code: def zeta(
      x: torch.Tensor,
      q: torch.Tensor,
      /,
      *,
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      temp = torch.logical_and(
          torch.ne(torch.remainder(x, 2), 0), torch.gt(x, 1)
      )
      temp = torch.logical_and(temp, torch.le(q, 0))
      nan_indices = torch.logical_or(temp, torch.lt(x, 1))
      result = torch.special.zeta(x, q)
      result.masked_fill_(nan_indices, float("nan"))
      return result
  
imports: from typing import Optional, Union, Tuple, List, Sequence
  from numbers import Number
  import torch
  import ivy
  from ivy import promote_types_of_inputs
  from ivy.functional.backends.torch.elementwise import _cast_for_unary_op
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from ..None import backend_version
label_desc: Use image node_id 17 for calling a global function with example usage: zeta() and returns: result