I have built the classification model using tensorflow estimator after saving the model , when converting it into tensorflow lite it shows an error

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import tensorflow as tf
converter = tf.lite.TFLiteConverter.from_saved_model("/content/drive/MyDrive/tensorflowtest/1618754788") #path to the SavedModel directenter code hereory
converter.target_spec.supported_ops = [
tf.lite.OpsSet.TFLITE_BUILTINS, # enable TensorFlow Lite ops.
 tf.lite.OpsSet.SELECT_TF_OPS # enable TensorFlow ops.
]

Model Saves Without Any Error

tflite_model = converter.convert()

When i execute this line I get this Exception

  ConverterError                            Traceback (most recent call last)

/usr/local/lib/python3.7/dist-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)
    295       return model_str
    296     except Exception as e:
--> 297       raise ConverterError(str(e))
    298 
    299   if distutils.spawn.find_executable(_toco_from_proto_bin) is None:

ConverterError: <unknown>:0: error: loc("head/predictions/str_classes"): 'tf.AsString' op is neither a custom op nor a flex op
<unknown>:0: error: failed while converting: 'main': 
Some ops in the model are custom ops, See instructions to implement custom ops: https://www.tensorflow.org/lite/guide/ops_custom 
Custom ops: AsString
Details:
    tf.AsString(tensor<?x1xi64>) -> (tensor<?x1x!tf.string>) : {device = "", fill = "", precision = -1 : i64, scientific = false, shortest = false, width = -1 : i64}

I tried Using tensor flow nightly but error still remains I am trying to build a classification model using tensorflow as then i want to convert it into tensorflow lite for Android App if you have any other appproch without converting into tensorflow lite that would be acceptable too

tensorflow-lite tensorflow machine-learning
1 Answers

The TF select option in the TFLite product does not allow tf.AsString op yet. For such cases, you can report the feature request at here.

The above op isn't included the TF select's allowed list, which can be fixed by adding the relevant code like this commit. It would be great if you can create a such PR.

The fix is submitted and the AsString op will be available through the TF select option since the tomorrow's TensorFlow nightly version.

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