code: def angle(x):
      if x.is_complex():
          return torch.where(
              torch.isnan(x.real),
              float("nan"),
              torch.atan2(x.imag, x.real),
          )
  
      # when x is real number
      #   if x >= 0, return 0
      #   if x < 0, return pi
      #   if x is nan, return nan
      _, dtype = elementwise_dtypes(
          x,
          type_promotion_kind=ELEMENTWISE_TYPE_PROMOTION_KIND.INT_TO_FLOAT,
      )
      pi = torch.scalar_tensor(math.pi, dtype=dtype, device=x.device)
      ret = torch.where(x < 0, pi, 0.0)
      return torch.where(torch.isnan(x), float("nan"), ret)
  
imports: import functools
  import logging
  import math
  import sys
  import typing
  from typing import Optional
  import torch
  import torch._decomp
  import torch._prims_common
  import torch.ao.quantization.fx._decomposed
  from torch._decomp import core_aten_decompositions, get_decompositions, remove_decompositions
  from torch._decomp.decompositions import _grid_sampler_2d, pw_cast_for_opmath
  from torch._decomp.decompositions_for_rng import extra_random_decomps
  from torch._higher_order_ops.out_dtype import out_dtype
  from torch._prims_common import elementwise_dtypes, ELEMENTWISE_TYPE_PROMOTION_KIND, type_to_dtype
  from .None import config, inductor_prims
label_desc: Use image node_id 15 for calling a global function with example usage: angle(x) and returns: torch, torch