code: def scatter_flat(
      indices: torch.Tensor,
      updates: torch.Tensor,
      /,
      *,
      size: Optional[int] = None,
      reduction: str = "sum",
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      target = out
      target_given = ivy.exists(target)
      if ivy.exists(size) and ivy.exists(target):
          ivy.utils.assertions.check_equal(
              len(target.shape), 1, as_array=False
          )
          ivy.utils.assertions.check_equal(
              target.shape[0], size, as_array=False
          )
      dtype = updates.dtype
      if reduction not in ["sum", "replace", "min", "max"]:
          raise ivy.utils.exceptions.IvyException(
              f'reduction is {reduction}, but it must be one of "sum", "min", "max" or'
              ' "replace"'
          )
      if target_given:
          output = out
      else:
          reduction = "replace"
          output = torch.zeros([size], dtype=dtype)
      global torch_scatter
      if torch_scatter is None:
          try:
              import torch_scatter as torch_scatter
          except ImportError as e:
              raise ivy.utils.exceptions.IvyException(
                  "Unable to import torch_scatter, verify this is correctly installed."
              ) from e
      if reduction == "replace":
          output[indices.type(torch.int64)] = updates
          res = output
      else:
          res = torch_scatter.scatter(
              updates,
              indices.type(torch.int64),
              out=output,
              reduce=reduction,
          )
      return res
  
imports: from functools import reduce
  from numbers import Number
  from operator import mul
  from typing import Optional, Union, Sequence, Callable, List, Tuple
  import numpy
  import torch
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes, _update_torch_views
  from .None import backend_version, is_variable
  from ...ivy.general import _broadcast_to
label_desc: Use image node_id 22 for calling a global function with example usage: scatter_flat() and returns: res