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
- Reference TensorFlow Model Colab: Demonstrate how to build your TF model.
- Reference TensorFlow Lite Model Colab: 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