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import logging |
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import pathlib |
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import gradio as gr |
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import pandas as pd |
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from gt4sd.algorithms.conditional_generation.reinvent import Reinvent, ReinventGenerator |
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from gt4sd.algorithms.registry import ApplicationsRegistry |
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from utils import draw_grid_generate |
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logger = logging.getLogger(__name__) |
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logger.addHandler(logging.NullHandler()) |
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def run_inference( |
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algorithm_version: str, |
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smiles: str, |
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length: float, |
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sample_uniquely: bool, |
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number_of_samples: int, |
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): |
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config = ReinventGenerator( |
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algorithm_version=algorithm_version, |
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max_sequence_length=length, |
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randomize=True, |
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sample_uniquely=sample_uniquely, |
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) |
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model = Reinvent(config, target=smiles) |
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samples = list(model.sample(number_of_samples)) |
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return draw_grid_generate(samples=samples, n_cols=5, seeds=[smiles]) |
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if __name__ == "__main__": |
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all_algos = ApplicationsRegistry.list_available() |
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algos = [ |
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x["algorithm_version"] |
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for x in list(filter(lambda x: "Reinvent" in x["algorithm_name"], all_algos)) |
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] |
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metadata_root = pathlib.Path(__file__).parent.joinpath("model_cards") |
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examples = pd.read_csv(metadata_root.joinpath("examples.csv"), header=None).fillna( |
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"" |
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) |
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with open(metadata_root.joinpath("article.md"), "r") as f: |
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article = f.read() |
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with open(metadata_root.joinpath("description.md"), "r") as f: |
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description = f.read() |
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demo = gr.Interface( |
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fn=run_inference, |
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title="REINVENT", |
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inputs=[ |
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gr.Dropdown( |
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algos, |
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label="Algorithm version", |
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value="v0", |
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), |
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gr.Textbox( |
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label="Primer SMILES", |
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placeholder="FP(F)F.CP(C)c1ccccc1.[Au]", |
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lines=1, |
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), |
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gr.Slider( |
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minimum=5, |
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maximum=400, |
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value=100, |
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label="Maximal sequence length", |
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step=1, |
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), |
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gr.Radio(choices=[True, False], label="Sampling uniquely", value=True), |
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gr.Slider( |
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minimum=1, maximum=50, value=10, label="Number of samples", step=1 |
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), |
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], |
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outputs=gr.HTML(label="Output"), |
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article=article, |
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description=description, |
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examples=examples.values.tolist(), |
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) |
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demo.launch(debug=True, show_error=True) |
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