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README.md
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### dataset description
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We downloaded PubChem-10m dataset from [here](https://deepchemdata.s3-us-west-1.amazonaws.com/datasets/pubchem_10m.txt.zip) and canonicalized it
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We used the following function to canonicalize the data.
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from rdkit import Chem
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def canonicalize(mol):
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mol = Chem.MolToSmiles(Chem.MolFromSmiles(mol),True)
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return mol
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---
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### dataset description
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We downloaded PubChem-10m dataset from [here](https://deepchemdata.s3-us-west-1.amazonaws.com/datasets/pubchem_10m.txt.zip) and canonicalized it.
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We used the following function to canonicalize the data and removed some SMILES that cannot be read by RDKit.
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```python:
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from rdkit import Chem
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def canonicalize(mol):
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mol = Chem.MolToSmiles(Chem.MolFromSmiles(mol),True)
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return mol
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```
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We randomly split the preprocessed data into train and validation. The ratio is 9 : 1.
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