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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) | |