class_docstr: A decorator class to check TFLite compatibility created by `lite.experimental.authoring.compatible`.
class_docstr_tok: ["A","decorator","class","to","check","TFLite","compatibility","created","by","`","lite.experimental.authoring.compatible","`","."]
docstr: Parses the given legacy ConverterError for OSS.
docstr_tok: ["Parses","the","given","legacy","ConverterError","for","OSS","."]
code: def _decode_error_legacy(self, err):
      """Parses the given legacy ConverterError for OSS."""
      for line in str(err).splitlines():
          # Check custom op usage error.
          if line.startswith(_CUSTOM_OPS_HDR):
              custom_ops = line[len(_CUSTOM_OPS_HDR) :]
              err_string = (
                  f"{_AUTHORING_ERROR_HDR}: op '{custom_ops}' is(are) not natively "
                  "supported by TensorFlow Lite. You need to provide a custom "
                  "operator. https://www.tensorflow.org/lite/guide/ops_custom"
              )
              self._log(err_string)
          # Check TensorFlow op usage error.
          elif line.startswith(_TF_OPS_HDR):
              tf_ops = line[len(_TF_OPS_HDR) :]
              err_string = (
                  f"{_AUTHORING_WARNING_HDR}: op '{tf_ops}' require(s) \"Select TF "
                  'Ops" for model conversion for TensorFlow Lite. '
                  "https://www.tensorflow.org/lite/guide/ops_select"
              )
              self._log(err_string)
  
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 8 for calling the _Compatible obj's underlying member method code with example usage: obj._decode_error_legacy(err) without return types