code: def compatible(target=None, converter_target_spec=None, **kwargs):
      """Wraps `tf.function` into a callable function with TFLite compatibility checking.
  
      Example:
  
      ```python
      @tf.lite.experimental.authoring.compatible
      @tf.function(input_signature=[
          tf.TensorSpec(shape=[None], dtype=tf.float32)
      ])
      def f(x):
          return tf.cosh(x)
  
      result = f(tf.constant([0.0]))
      # COMPATIBILITY WARNING: op 'tf.Cosh' require(s) "Select TF Ops" for model
      # conversion for TensorFlow Lite.
      # Op: tf.Cosh
      #   - tensorflow/python/framework/op_def_library.py:748
      #   - tensorflow/python/ops/gen_math_ops.py:2458
      #   - <stdin>:6
      ```
  
      WARNING: Experimental interface, subject to change.
  
      Args:
        target: A `tf.function` to decorate.
        converter_target_spec : target_spec of TFLite converter parameter.
        **kwargs: The keyword arguments of the decorator class _Compatible.
  
      Returns:
         A callable object of `tf.lite.experimental.authoring._Compatible`.
      """
      if target is None:
  
          def wrapper(target):
              return _Compatible(
                  target, converter_target_spec, **kwargs
              )
  
          return wrapper
      else:
          return _Compatible(target, converter_target_spec, **kwargs)
  
imports: import functools
  from tensorflow.lite.python import convert
  from tensorflow.lite.python import lite
  from tensorflow.lite.python.metrics import converter_error_data_pb2
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 1 for calling a global function with example usage: compatible(target, converter_target_spec) and returns: wrapper, _Compatible, _Compatible