optimum/quanto/tensor/weights/marlin/fp8/packed.py [223:239]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    def __tensor_flatten__(self):
        inner_tensors = ["_data"]
        # Since meta can be used for serialization, use only AST compatible strings
        meta = {
            "size": str(list(self.size())),
            "stride": str(self.stride()),
        }
        return inner_tensors, meta

    @staticmethod
    def __tensor_unflatten__(inner_tensors, meta, outer_size, outer_stride):
        assert len(inner_tensors) == 1
        assert len(meta) == 2
        data = inner_tensors["_data"]
        # Meta should contain only AST compatible strings
        size = ast.literal_eval(meta["size"])
        stride = ast.literal_eval(meta["stride"])
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



optimum/quanto/tensor/weights/marlin/int4/packed.py [119:133]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    def __tensor_flatten__(self):
        inner_tensors = ["_data"]
        meta = {
            "size": str(list(self.size())),
            "stride": str(self.stride()),
        }
        return inner_tensors, meta

    @staticmethod
    def __tensor_unflatten__(inner_tensors, meta, outer_size, outer_stride):
        assert len(inner_tensors) == 1
        assert len(meta) == 2
        data = inner_tensors["_data"]
        size = ast.literal_eval(meta["size"])
        stride = ast.literal_eval(meta["stride"])
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



