[Tracking Issue] TFLite operator support

[leandron]

In https://github.com/apache/tvm/issues/9187 we implemented quantised version of operators in TFLite frontend. Recently, I just noticed a few more operators (with varying priorities) that can be taken as beginner friendly tasks, for someone who's starting in TVM.

I'm creating this as a tracking issue to mark those operators that need to have quantization support implemented and tested:

• [x] FLOOR_DIV (#15724)
• [x] FLOOR_MOD (#15733)
• [x] DIV (#15768)
• [x] POW (#15798)
• [ ] REVERSE_SEQUENCE (#15915)
• [x] SQUARE (#15914)
• [x] ELU (#15821)
• [ ] LOCAL_RESPONSE_NORMALIZATION (LRN)
• [ ] L2_NORMALIZATION
• [x] MIRROR_PAD (#16243)
• [ ] ARG_MIN (#15922)
• [x] NOT_EQUAL (#15769)
• [x] LESS (#15746)
• [x] LESS_EQUAL (#15790)
• [x] GREATER_EQUAL (#15775)

For each operator above, there are actions to be taken:

• Remove the conditional block if self.is_quantized(op): ...
• Implement unit tests
• ask any committer in the project to update this issue, reflecting the PR to support the operators on the list above

https://github.com/apache/tvm/pull/9165 can be used as an example.

In case you're interested, a good starting point is the TFLite frontend: https://github.com/apache/tvm/blob/bee073b0c8e8625216184a2dbb0204c0a376fc26/python/tvm/relay/frontend/tflite.py#L78-L185