[TFLite] Add support for int8 quantized DivOp
Hi @sirakiin Can you please review this PR ? Thank you! Hi @sirakiin Can you please review this PR ? Thank you! Hi @sirakiin Can you please review this PR ? Thank you! Hi @lgeiger Can you please resolve conflicts? Thank you! Hi @lgeiger Can you please resolve conflicts? Thank you! Hi @lgeiger Can you please resolve conflicts? Thank you! > Hi @lgeiger Can you please resolve conflicts? Thank you!

@gbaned Rebased the PR. Out of interest will this ever be merged? It's been 10 months since I opened it without a response... Hi @rascani Can you please review this PR ? Thank you! Hi @rascani Can you please review this PR ? Thank you!
This PR adds support for quantized int8 inputs and outputs to the `div` op. TFLite Micro added support for int8 quantized divides in https://github.com/tensorflow/tflite-micro/pull/1196, but until now the MLIR based converter would force the op to stay in float due to missing TFLite support for it. This PR fixes this and adds support for int8 quantized divide ops to TFLite and the converter.