---------------------------------------------------------------------------
Exception                                 Traceback (most recent call last)
/Applications/anaconda3/lib/python3.7/site-packages/tensorflow/lite/python/convert.py in toco_convert_protos(model_flags_str, toco_flags_str, input_data_str, debug_info_str, enable_mlir_converter)
    212                                                  debug_info_str,
--> 213                                                  enable_mlir_converter)
    214       return model_str

/Applications/anaconda3/lib/python3.7/site-packages/tensorflow/lite/python/wrap_toco.py in wrapped_toco_convert(model_flags_str, toco_flags_str, input_data_str, debug_info_str, enable_mlir_converter)
     37       debug_info_str,
---> 38       enable_mlir_converter)
     39 

Exception: <unknown>:0: error: loc("boosted_trees"): 'tf.BoostedTreesEnsembleResourceHandleOp' op is neither a custom op nor a flex op
<unknown>:0: error: loc("boosted_trees/BoostedTreesPredict"): 'tf.BoostedTreesPredict' op is neither a custom op nor a flex op
<unknown>:0: error: loc("boosted_trees/head/predictions/str_classes"): 'tf.AsString' op is neither a custom op nor a flex op
<unknown>:0: error: failed while converting: 'main': Ops that need custom implementation (enabled via setting the -emit-custom-ops flag):
	tf.AsString {device = "", fill = "", precision = -1 : i64, scientific = false, shortest = false, width = -1 : i64}
	tf.BoostedTreesEnsembleResourceHandleOp {container = "", device = "", shared_name = "boosted_trees/"}
	tf.BoostedTreesPredict {device = "", logits_dimension = 7 : i64, num_bucketized_features = 18 : i64}


During handling of the above exception, another exception occurred:

ConverterError                            Traceback (most recent call last)
<ipython-input-33-ddfbc74c8e86> in <module>
      5 ]
      6 
----> 7 tflite_model = converter.convert()
      8 
      9 

/Applications/anaconda3/lib/python3.7/site-packages/tensorflow/lite/python/lite.py in convert(self)
    737     converter_kwargs.update(quant_mode.converter_flags())
    738 
--> 739     result = _convert_saved_model(**converter_kwargs)
    740     calibrate_and_quantize, flags = quant_mode.quantizer_flags()
    741     if calibrate_and_quantize:

/Applications/anaconda3/lib/python3.7/site-packages/tensorflow/lite/python/convert.py in convert_saved_model(saved_model_dir, saved_model_version, saved_model_tags, saved_model_exported_names, **kwargs)
    635       None,  # input_data, unused
    636       None,  # debug_info_str, unused
--> 637       enable_mlir_converter=True)
    638   return data
    639 

/Applications/anaconda3/lib/python3.7/site-packages/tensorflow/lite/python/convert.py in toco_convert_protos(model_flags_str, toco_flags_str, input_data_str, debug_info_str, enable_mlir_converter)
    214       return model_str
    215     except Exception as e:
--> 216       raise ConverterError(str(e))
    217 
    218   if distutils.spawn.find_executable(_toco_from_proto_bin) is None:

ConverterError: <unknown>:0: error: loc("boosted_trees"): 'tf.BoostedTreesEnsembleResourceHandleOp' op is neither a custom op nor a flex op
<unknown>:0: error: loc("boosted_trees/BoostedTreesPredict"): 'tf.BoostedTreesPredict' op is neither a custom op nor a flex op
<unknown>:0: error: loc("boosted_trees/head/predictions/str_classes"): 'tf.AsString' op is neither a custom op nor a flex op
<unknown>:0: error: failed while converting: 'main': Ops that need custom implementation (enabled via setting the -emit-custom-ops flag):
	tf.AsString {device = "", fill = "", precision = -1 : i64, scientific = false, shortest = false, width = -1 : i64}
	tf.BoostedTreesEnsembleResourceHandleOp {container = "", device = "", shared_name = "boosted_trees/"}
	tf.BoostedTreesPredict {device = "", logits_dimension = 7 : i64, num_bucketized_features = 18 : i64}