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Update gradio_app.py
Browse files- gradio_app.py +3 -5
gradio_app.py
CHANGED
@@ -51,7 +51,7 @@ def function(model_name: str, num_molecules: int, seed_num: int) -> tuple[PIL.Im
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config = model_configs[model_name]
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config.sample_num = num_molecules
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config.seed =
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inferer = Inference(config)
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scores = inferer.inference() # create scores_df out of this
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@@ -67,13 +67,13 @@ def function(model_name: str, num_molecules: int, seed_num: int) -> tuple[PIL.Im
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with open(new_path) as f:
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inference_drugs = f.read()
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generated_molecule_list = inference_drugs.split("\n")
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rng = random.Random(config.seed)
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if num_molecules > 12:
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selected_molecules = rng.choices(generated_molecule_list, k=12)
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else:
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selected_molecules =
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selected_molecules = [Chem.MolFromSmiles(mol) for mol in selected_molecules if Chem.MolFromSmiles(mol) is not None]
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@@ -126,12 +126,10 @@ with gr.Blocks() as demo:
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maximum=10_000,
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)
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val = random.randint(0, 10000)
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seed_num = gr.Number(
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label="RNG seed value (can be used for reproducibility):",
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precision=0, # integer input
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minimum=0,
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value=val,
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)
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submit_button = gr.Button(
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config = model_configs[model_name]
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config.sample_num = num_molecules
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config.seed = random.randint(0, 10000)
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inferer = Inference(config)
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scores = inferer.inference() # create scores_df out of this
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with open(new_path) as f:
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inference_drugs = f.read()
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generated_molecule_list = inference_drugs.split("\n")[:-1]
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rng = random.Random(config.seed)
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if num_molecules > 12:
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selected_molecules = rng.choices(generated_molecule_list, k=12)
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else:
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+
selected_molecules = generated_molecule_list
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selected_molecules = [Chem.MolFromSmiles(mol) for mol in selected_molecules if Chem.MolFromSmiles(mol) is not None]
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maximum=10_000,
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)
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seed_num = gr.Number(
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label="RNG seed value (can be used for reproducibility):",
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precision=0, # integer input
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minimum=0,
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)
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submit_button = gr.Button(
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