text: from os import name
  import torch
  import sys
  from net import *
  from data import *
  sys.path.insert(0, "/home/megh/projects/entity-norm/cnn-norm-obo")
  from code.dataset import *
  
  class CNNNorm():
      def __init__(self,data_path = os.path.join("../../../data/datasets/cl.obo")) -> None:
          name_array, query_id_array, mention2id, edge_index  = load_data(filename=data_path)
  
          queries_train, queries_valid, queries_test = data_split(query_id_array = query_id_array, is_unseen=1, test_size=0.33)
  
          dummy_m = torch.rand(24,1,50,3)
          dummy_y = torch.rand(24,1,50,4)
          print("Dummy input sizes are:")
          print("m size ", dummy_m.shape)
          print("y size ", dummy_y.shape)
  
          self.dataset_ranking =  RankingDataset(queries_train, mention2id, name_array)
          model = RankingCNN()
  
          out  = model(dummy_m,dummy_y)
          
      def train():
          pass
  
  if __name__ == "__main__":
      cnn_norm = CNNNorm()