TFLM output does not match TfLite output for Conv OP

First found during manual testing and confirmed with layer_by_layer_debugger script.
Output:

AssertionError: 
Arrays are not equal


TFLM output does not match TfLite output.
 Subgraph number is 0 
 Layer number is 2 
 The Tensor Index where this output does not match is 46 



Mismatched elements: 80 / 51200 (0.156%)
Max absolute difference among violations: 1
Max relative difference among violations: 1.
 ACTUAL: array([[[[   7,   14,    6,   17,    4,   -5,  -20,    8],
         [   1,  -34,   15,  -12,   15,   15,    7,    6],
         [   2,   15,   -5,   47,    6,   -6,   -3,    0],...
 DESIRED: array([[[[   7,   14,    6,   17,    4,   -5,  -20,    8],
         [   1,  -34,   15,  -12,   15,   15,    7,    6],
         [   2,   15,   -5,   47,    6,   -6,   -3,    0],...

The model in question is attached:

tflite_learn_977.tflite.zip

The difference is between optimized Conv kernel used in full tflite and reference kernel used in tflite micro.

Potentially related:
https://github.com/tensorflow/tflite-micro/issues/2629