esrgan re-convert to tflite fail
Hi @xufuji456 

The ESRGAN expects the input shape of `50x50x3`, hence we need to resize the input tensor before allocating the tensors.
```
# Load TFLite model and allocate tensors.
interpreter = tf.lite.Interpreter(model_path=esrgan_model_path)
interpreter.resize_tensor_input(input_details[0]['index'],[1,50,50,3])
interpreter.allocate_tensors()
```
Please find the [gist](https://colab.research.google.com/gist/pjpratik/e31c0319abbb9efb94b6c2c11af90537/61348.ipynb) modified to be comptatible for TF2.13 and let us know if helps.

Thanks.  @pjpratik Thank you for your reply.
 if I want to convert into 640x360 resolution, how should I do?
I see here support re-convert model https://github.com/tensorflow/examples/blob/master/lite/examples/super_resolution/ml/super_resolution.ipynb Hi @xufuji456 

The ESRGAN produces x4 Super Resolution Image from images. If you want to convert to 640x360 resolution, you may need to pass 160x90 image and modify the input accordingly.
```
concrete_func.inputs[0].set_shape([1, 160, 90, 3])
```
and after the conversion, accordingly we need to to resize the tensor 
```
interpreter.resize_tensor_input(input_details[0]['index'],[1,50,50,3])
```
and the pass the input image matching the size.

Thanks.
 Hello @pjpratik 
It does work, thanks a lot. 
ESRGAN has a good result, However, it takes a lot of times.
If I want to use SRGAN with x2 super resolution, for example, convert 640x360 into 1280x720.
How to convert the model into TensorFlow-lite, that running on platform of Android. Hi @xufuji456 

Glad it worked.

If you would like to use SRGAN, you have convert SRGAN into TFLite model using different conversion options like `from_saved_model` format and `from_keras_model`.

Please refer to this [document](https://www.tensorflow.org/lite/models/convert/convert_models) on different ways of model for converting to TFLite.

Once the model is converted with specified model input dimesnions, it can be used for inference on Android.

Thanks. This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you. Are you satisfied with the resolution of your issue?
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/61348">Yes</a>
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=No&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/61348">No</a>

### 1. System information

- OS Platform and Distribution: macOS 12.2.1; Apple M1; MacBook Pro
- TensorFlow installation : pip3 install tensorflow
- TensorFlow library: 2.13.0

### 2. Code

Provide code to help us reproduce your issues using one of the following options:

#### Option A: Reference colab notebooks

1)  Reference [TensorFlow Model Colab](https://colab.research.google.com/gist/ymodak/e96a4270b953201d5362c61c1e8b78aa/tensorflow-datasets.ipynb?authuser=1): Demonstrate how to build your TF model.
2)  Reference [TensorFlow Lite Model Colab](https://colab.research.google.com/gist/ymodak/0dfeb28255e189c5c48d9093f296e9a8/tensorflow-lite-debugger-colab.ipynb): Demonstrate how to convert your TF model to a TF Lite model (with quantization, if used) and run TFLite Inference (if possible).

```
convert tflite:  https://github.com/tensorflow/examples/blob/master/lite/examples/super_resolution/ml/super_resolution.ipynb
```

#### Option B: Paste your code here or provide a link to a custom end-to-end colab

```
test demo:  https://github.com/tensorflow/examples/tree/master/lite/examples/super_resolution
```

### 3. Failure after conversion
If the conversion is successful, but the generated model is wrong, then state what is wrong:

- Model produces some errors

### 4. (optional) RNN conversion support
model is esrgan

### 5. (optional) Any other info / logs
case1.  enable optimize like "tf.lite.Optimize.DEFAULT",  load model fail: Didn't find op for builtin opcode 'DEQUANTIZE' version '5'
case2. disable optimize, set_shape 50x50, run fail msg: Something went wrong when copying input buffer to input tensor
case3. disable optimize, set_shape 640x360, run fail msg: signal 11 (SIGSEGV): stack pointer is in a non-existent map; likely due to stack overflow.  function crash: SuperResolution.cpp->DoSuperResolution() line at: TfLiteInterpreterAllocateTensors
