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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def pack_weights(self, args):
 """Pack separate weight matrices into a single packed weight. Parameters args : dict of str -> NDArray Dictionary containing unpacked weights. Returns ------- args : dict of str -> NDArray Dictionary with packed weights associated with this cell. """

        args = args.copy()
        if not self._gate_names:
            return args
        for group_name in ['i2h', 'h2h']:
            weight = []
            bias = []
            for gate in self._gate_names:
                wname = '%s%s%s_weight'%(self._prefix, group_name, gate)
                weight.append(args.pop(wname))
                bname = '%s%s%s_bias'%(self._prefix, group_name, gate)
                bias.append(args.pop(bname))
            args['%s%s_weight'%(self._prefix, group_name)] = ndarray.concatenate(weight)
            args['%s%s_bias'%(self._prefix, group_name)] = ndarray.concatenate(bias)
        return args