This really seems:

  

      github.com/tensorflow/tensorflow
  

  
    
  
	  
  

  
    
      Failed to convert weights to 8 bit precision: "Quantize weights tool only supports tflite models with one subgraph"  21
    

    
      
        opened 
        
          
        
        Dec 18, 2019
      
      

        
          closed 
        
          
        
        May 19, 2021
      
        

      
        
          
          rutrilla
        
      
    

    
        TF 2.1
        comp:lite
        stalled
        stat:awaiting response
        type:feature
    
  


  
    ### System information
- **Have I written custom code (as opposed to using a st…ock example script provided in TensorFlow)**: Yes
- **OS Platform and Distribution (e.g., Linux Ubuntu 16.04)**: Google Colab (GPU)
- **TensorFlow installed from (source or binary)**: Binary
- **TensorFlow version (use command below)**: 2.1.0-dev20191217 
- **Python version**: 3
- **Exact command to reproduce**:

```bash
!pip install tf-nightly
import tensorflow as tf
from tensorflow.keras import Sequential
from tensorflow.keras.layers import GRU, Dense, Dropout

model = Sequential()
model.add(GRU(100, activation='relu', return_sequences=False, input_shape=(128,2)))
model.add(Dropout(0.2))
model.add(Dense(11, activation='softmax'))

converter = tf.lite.TFLiteConverter.from_keras_model(model)
converter.experimental_new_converter = True
tflite_model = converter.convert()
converter.optimizations = [tf.lite.Optimize.OPTIMIZE_FOR_SIZE]
tflite_model_quant = converter.convert()
```

### Error message
```bash
E tensorflow/lite/tools/optimize/quantize_weights.cc:351] Quantize weights tool only supports tflite models with one subgraph.
```

### Describe the problem
First, I used the new converter (with the experimental flag converter.experimental_new_converter = True) to convert an RNN model from TensorFlow to TensorFlow Lite's flat buffer format, as suggested in the issue #32608.

This works correctly, but then when I try to perform a post-training weight quantization, I got an error saying that the quantize weights tool only supports tflite models with one subgraph. 

Is there a problem with my procedure? Or is that feature not yet supported? In that case, I would like to request this feature.

Thanks in advance for your help.

### Source code / logs
The attached file can be used to reproduce the error with a trained model (.h5). 
[GRU_1L.zip](https://github.com/tensorflow/tensorflow/files/3974453/GRU_1L.zip)