RuntimeError                              Traceback (most recent call last)
<ipython-input-4-00def698b3cd> in <module>()
     23
     24 converter.optimizations = [tf.lite.Optimize.DEFAULT]
---> 25 tflite_model = converter.convert()
     26
     27 tflite_filename = model_checkpoint_name + "_" + quantization_strategy + ".tflite"

3 frames
/usr/local/lib/python3.6/dist-packages/tensorflow/lite/python/lite.py in convert(self)
   1916         None value for dimension in input_tensor.
   1917     """
-> 1918     return super(TFLiteConverter, self).convert()
   1919
   1920

/usr/local/lib/python3.6/dist-packages/tensorflow/lite/python/lite.py in convert(self)
   1283
   1284     if calibrate_quantize:
-> 1285       result = self._calibrate_quantize_model(result, **flags)
   1286
   1287     if self._experimental_sparsify_model:

/usr/local/lib/python3.6/dist-packages/tensorflow/lite/python/lite.py in _calibrate_quantize_model(self, result, inference_input_type, inference_output_type, activations_type, allow_float)
    474       return calibrate_quantize.calibrate_and_quantize(
    475           self.representative_dataset.input_gen, inference_input_type,
--> 476           inference_output_type, allow_float, activations_type)
    477
    478   def _is_unknown_shapes_allowed(self):

/usr/local/lib/python3.6/dist-packages/tensorflow/lite/python/optimize/calibrator.py in calibrate_and_quantize(self, dataset_gen, input_type, output_type, allow_float, activations_type, resize_input)
     96         np.dtype(input_type.as_numpy_dtype()).num,
     97         np.dtype(output_type.as_numpy_dtype()).num, allow_float,
---> 98         np.dtype(activations_type.as_numpy_dtype()).num)
     99
    100   def calibrate_and_quantize_single(self,

RuntimeError: Mismatch between number of weight maxs and channels: 1 vs 32