parameters: (self)
return_statement: return int(sum([np.prod(w) for w in weight_shapes]))
docstring: Count the total number of scalars composing the weights.
  
      Returns:
          An integer count.
  
      Raises:
          ValueError: if the layer isn't yet built
            (in which case its weights aren't yet defined).
docstring_summary: Count the total number of scalars composing the weights.
docstring_tokens: Count the total number of scalars composing the weights .
function: def count_params(self):
      """Count the total number of scalars composing the weights.
  
      Returns:
          An integer count.
  
      Raises:
          ValueError: if the layer isn't yet built
            (in which case its weights aren't yet defined).
      """
      if not self.built:
        if self.__class__.__name__ == 'Sequential':
          self.build()  # pylint: disable=no-value-for-parameter
        else:
          raise ValueError('You tried to call `count_params` on ' + self.name +
                           ', but the layer isn\'t built. '
                           'You can build it manually via: `' + self.name +
                           '.build(batch_input_shape)`.')
      weight_shapes = [w.get_shape().as_list() for w in self.weights]
      return int(sum([np.prod(w) for w in weight_shapes]))
function_tokens: def count_params ( self ) : if not self . built : if self . __class__ . __name__ == 'Sequential' : self . build ( ) # pylint: disable=no-value-for-parameter else : raise ValueError ( 'You tried to call `count_params` on ' + self . name + ', but the layer isn\'t built. ' 'You can build it manually via: `' + self . name + '.build(batch_input_shape)`.' ) weight_shapes = [ w . get_shape ( ) . as_list ( ) for w in self . weights ] return int ( sum ( [ np . prod ( w ) for w in weight_shapes ] ) )