(self)
return num_total_params, num_trainable_params
r"""
        Computes the number of parameters in this model.

        Args: None

        Returns:
            int: Total number of weight parameters for this model.
            int: Total number of trainable parameters for this model.
r"""
        Computes the number of parameters in this model.
r Computes the number of parameters in this model .
def count_params(self):
        r"""
        Computes the number of parameters in this model.

        Args: None

        Returns:
            int: Total number of weight parameters for this model.
            int: Total number of trainable parameters for this model.

        """
        num_total_params = sum(np.prod(p.shape) for p in self.parameters())
        num_trainable_params = sum(np.prod(p.shape) for p in self.parameters(requires_grad=True))

        return num_total_params, num_trainable_params
def count_params ( self ) : num_total_params = sum ( np . prod ( p . shape ) for p in self . parameters ( ) ) num_trainable_params = sum ( np . prod ( p . shape ) for p in self . parameters ( requires_grad = True ) ) return num_total_params , num_trainable_params