original_docstring: 
          Calculate the distance of an edge. Take the vertices of the edge and calculate the distance between their
          embeddings.
          We use to calculate The distance with L1, l2, Cosine Similarity.
          :param edge: the edge we want to find its distance.
          :return: The distance
          
docstring: Calculate the distance of an edge. Take the vertices of the edge and calculate the distance between their
  embeddings.
  We use to calculate The distance with L1, l2, Cosine Similarity.
docstring_tokens: Calculate the distance of an edge . Take the vertices of the edge and calculate the distance between their embeddings . We use to calculate The distance with L1 l2 Cosine Similarity .
code: def edge_distance(self, edge):
          """
          Calculate the distance of an edge. Take the vertices of the edge and calculate the distance between their
          embeddings.
          We use to calculate The distance with L1, l2, Cosine Similarity.
          :param edge: the edge we want to find its distance.
          :return: The distance
          """
          embd1 = np.array(self.dict_projections[edge[0]]).astype(float)
          embd2 = np.array(self.dict_projections[edge[1]]).astype(float)
          if self.norm == set('L1 Norm'):
              norm = la.norm(np.subtract(embd1, embd2), 1)
          elif self.norm == set('L2 Norm'):
              norm = la.norm(np.subtract(embd1, embd2), 1)
          elif self.norm == set('cosine'):
              norm = cosine_similarity(embd1.reshape(1, -1), embd2.reshape(1, -1))[0]
          return norm
code_tokens: def edge_distance ( self , edge ) : embd1 = np . array ( self . dict_projections [ edge [ 0 ] ] ) . astype ( float ) embd2 = np . array ( self . dict_projections [ edge [ 1 ] ] ) . astype ( float ) if self . norm == set ( 'L1 Norm' ) : norm = la . norm ( np . subtract ( embd1 , embd2 ) , 1 ) elif self . norm == set ( 'L2 Norm' ) : norm = la . norm ( np . subtract ( embd1 , embd2 ) , 1 ) elif self . norm == set ( 'cosine' ) : norm = cosine_similarity ( embd1 . reshape ( 1 , - 1 ) , embd2 . reshape ( 1 , - 1 ) ) [ 0 ] return norm
short_docstring: Calculate the distance of an edge.
short_docstring_tokens: Calculate the distance of an edge .
comment: """
          Calculate the distance of an edge. Take the vertices of the edge and calculate the distance between their
          embeddings.
          We use to calculate The distance with L1, l2, Cosine Similarity.
          :param edge: the edge we want to find its distance.
          :return: The distance
          """