def from_input_list_with_batch_size_static_batch(
        cls, inputs: List[torch.Tensor], max_batch_size: int, batch_dim: int = 0
    ) -> List["TensorSpec"]:
        """
        Most of the recommendation models will work fine using this function.

        We make an assumption that inferred lowerable subgraph inputs will have
        a single batch dimension with the same max batch size.
        """
        result: List[TensorSpec] = []

        for t in inputs:
            shape: List[IntVar] = []
            for _, d in enumerate(t.shape):
                shape.append(IntImm(d))
            result.append(TensorSpec(shape, t.dtype))

        return result

        Most of the recommendation models will work fine using this function.

        We make an assumption that inferred lowerable subgraph inputs will have
        a single batch dimension with the same max batch size.
        
fx2ait/fx2ait/tensor_spec.py