@register_meta(aten.index.Tensor)
def meta_index_Tensor(self, indices):
    result: List[Optional[Tensor]] = []
    for i, index in enumerate(indices):
        if index is not None:
            check(
                index.dtype in [torch.long, torch.int, torch.int8, torch.bool],
                lambda: "tensors used as indices must be long, int, byte or bool tensors",
            )
            if index.dtype in [torch.int8, torch.bool]:
                nonzero = index.nonzero()
                k = len(result)
                check(
                    k + index.ndim <= self.ndim,
                    lambda: f"too many indices for tensor of dimension {self.ndim}",
                    IndexError,
                )
                for j in range(index.ndim):
                    check(
                        index.shape[j] == self.shape[k + j],
                        lambda: f"The shape of the mask {index.shape} at index {i} "
                        f"does not match the shape of the indexed tensor {self.shape} at index {k + j}",
                        IndexError,
                    )
                    result.append(nonzero.select(1, j))
            else:
                result.append(index)
        else:
            result.append(index)
    return result