osbm commited on
Commit
a7af5cb
·
1 Parent(s): 479ed5f

Update new_dataloader.py

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Files changed (1) hide show
  1. new_dataloader.py +8 -8
new_dataloader.py CHANGED
@@ -59,19 +59,19 @@ class DruggenDataset(InMemoryDataset):
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  print('Created bonds encoder and decoder with {} bond types and 1 PAD symbol!'.format(
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  self.bond_num_types - 1))
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  #dataset_names = str(self.dataset_name)
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- with open("DrugGEN/data/encoders/" +"atom_" + self.dataset_name + ".pkl","wb") as atom_encoders:
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  pickle.dump(self.atom_encoder_m,atom_encoders)
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- with open("DrugGEN/data/decoders/" +"atom_" + self.dataset_name + ".pkl","wb") as atom_decoders:
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  pickle.dump(self.atom_decoder_m,atom_decoders)
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- with open("DrugGEN/data/encoders/" +"bond_" + self.dataset_name + ".pkl","wb") as bond_encoders:
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  pickle.dump(self.bond_encoder_m,bond_encoders)
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- with open("DrugGEN/data/decoders/" +"bond_" + self.dataset_name + ".pkl","wb") as bond_decoders:
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  pickle.dump(self.bond_decoder_m,bond_decoders)
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@@ -118,11 +118,11 @@ class DruggenDataset(InMemoryDataset):
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  return np.vstack((features, np.zeros((max_length - features.shape[0], features.shape[1]))))
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  def decoder_load(self, dictionary_name, file):
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- with open("DrugGEN/data/decoders/" + dictionary_name + "_" + file + '.pkl', 'rb') as f:
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  return pickle.load(f)
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  def drugs_decoder_load(self, dictionary_name):
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- with open("DrugGEN/data/decoders/" + dictionary_name +'.pkl', 'rb') as f:
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  return pickle.load(f)
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  def matrices2mol(self, node_labels, edge_labels, strict=True, file_name=None):
@@ -151,7 +151,7 @@ class DruggenDataset(InMemoryDataset):
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  ''' Loading the atom and bond decoders '''
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- with open("DrugGEN/data/decoders/" + dictionary_name +"_" + file +'.pkl', 'rb') as f:
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  return pickle.load(f)
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  def matrices2mol_drugs(self, node_labels, edge_labels, strict=True, file_name=None):
@@ -291,5 +291,5 @@ class DruggenDataset(InMemoryDataset):
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  if __name__ == '__main__':
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- data = DruggenDataset("DrugGEN/data")
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  print('Created bonds encoder and decoder with {} bond types and 1 PAD symbol!'.format(
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  self.bond_num_types - 1))
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  #dataset_names = str(self.dataset_name)
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+ with open("data/encoders/" +"atom_" + self.dataset_name + ".pkl","wb") as atom_encoders:
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  pickle.dump(self.atom_encoder_m,atom_encoders)
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+ with open("data/decoders/" +"atom_" + self.dataset_name + ".pkl","wb") as atom_decoders:
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  pickle.dump(self.atom_decoder_m,atom_decoders)
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+ with open("data/encoders/" +"bond_" + self.dataset_name + ".pkl","wb") as bond_encoders:
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  pickle.dump(self.bond_encoder_m,bond_encoders)
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+ with open("data/decoders/" +"bond_" + self.dataset_name + ".pkl","wb") as bond_decoders:
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  pickle.dump(self.bond_decoder_m,bond_decoders)
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  return np.vstack((features, np.zeros((max_length - features.shape[0], features.shape[1]))))
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  def decoder_load(self, dictionary_name, file):
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+ with open("data/decoders/" + dictionary_name + "_" + file + '.pkl', 'rb') as f:
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  return pickle.load(f)
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  def drugs_decoder_load(self, dictionary_name):
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+ with open("data/decoders/" + dictionary_name +'.pkl', 'rb') as f:
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  return pickle.load(f)
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  def matrices2mol(self, node_labels, edge_labels, strict=True, file_name=None):
 
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  ''' Loading the atom and bond decoders '''
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+ with open("data/decoders/" + dictionary_name +"_" + file +'.pkl', 'rb') as f:
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  return pickle.load(f)
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  def matrices2mol_drugs(self, node_labels, edge_labels, strict=True, file_name=None):
 
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  if __name__ == '__main__':
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+ data = DruggenDataset("data")
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