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import os | |
import gradio as gr | |
import uuid | |
import shutil | |
from openvideo import push_file_to_hf | |
try: | |
import ml4co_kit | |
except: | |
os.system("pip install ml4co-kit-0.0.2a1.tar.gz") | |
import ml4co_kit | |
from ml4co_kit import CVRPPyVRPSolver | |
from ml4co_kit import CVRPDataGenerator | |
FILEPATH = "data/cvrp/uniform/cvrp100_uniform.txt" | |
def handle( | |
hf_token: str | |
): | |
cur_iter = 0 | |
max_iter = 1000 | |
while(cur_iter < max_iter): | |
solver = CVRPPyVRPSolver(time_limit=60) | |
gen = CVRPDataGenerator( | |
num_threads=8, | |
nodes_num=100, | |
min_capacity=50, | |
max_capacity=50, | |
solver=solver, | |
train_samples_num=160, | |
val_samples_num=0, | |
test_samples_num=0 | |
) | |
gen.generate() | |
filename = uuid.uuid4().hex[:9] + ".txt" | |
push_file_to_hf( | |
hf_token=hf_token, | |
hf_repo_id="ML4CO/ML4VRP", | |
file_path=FILEPATH, | |
path_in_repo=filename | |
) | |
shutil.rmtree("data/cvrp") | |
cur_iter = cur_iter + 1 | |
with gr.Blocks() as demo: | |
gr.Markdown( | |
''' | |
VRP Data Generating | |
''' | |
) | |
hf_token = gr.Textbox(label="HuggingFace Token") | |
with gr.Row(): | |
button = gr.Button("Submit", variant="primary") | |
clear = gr.Button("Clear") | |
button.click( | |
handle, | |
[hf_token], | |
outputs=None | |
) | |
if __name__ == "__main__": | |
demo.launch(debug = True) |