update admet model

examples/single_pred/admet/run.py

@@ -1,3 +1,4 @@
+from rdkit.DataStructs import cDataStructs
 from DeepPurpose import CompoundPred as models
 from DeepPurpose.utils import *
 
@@ -14,11 +15,14 @@
 args = parser.parse_args()
 drug_encoding = args.model
 
-if drug_encoding not in ['RDKit2D', 'Morgan', 'CNN']:
-    raise ValueError("You have to specify from 'RDKit2D', 'Morgan', 'CNN'!")
+if drug_encoding not in ['RDKit2D', 'Morgan', 'CNN', 'NeuralFP', 'MPNN', 'AttentiveFP', 'AttrMasking', 'ContextPred']:
+    raise ValueError("You have to specify from 'RDKit2D', 'Morgan', 'CNN', 'NeuralFP', 'MPNN', 'AttentiveFP', 'AttrMasking', 'ContextPred'!")
 
 if drug_encoding == 'RDKit2D':
     drug_encoding = 'rdkit_2d_normalized'
+
+if drug_encoding in ['NeuralFP', 'AttentiveFP', 'AttrMasking', 'ContextPred']:
+    drug_encoding = 'DGL_' + drug_encoding
 
 predictions_all_seeds = {}
 results_all_seeds = {}
@@ -67,4 +71,4 @@ def get_metric(x):
         return [round(np.mean(metric), 3), round(np.std(metric), 3)]
     return dict(df.apply(get_metric, axis = 1))
 
-print(to_submission_format(results_all_seeds)) 
+print(to_submission_format(results_all_seeds))