def _specialized_reduce_window(reducer, identity, operand, *, window_dimensions, window_strides, padding, base_dilation, window_dilation, _in_avals, _out_aval, name=None):
    'Wraps the TensorFlow reduce window operation based on a reducer and an\n\n  identity function defining the initial value of the reduction depending on\n  the dtype of the operand.\n\n  Args:\n    reducer: reduction function of type TfVal -> TfVal -> TfVal\n    identity: function that takes a TensorFlow dtype as a parameter and returns\n      the starting value of the reduction.\n    operand: N dimensional array containing elements of type T\n    window_dimensions: array of integers for window dimension values\n    window_strides: array of integers for window stride values\n    padding: array of pairs of integers for padding values\n    base_dilation: array of integers for base dilation values\n    window_dilation: array of integers for window dilation values\n    name: the name of the specialized reduce window primitive for which this\n      conversion function is called. This information may help to choose a\n      different conversion path (optional)\n\n  Returns:\n    The reduced operand.\n  '
    if ((not _enable_xla) and (name in ['reduce_window_max', 'reduce_window_sum'])):
        return _try_tf_pool(name, operand, window_dimensions, window_strides, padding, base_dilation, window_dilation)
    return _common_reduce_window(operand, identity(operand.dtype), reducer, window_dimensions, window_strides, padding, base_dilation, window_dilation, _in_avals, _out_aval)
Wraps the TensorFlow reduce window operation based on a reducer and an

identity function defining the initial value of the reduction depending on
the dtype of the operand.

Args:
  reducer: reduction function of type TfVal -> TfVal -> TfVal
  identity: function that takes a TensorFlow dtype as a parameter and returns
    the starting value of the reduction.
  operand: N dimensional array containing elements of type T
  window_dimensions: array of integers for window dimension values
  window_strides: array of integers for window stride values
  padding: array of pairs of integers for padding values
  base_dilation: array of integers for base dilation values
  window_dilation: array of integers for window dilation values
  name: the name of the specialized reduce window primitive for which this
    conversion function is called. This information may help to choose a
    different conversion path (optional)

Returns:
  The reduced operand.
def _specialized_reduce_window(reducer, identity, operand, *, window_dimensions, window_strides, padding, base_dilation, window_dilation, _in_avals, _out_aval, name=None):
    'Wraps the TensorFlow reduce window operation based on a reducer and an\n\n  identity function defining the initial value of the reduction depending on\n  the dtype of the operand.\n\n  Args:\n    reducer: reduction function of type TfVal -> TfVal -> TfVal\n    identity: function that takes a TensorFlow dtype as a parameter and returns\n      the starting value of the reduction.\n    operand: N dimensional array containing elements of type T\n    window_dimensions: array of integers for window dimension values\n    window_strides: array of integers for window stride values\n    padding: array of pairs of integers for padding values\n    base_dilation: array of integers for base dilation values\n    window_dilation: array of integers for window dilation values\n    name: the name of the specialized reduce window primitive for which this\n      conversion function is called. This information may help to choose a\n      different conversion path (optional)\n\n  Returns:\n    The reduced operand.\n  '
    if ((not _enable_xla) and (name in ['reduce_window_max', 'reduce_window_sum'])):
        return _try_tf_pool(name, operand, window_dimensions, window_strides, padding, base_dilation, window_dilation)
    return _common_reduce_window(operand, identity(operand.dtype), reducer, window_dimensions, window_strides, padding, base_dilation, window_dilation, _in_avals, _out_aval)