polymer_blocks / app.py
jannisborn's picture
update
1634315 unverified
raw
history blame
2.12 kB
import logging
import pathlib
import gradio as gr
import pandas as pd
from gt4sd.algorithms.generation.polymer_blocks import (
PolymerBlocksGenerator,
PolymerBlocks,
)
from gt4sd.algorithms.registry import ApplicationsRegistry
from utils import draw_grid_generate
logger = logging.getLogger(__name__)
logger.addHandler(logging.NullHandler())
def run_inference(algorithm_version: str, length: float, number_of_samples: int):
config = PolymerBlocksGenerator(
algorithm_version=algorithm_version,
batch_size=32,
generated_length=length,
)
model = PolymerBlocks(config)
samples = list(model.sample(number_of_samples))
return draw_grid_generate(samples=samples, n_cols=5, seeds=[])
if __name__ == "__main__":
# Preparation (retrieve all available algorithms)
all_algos = ApplicationsRegistry.list_available()
algos = [
x["algorithm_version"]
for x in list(
filter(lambda x: "PolymerBlocks" in x["algorithm_name"], all_algos)
)
]
# Load metadata
metadata_root = pathlib.Path(__file__).parent.joinpath("model_cards")
examples = pd.read_csv(metadata_root.joinpath("examples.csv"), header=None).fillna(
""
)
with open(metadata_root.joinpath("article.md"), "r") as f:
article = f.read()
with open(metadata_root.joinpath("description.md"), "r") as f:
description = f.read()
demo = gr.Interface(
fn=run_inference,
title="Polymer Blocks",
inputs=[
gr.Dropdown(algos, label="Algorithm version", value="v0"),
gr.Slider(
minimum=5,
maximum=400,
value=100,
label="Maximal sequence length",
step=1,
),
gr.Slider(
minimum=1, maximum=50, value=10, label="Number of samples", step=1
),
],
outputs=gr.HTML(label="Output"),
article=article,
description=description,
examples=examples.values.tolist(),
)
demo.launch(debug=True, show_error=True)