code: def kaiser_bessel_derived_window(
      window_length, beta=12.0, dtype=dtypes.float32, name=None
  ):
      """Generate a [Kaiser Bessel derived window][kbd].
  
      Args:
        window_length: A scalar `Tensor` indicating the window length to generate.
        beta: Beta parameter for Kaiser window.
        dtype: The data type to produce. Must be a floating point type.
        name: An optional name for the operation.
  
      Returns:
        A `Tensor` of shape `[window_length]` of type `dtype`.
  
      [kbd]:
        https://en.wikipedia.org/wiki/Kaiser_window#Kaiser%E2%80%93Bessel-derived_(KBD)_window
      """
      with ops.name_scope(name, "kaiser_bessel_derived_window"):
          window_length = _check_params(window_length, dtype)
          halflen = window_length // 2
          kaiserw = kaiser_window(halflen + 1, beta, dtype=dtype)
          kaiserw_csum = math_ops.cumsum(kaiserw)
          halfw = math_ops.sqrt(kaiserw_csum[:-1] / kaiserw_csum[-1])
          window = array_ops.concat((halfw, halfw[::-1]), axis=0)
      return window
  
file_path: tensorflow-upstream/tensorflow/python/ops/signal/window_ops.py
imports: import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import special_math_ops
  from tensorflow.python.util import dispatch
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 3 for calling a global function with example usage: kaiser_bessel_derived_window(window_length, beta, dtype, name) and returns: window