parameters: (self, x, batch_size=None)
return_statement: return np.sum(self.evaluate(x=x, batch_size=batch_size)[GMM.SCORES])
docstring: Predict total sum of distances to nearest clusters.
  
      Args:
        x: 2-D matrix or iterator.
        batch_size: size to use for batching up x for querying the model.
  
      Returns:
        Total score.
docstring_summary: Predict total sum of distances to nearest clusters.
docstring_tokens: Predict total sum of distances to nearest clusters .
function: def score(self, x, batch_size=None):
      """Predict total sum of distances to nearest clusters.
  
      Args:
        x: 2-D matrix or iterator.
        batch_size: size to use for batching up x for querying the model.
  
      Returns:
        Total score.
      """
      return np.sum(self.evaluate(x=x, batch_size=batch_size)[GMM.SCORES])
function_tokens: def score ( self , x , batch_size = None ) : return np . sum ( self . evaluate ( x = x , batch_size = batch_size ) [ GMM . SCORES ] )