wenhao-gao commited on
Commit
1b7c1ca
1 Parent(s): f57c985
Files changed (1) hide show
  1. app.py +5 -5
app.py CHANGED
@@ -17,7 +17,7 @@ last_result = {}
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  # Function to clear all inputs
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  def clear_inputs():
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  # Return default or empty values to reset each input component
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- return None, 24, 64, 0
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  def sample(smi, search_width, exhaustiveness):
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  result_df = run_sampling_one_cpu(
@@ -58,7 +58,7 @@ with gr.Blocks() as demo:
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  # Demo of [SynFormer](https://github.com/wenhao-gao/synformer/tree/main)
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  This page demonstrates the SynFormer-ED model, which takes a molecule as input—regardless of its synthetic accessibility—and outputs
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  identical or approximate molecules along with their associated synthetic paths. The demo runs on CPUs and typically takes about
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- one minute per run but can be accelerated by reducing the search width and exhaustiveness. The model may take longer if the server
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  is busy. Since the sampling is stochastic, you may run the demo multiple times to explore different results, with a maximum of
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  30 molecules displayed at once.
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  To learn more about SynFormer’s architecture and applications, check out [our paper](https://github.com/wenhao-gao/synformer/tree/main).
@@ -68,8 +68,8 @@ with gr.Blocks() as demo:
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  with gr.Row():
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  with gr.Column(scale=0.5):
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  input_molecule = molecule2d(label="SMILES Input")
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- slider_1 = gr.Slider(minimum=1, maximum=100, step=1, label="Search Width", value=24)
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- slider_2 = gr.Slider(minimum=1, maximum=100, step=1, label="Exhaustiveness", value=64)
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  with gr.Row():
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  with gr.Column(scale=0.5):
@@ -119,4 +119,4 @@ with gr.Blocks() as demo:
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  outputs=[input_molecule, slider_1, slider_2, index_slider]
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  )
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- demo.launch()
 
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  # Function to clear all inputs
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  def clear_inputs():
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  # Return default or empty values to reset each input component
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+ return None, 8, 8, 0
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  def sample(smi, search_width, exhaustiveness):
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  result_df = run_sampling_one_cpu(
 
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  # Demo of [SynFormer](https://github.com/wenhao-gao/synformer/tree/main)
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  This page demonstrates the SynFormer-ED model, which takes a molecule as input—regardless of its synthetic accessibility—and outputs
60
  identical or approximate molecules along with their associated synthetic paths. The demo runs on CPUs and typically takes about
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+ one minute per run on local machine, but can be accelerated by reducing the search width and exhaustiveness. The model may take longer if the server
62
  is busy. Since the sampling is stochastic, you may run the demo multiple times to explore different results, with a maximum of
63
  30 molecules displayed at once.
64
  To learn more about SynFormer’s architecture and applications, check out [our paper](https://github.com/wenhao-gao/synformer/tree/main).
 
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  with gr.Row():
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  with gr.Column(scale=0.5):
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  input_molecule = molecule2d(label="SMILES Input")
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+ slider_1 = gr.Slider(minimum=1, maximum=100, step=1, label="Search Width", value=8)
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+ slider_2 = gr.Slider(minimum=1, maximum=100, step=1, label="Exhaustiveness", value=8)
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  with gr.Row():
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  with gr.Column(scale=0.5):
 
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  outputs=[input_molecule, slider_1, slider_2, index_slider]
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  )
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+ demo.launch()