[TFLite] Add int8 and int16x8 support for LOG operator
Hi @Tessil, one error left to fix. The E2E tests (whose params are in part generated by elementwise.py) are failing. Specifically when quant_16x8=True for rsqrt fails with "Type INT16 is unsupported by op Rsqrt." Then, some of the log tests are generating different numbers from what is expected. Let me know if you have any troubles reproducing, thanks. Hi @grantjensen I wasn't able to reproduce the issues.

I ran the following two commands with success:
`bazel run //tensorflow/lite/testing:generate_examples -- --zip_to_output=log -- --output_path=test`
`bazel test //tensorflow/lite/kernels:elementwise_test`

I have updated the PR though to remove QI16 from the MLIR TFL_LogOp definition as it's not necessary currently (no official support for int16x8 MLIR quantizer). ` bazel test //third_party/tensorflow/lite/testing:zip_test_log`
 ` bazel test //third_party/tensorflow/lite/testing:zip_test_rsqrt` @grantjensen Thank you, it seems I had the wrong command, I fixed the tests. Note that I reduced the max_value as int8 isn't sufficient to represent the quantized range from log(0.1) to log(100) with good enough precision.
Hello,

This PR adds int8 and int16 quantization support for the LOG operator using a lookup table.


Thanks,
Thibaut