gr.update(visible=False)
def on_application_load():
leaderboard_server.update_leaderboard()
return (
gr.DataFrame(value=leaderboard_server.get_leaderboard(category=leaderboard_server.tasks_category_overall), visible=True),
gr.update(choices=leaderboard_server.submission_ids),
gr.update(value=leaderboard_server.tasks_category_overall),
)
custom_css = """
footer {visibility: hidden}
.leaderboard-table tr:first-child th {
background-color: var(--table-even-background-fill);
}
.leaderboard-table th:first-child, .leaderboard-table td:first-child {
position: sticky;
left: 0;
z-index: 1;
background-color: inherit;
}
.leaderboard-table th:nth-child(2), .leaderboard-table td:nth-child(2) {
position: sticky;
left: var(--cell-width-0);
z-index: 1;
background-color: inherit;
}
.leaderboard-table th:nth-child(3), .leaderboard-table td:nth-child(3) {
position: sticky;
left: calc(var(--cell-width-0) + var(--cell-width-1));
z-index: 1;
background-color: inherit;
}
.leaderboard-table th:nth-child(4), .leaderboard-table td:nth-child(4) {
position: sticky;
left: calc(var(--cell-width-0) + var(--cell-width-1) + var(--cell-width-2));
z-index: 1;
background-color: inherit;
}
.leaderboard-table th:nth-child(5), .leaderboard-table td:nth-child(5) {
position: sticky;
left: calc(var(--cell-width-0) + var(--cell-width-1) + var(--cell-width-2) + var(--cell-width-3));
z-index: 1;
background-color: inherit;
}
.leaderboard-table th:nth-child(5)::after, .leaderboard-table td:nth-child(5)::after {
box-shadow: inset 5px 0px 4px -4px var(--border-color-primary);
position: absolute;
top: 0;
right: 0;
bottom: -1px;
content: "";
width: 30px;
transform: translateX(100%);
}
"""
with gr.Blocks(theme=gr.themes.Soft(text_size=text_md), css=custom_css) as main:
gr.Markdown(HEADER_MARKDOWN)
with gr.Tabs():
with gr.TabItem('Leaderboard'):
with gr.Column():
gr.Markdown(LEADERBOARD_TAB_TITLE_MARKDOWN)
with gr.Row():
category_of_tasks = gr.Dropdown(
choices=[leaderboard_server.tasks_category_overall] + list(leaderboard_server.tasks_categories),
value=leaderboard_server.tasks_category_overall,
label="Category of benchmarks",
interactive=True,
)
with gr.Row():
results_table = gr.DataFrame(
leaderboard_server.get_leaderboard(category=leaderboard_server.tasks_category_overall),
interactive=False,
label=None,
visible=True,
datatype="markdown",
elem_classes="leaderboard-table",
)
category_of_tasks.change(
fn=change_leaderboard_category,
inputs=category_of_tasks,
outputs=results_table,
)
with gr.TabItem('Model details'):
gr.Markdown(MORE_DETAILS_MARKDOWN)
detail_dropdown = gr.Dropdown(
choices=leaderboard_server.submission_ids, # TODO: team_name/model_name
label="Select model",
interactive=True,
)
with gr.Row():
model_description = gr.Text(value='', label='Model description', visible=False, interactive=False)
model_url = gr.Text(value='', label='Model url', visible=False, interactive=False)
detail_dropdown.change(
fn=fetch_model_detail,
inputs=[detail_dropdown],
outputs=[model_description, model_url],
)
with gr.TabItem('Submission'):
with gr.Column():
gr.Markdown(SUBMISSION_TAB_TITLE_MARKDOWN)
submission_inputs = dict.fromkeys(SUBMISSION_INPUTS)
with gr.Row():
submission_inputs["team_name"] = gr.Textbox(label='Team name', type='text')
submission_inputs["model_name"] = gr.Textbox(label='Model name', type='text')
submission_inputs["model_type"] = gr.Dropdown(
label="Model type",
choices=("chat", "pretrained", "ensemble"),
)
submission_inputs["parameters"] = gr.Number(
label='Parameters (B)',
value=0.01,
step=0.01,
)
with gr.Row():
submission_inputs["input_length"] = gr.Number(
label='Input length (# tokens)',
value=0,
step=1,
)
submission_inputs["precision"] = gr.Dropdown(
label="Precision",
choices=("float32", "bfloat32", "float16", "bfloat16", "8bit", "4bit"),
)
submission_inputs["description"] = gr.Textbox(label='Description', type='text')
submission_inputs["link_to_model"] = gr.Textbox(label='Link to model', type='text')
submission_inputs["submission_file"] = gr.File(label='Upload your results', type='filepath')
pre_submission_btn = gr.Button(value='Pre-submit model', interactive=True)
submit_prompt = gr.Markdown(
SUBMISSION_DETAILS_MARKDOWN,
visible=False
)
pre_submit_info = gr.Markdown(
RANKING_AFTER_SUBMISSION_MARKDOWN,
visible=False
)
pre_submit_table = gr.DataFrame(pd.DataFrame(), interactive=False, label=None, visible=False)
submission_btn_yes = gr.Button(value='Submit model', interactive=False, visible=False)
submission_btn_no = gr.Button(value='Reverse process', interactive=False, visible=False)
with Modal(visible=False) as modal_submit:
gr.Markdown(MODAL_SUBMIT_MARKDOWN)
modal_submit_yes = gr.Button("Yes", interactive=True)
modal_submit_no = gr.Button("No", interactive=True)
pre_submission_btn.click(
fn=on_submit_pressed,
concurrency_limit=1,
outputs=[pre_submission_btn],
).then(
fn=process_submission,
inputs=list(submission_inputs.values()),
outputs=[
pre_submission_btn,
submit_prompt,
submission_btn_yes,
submission_btn_no,
pre_submit_info,
pre_submit_table,
],
)
submission_btn_yes.click(
fn=show_modal,
outputs=[modal_submit]
)
modal_submit_yes.click(
fn=submit_results,
outputs=[
pre_submission_btn,
submission_btn_yes,
submission_btn_no,
submit_prompt,
pre_submit_info,
pre_submit_table,
results_table,
modal_submit,
detail_dropdown,
category_of_tasks,
],
)
modal_submit_no.click(
fn=hide_modal,
outputs=[modal_submit]
)
submission_btn_no.click(
fn=erase_pre_submit,
outputs=[
pre_submission_btn,
submission_btn_yes,
submission_btn_no,
submit_prompt,
pre_submit_info,
pre_submit_table,
],
)
main.load(
on_application_load,
inputs=None,
outputs=[
results_table,
detail_dropdown,
category_of_tasks,
]
)
main.launch()
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