code: def scatter_flat(
      indices: Union[tf.Tensor, tf.Variable],
      updates: Union[tf.Tensor, tf.Variable],
      /,
      *,
      size: Optional[int] = None,
      reduction: str = "sum",
      out: Optional[Union[tf.Tensor, tf.Variable]] = None,
  ) -> Union[tf.Tensor, tf.Variable]:
      if indices.dtype != tf.int32 or indices.dtype != tf.int64:
          if indices.dtype in [tf.int8, tf.int16, tf.uint8, tf.uint16]:
              indices = tf.cast(indices, tf.int32)
          else:
              indices = tf.cast(indices, tf.int64)
      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
          )
      if not target_given:
          target = tf.zeros([size], dtype=updates.dtype)
          res = tf.tensor_scatter_nd_update(
              target, tf.expand_dims(indices, -1), updates
          )
      elif reduction == "max":
          res = tf.tensor_scatter_nd_max(
              target, tf.expand_dims(indices, -1), updates
          )
      elif reduction == "min":
          res = tf.tensor_scatter_nd_min(
              target, tf.expand_dims(indices, -1), updates
          )
      elif reduction == "replace":
          res = tf.tensor_scatter_nd_update(
              target, tf.expand_dims(indices, -1), updates
          )
      elif reduction == "sum":
          res = tf.tensor_scatter_nd_add(
              target, tf.expand_dims(indices, -1), updates
          )
      else:
          raise ivy.utils.exceptions.IvyException(
              f'reduction is {reduction}, but it must be one of "sum", "min", "max" or'
              ' "replace"'
          )
      return ivy.inplace_update(out, res) if ivy.exists(out) else res
  
imports: from typing import Optional, Union, Sequence, Callable, Tuple
  import numpy
  import multiprocessing
  from numbers import Number
  import tensorflow
  import ivy
  from ivy.functional.ivy.gradients import _is_variable
  from ivy.func_wrapper import with_unsupported_dtypes
  from ivy.utils.exceptions import _check_inplace_update_support
  from .None import backend_version
  from ...ivy.general import _broadcast_to
label_desc: Use image node_id 21 for calling a global function with example usage: scatter_flat() and returns: unknown