optimum/quanto/tensor/weights/awq/qbits.py [112:138]:
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        return WeightQBitsTensor(
            self._qtype, self._axis, self._group_size, self.size(), self.stride(), data, scale, shift
        )

    def __tensor_flatten__(self):
        inner_tensors = ["_data", "_scale", "_shift"]
        # Since meta can be used for serialization, use only strings
        meta = {
            "qtype": self._qtype.name,
            "axis": str(self._axis),
            "group_size": str(self._group_size),
            "size": str(list(self.size())),
            "stride": str(list(self.stride())),
        }
        return inner_tensors, meta

    @staticmethod
    def __tensor_unflatten__(inner_tensors, meta, outer_size, outer_stride):
        assert len(inner_tensors) == 3
        assert len(meta) == 5
        data, scale, shift = inner_tensors["_data"], inner_tensors["_scale"], inner_tensors["_shift"]
        # Meta should only contain strings, AST compatible except qtype
        qtype = qtypes[meta["qtype"]]
        axis = ast.literal_eval(meta["axis"])
        group_size = ast.literal_eval(meta["group_size"])
        size = ast.literal_eval(meta["size"])
        stride = ast.literal_eval(meta["stride"])
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optimum/quanto/tensor/weights/marlin/int4/qbits.py [117:143]:
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        return WeightQBitsTensor(
            self._qtype, self._axis, self._group_size, self.size(), self.stride(), data, scale, shift
        )

    def __tensor_flatten__(self):
        inner_tensors = ["_data", "_scale", "_shift"]
        # Since meta can be used for serialization, use only strings
        meta = {
            "qtype": self._qtype.name,
            "axis": str(self._axis),
            "group_size": str(self._group_size),
            "size": str(list(self.size())),
            "stride": str(list(self.stride())),
        }
        return inner_tensors, meta

    @staticmethod
    def __tensor_unflatten__(inner_tensors, meta, outer_size, outer_stride):
        assert len(inner_tensors) == 3
        assert len(meta) == 5
        data, scale, shift = inner_tensors["_data"], inner_tensors["_scale"], inner_tensors["_shift"]
        # Meta should only contain strings, AST compatible except qtype
        qtype = qtypes[meta["qtype"]]
        axis = ast.literal_eval(meta["axis"])
        group_size = ast.literal_eval(meta["group_size"])
        size = ast.literal_eval(meta["size"])
        stride = ast.literal_eval(meta["stride"])
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