File size: 4,236 Bytes
281711d 1c33a6b 281711d 2982a51 281711d 3e3ca09 b20af37 b8be656 281711d 51aaefc 281711d 63bdadc 50e75cf 956b725 1c33a6b 63bdadc 2a5d0b4 1ff7bc3 2982a51 b8be656 2982a51 82c5741 50e75cf 82c5741 281711d 20a6e65 63bdadc 20a6e65 1ff7bc3 63bdadc 1e4ed96 3e3ca09 20a6e65 d6d49d1 6736504 d6d49d1 6736504 3e3ca09 d6d49d1 20a6e65 b8be656 20a6e65 b8be656 e8b7916 1c33a6b e8b7916 1e4ed96 e8b7916 1e4ed96 b8be656 82c5741 b8be656 50e75cf b8be656 e8b7916 1c33a6b 82c5741 1c33a6b 3e3ca09 1c33a6b 3e3ca09 d6d49d1 6736504 d6d49d1 281711d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 |
import pathlib
from pathlib import Path
import tempfile
from typing import BinaryIO, Literal
import json
import pandas as pd
import gradio as gr
from datasets import load_dataset
from huggingface_hub import upload_file, hf_hub_download
from gradio_leaderboard import ColumnFilter, Leaderboard, SelectColumns
from evaluation import evaluate_problem
from datetime import datetime
import os
from submit import submit_boundary
from about import PROBLEM_TYPES, TOKEN, CACHE_PATH, API, submissions_repo, results_repo
from utils import read_boundary, write_results, get_user
def evaluate_boundary(filename):
local_path = read_boundary(filename)
with Path(local_path).open("r") as f:
raw = f.read()
data_dict = json.loads(raw)
result = evaluate_problem(data_dict['problem_type'], local_path)
write_results(data_dict, result)
return
def get_leaderboard():
ds = load_dataset(results_repo, split='train')
df = pd.DataFrame(ds)
score_field = "score" if "score" in df.columns else "objective" # fallback
df = df.sort_values(by=score_field, ascending=True)
return df
def show_output_box(message):
return gr.update(value=message, visible=True)
def gradio_interface() -> gr.Blocks:
with gr.Blocks() as demo:
with gr.Tabs(elem_classes="tab-buttons"):
with gr.TabItem("Leaderboard", elem_id="boundary-benchmark-tab-table"):
gr.Markdown("# Boundary Design Leaderboard")
leaderboard_df = get_leaderboard()
Leaderboard(
value=leaderboard_df,
select_columns=["submission_time", "feasibility", "score", "objective", "user"],
search_columns=["submission_time", "score", "user"],
hide_columns=["result_filename", "submission_filename", "minimize_objective", "boundary_json", "evaluated"],
filter_columns=["problem_type"],
)
# def update_leaderboard(problem_type):
# return get_leaderboard(problem_type)
# leaderboard_type.change(fn=update_leaderboard, inputs=leaderboard_type, outputs=leaderboard_df)
with gr.TabItem("About", elem_id="boundary-benchmark-tab-table"):
gr.Markdown(
"""
# Welcome to the Fusion Challenge!
Upload your plasma boundary JSON and select the problem type to get your score.
"""
)
with gr.TabItem("Submit", elem_id="boundary-benchmark-tab-table"):
gr.Markdown(
"""
# Plasma Boundary Evaluation Submission
Upload your plasma boundary JSON and select the problem type to get your score.
"""
)
user_state = gr.State(value=None)
filename = gr.State(value=None)
eval_state = gr.State(value=None)
gr.LoginButton()
demo.load(get_user, inputs=None, outputs=user_state)
with gr.Row():
problem_type = gr.Dropdown(PROBLEM_TYPES, label="Problem Type")
boundary_file = gr.File(label="Boundary JSON File (.json)")
boundary_file
message = gr.Textbox(label="Submission Status", lines=3, visible=False)
submit_btn = gr.Button("Evaluate")
submit_btn.click(
submit_boundary,
inputs=[problem_type, boundary_file, user_state],
outputs=[message, filename],
).then(
fn=show_output_box,
inputs=[message],
outputs=[message],
).then(
fn=evaluate_boundary,
inputs=[filename],
outputs=[eval_state]
)
'''.then(
fn=update_leaderboard,
inputs=[problem_type],
outputs=[leaderboard_df]
)'''
return demo
if __name__ == "__main__":
gradio_interface().launch()
|