saicharan2804 commited on
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6bdd4e7
1 Parent(s): bbe40ff

Removed some metrics

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Files changed (1) hide show
  1. my_metric.py +14 -14
my_metric.py CHANGED
@@ -8,7 +8,7 @@ from tdc import Oracle
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  _DESCRIPTION = """
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- Moses and PyTDC metrics
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  Comprehensive suite of metrics designed to assess the performance of molecular generation models, for understanding how well a model can produce novel, chemically valid molecules that are relevant to specific research objectives.
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  """
@@ -81,28 +81,28 @@ class my_metric(evaluate.Metric):
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  Results = metrics.get_all_metrics(gen = generated_smiles, train= train_smiles)
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- evaluator = Evaluator(name = 'Diversity')
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- Diversity = evaluator(generated_smiles)
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  evaluator = Evaluator(name = 'KL_Divergence')
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  KL_Divergence = evaluator(generated_smiles, train_smiles)
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- evaluator = Evaluator(name = 'FCD_Distance')
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- FCD_Distance = evaluator(generated_smiles, train_smiles)
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- evaluator = Evaluator(name = 'Novelty')
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- Novelty = evaluator(generated_smiles, train_smiles)
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- evaluator = Evaluator(name = 'Validity')
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- Validity = evaluator(generated_smiles)
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  Results.update({
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- "PyTDC_Diversity": Diversity,
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- "PyTDC_KL_Divergence": KL_Divergence,
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- "PyTDC_FCD_Distance": FCD_Distance,
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- "PyTDC_Novelty": Novelty,
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- "PyTDC_Validity": Validity,
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  })
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  _DESCRIPTION = """
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+
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  Comprehensive suite of metrics designed to assess the performance of molecular generation models, for understanding how well a model can produce novel, chemically valid molecules that are relevant to specific research objectives.
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  """
 
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  Results = metrics.get_all_metrics(gen = generated_smiles, train= train_smiles)
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+ # evaluator = Evaluator(name = 'Diversity')
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+ # Diversity = evaluator(generated_smiles)
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  evaluator = Evaluator(name = 'KL_Divergence')
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  KL_Divergence = evaluator(generated_smiles, train_smiles)
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+ # evaluator = Evaluator(name = 'FCD_Distance')
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+ # FCD_Distance = evaluator(generated_smiles, train_smiles)
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+ # evaluator = Evaluator(name = 'Novelty')
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+ # Novelty = evaluator(generated_smiles, train_smiles)
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+ # evaluator = Evaluator(name = 'Validity')
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+ # Validity = evaluator(generated_smiles)
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  Results.update({
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+ # "PyTDC_Diversity": Diversity,
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+ "KL_Divergence": KL_Divergence,
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+ # "PyTDC_Validity": Validity,FCD_Distance": FCD_Distance,
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+ # "PyTDC_Novelty": Novelty,
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+ # "PyTDC_
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  })
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