import tensorflow as tf


    combine_inputs = _WeightedMeanAndVarAccumulator(
        count=x_count,
        mean=x_mean,
        variance=x_variance,
        weight=tf.zeros([], tf.float32))

    output_shape = ()
    if not reduce_instance_dims:
      # We need to use tf.expand_dims to artificially add a batch dimension.
      output_shape = _get_output_shape_from_input(
          tf.expand_dims(x_count, axis=0))

    x_mean, x_var = _apply_cacheable_combiner(
        WeightedMeanAndVarCombiner(output_dtype.as_numpy_dtype, output_shape),
        *combine_inputs)

  return x_mean, x_var


@common.log_api_use(common.ANALYZER_COLLECTION)
def tukey_location(x: common_types.TensorType,
