docstr: Get similarity score between two feature vectors: 1. feature vector of an opened image;
  and 2. feature vector from base table.
code: def forward(self, df: pd.DataFrame) -> pd.DataFrame:
      """
      Get similarity score between two feature vectors: 1. feature vector of an opened image;
      and 2. feature vector from base table.
      """
  
      def _similarity(row: pd.Series) -> float:
          open_feat_np, base_feat_np = (
              row.iloc[0],
              row.iloc[1],
          )
  
          # TODO: currently system takes care of feature vector shape
          # transformation. Improve this later on.
          # Transform to 2D.
          open_feat_np = open_feat_np.reshape(1, -1)
          base_feat_np = base_feat_np.reshape(1, -1)
          import faiss
  
          distance_np = faiss.pairwise_distances(
              open_feat_np, base_feat_np
          )
  
          return self._get_distance(distance_np)
  
      ret = pd.DataFrame()
      ret["distance"] = df.apply(_similarity, axis=1)
      return ret
  
file_path: evadb/evadb/functions/ndarray/similarity.py
imports: import pandas
  from evadb.functions.abstract.abstract_function import AbstractFunction
  from evadb.utils.generic_utils import try_to_import_faiss
label_desc: Use image node_id 4 for calling the Similarity obj's underlying member method code with example usage: obj.forward(df) and returns: ret, self