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Change logging in optimization to record auc_top10. #26

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Change logging in optimization to record auc_top10. #26

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22 changes: 10 additions & 12 deletions main/optimizer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -115,21 +115,14 @@ def log_intermediate(self, mols=None, scores=None, finish=False):
# Uncomment this line if want to log top-10 moelucles figures, so as the best_mol key values.
# temp_top10 = list(self.mol_buffer.items())[:10]

# Create status dict with metrics
avg_top1 = np.max(scores)
avg_top10 = np.mean(sorted(scores, reverse=True)[:10])
avg_top100 = np.mean(scores)
avg_sa = np.mean(self.sa_scorer(smis))
diversity_top100 = self.diversity_evaluator(smis)

print(f'{n_calls}/{self.max_oracle_calls} | '
f'avg_top1: {avg_top1:.3f} | '
f'avg_top10: {avg_top10:.3f} | '
f'avg_top100: {avg_top100:.3f} | '
f'avg_sa: {avg_sa:.3f} | '
f'div: {diversity_top100:.3f}')

# try:
wandb.log({
status_dict = {
"n_oracle": n_calls,
"avg_top1": avg_top1,
"avg_top10": avg_top10,
"avg_top100": avg_top100,
Expand All @@ -138,11 +131,16 @@ def log_intermediate(self, mols=None, scores=None, finish=False):
"auc_top100": top_auc(self.mol_buffer, 100, finish, self.freq_log, self.max_oracle_calls),
"avg_sa": avg_sa,
"diversity_top100": diversity_top100,
"n_oracle": n_calls,
# "best_mol": wandb.Image(Draw.MolsToGridImage([Chem.MolFromSmiles(item[0]) for item in temp_top10],
# molsPerRow=5, subImgSize=(200,200), legends=[f"f = {item[1][0]:.3f}, #oracle = {item[1][1]}" for item in temp_top10]))
})
}

# Print status dict
print_formatted_dict = {k: f'{v:.3f}' if (isinstance(v, float) and not isinstance(v, int)) else v for k, v in status_dict.items()}
print(" | ".join([f'{k}: {v}' for k, v in print_formatted_dict.items()]))

# Log to wandb
wandb.log(status_dict)

def __len__(self):
return len(self.mol_buffer)
Expand Down