code: def reduce_variance(
      input_tensor: ragged_tensor.Ragged,
      axis=None,
      keepdims=False,
      name=None,
  ):
      """For docs, see: _RAGGED_REDUCE_DOCSTRING."""
      with ops.name_scope(
          name, "RaggedReduceVariance", [input_tensor, axis]
      ):
          input_tensor = (
              ragged_tensor.convert_to_tensor_or_ragged_tensor(
                  input_tensor, name="input_tensor"
              )
          )
          if input_tensor.dtype.is_complex:
              raise ValueError(
                  "reduce_variance is not supported for RaggedTensors with complex"
                  " dtypes."
              )
          square_of_input = math_ops.square(input_tensor)
          mean_of_square = reduce_mean(
              square_of_input, axis=axis, keepdims=keepdims
          )
          mean = reduce_mean(input_tensor, axis=axis, keepdims=keepdims)
          square_of_mean = math_ops.square(mean)
          # Note: the above method of computing variance is not numerically stable,
          # and can result in negative variances.  Here we clip to >= 0.
          return math_ops.maximum(mean_of_square - square_of_mean, 0)
  
imports: import functools
  import typing
  import numpy
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import gen_ragged_math_ops
  from tensorflow.python.ops import map_fn
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops.ragged import ragged_functional_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.ops.ragged import segment_id_ops
  from tensorflow.python.util import dispatch
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 17 for calling a global function with example usage: reduce_variance(input_tensor, axis, keepdims, name) and returns: math_ops