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, going to queue for the 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!') with leaderboard_server.var_lock.ro: leaderboard = leaderboard_server.get_leaderboard(category=leaderboard_server.TASKS_CATEGORY_OVERALL) submission_ids = leaderboard_server.submission_ids 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, visible=True), gr.update(visible=False), gr.update(choices=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.DataFrame( 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() with leaderboard_server.var_lock.ro: 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 td:first-child p { margin: 0px; } .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) with leaderboard_server.var_lock.ro: 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, outputs=[pre_submission_btn], ).then( # TODO: Zjistit proč to neběží konkurentně. 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()