code: def _CustomReciprocal(x):
      """Wrapper function around `math_ops.div_no_nan()` to perform a "safe" reciprocal incase the input is zero. Avoids divide by zero and NaNs.
  
      Input:
        x -> input tensor to be reciprocat-ed.
      Returns:
        x_reciprocal -> reciprocal of x without NaNs.
      """
      return math_ops.div_no_nan(math_ops.cast(1.0, x.dtype), x)
  
file_path: tensorflow/tensorflow/python/ops/image_grad.py
imports: from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import gen_image_ops
  from tensorflow.python.ops import math_ops
label_desc: Use image node_id 6 for calling a global function with example usage: _CustomReciprocal(x) and returns: math_ops