* Fixed onnx test failures when run on a cpu backend

* Updated check_torch_conversion function to include output comparison

[CoreML] Solve CoreML frontend issue of image scaler and padding so that Mobilenet mlmodel can work correctly. (#3800)

* [VTA][TSIM] parallel hardware compilation with macOS and debug support

* simplify

* QNN quantize and dequantize operators.

* addressing review comments.

* addressing review comments.

* Adding new line at the end of the file.

* Adhering to styling guidelines.

* Adding name to contributors.

* Fixing lint issue.

* Fixing file name.

* Removing unnecessary code.

* [Relay][Frontend][ONNX] Add Sign and Equal operators to ONNX frontend

* Dummy change to retrigger integration test

* Refactor.

* update

* update

* update

* update

* update

* update

* [VTA][Chisel] scale dram base address in hardware instead of runtime

* remove trailing spaces

* Support BatchMatMul with shapes greater than length 3

* Fixes

* Add tests

* Remove dependency on Python3

* Clean up

* Merge with master

* Resolve comments

* [VTA][Chisel] run all unittests by default

* better naming

* add generated unittest folder to clean rule

* building TSIM specific library along with fast simulator to quickly switch between dlls

* cmake controlled TSIM libraries

* always build tsim driver in either simulation modes

* build DLLs based on CMAKE flags

* updating the jenkinsfile

* small restructuring

* reducing the cmake flags

* update instructions

* reverting to 3 flags

* update Jenkinsfile

* adding new line

* enabling TSIM unit and integration tests

* fix description

* temporarily disabling task_python_vta tests in CPU Build stage

* move CPU tests in unit test stage

* stage  reorg

* better make

* disabling TSIM tests for now

* reverting some restructuring

* fix

* added alutest

* fix indent

* name change for cycle

* improved data gen and infra

* added alutest

* fix indent

* name change for cycle

* improved data gen and infra

* fix space

* fix indent

* fixes

* aluRef

* fix randomarary

* add

* Revert "add"

This reverts commit 87077daebbe055dee11f80e37da3a6291138e0f0.

* Revert "fix randomarary"

This reverts commit df386c1e660eb6ebcff1a1f905610573676f1589.

* Revert "aluRef"

This reverts commit 8665f0d4a7b12b796b2cb1ca6bf9cfe5613ee389.

* should fix dlmc-core

* [ARITH] Simplify casts of constants 0 and 1

* [EXPR] is_const_value to check whether non-ints are consts

* Revert "[EXPR] is_const_value to check whether non-ints are consts"

This reverts commit 7e1b3462e3f74fd0afb1541d72978107cfa23c30.

* Use tvm::cast

* Added relay and topi mirror_pad operator.

* Added mirror_padding to tensorflow frontend.

* Added mirrorpad testing in tensorflow frontent.

* Added space_to_depth in tf frontend.

* Added tests for spacetodepth.

* spacetodepth bug fix.

* Lint fix

* Added mirror pad python attrs.

* Pad code formatting.

* Syntax improvement

* Hopefully last lint fix

* Don't replace reduction init axis with new axis if bound to a thread.

* Linter.

* Reduce bind test case.

* Guard test on CUDA support.

* [CUDA TE TESTS] Add rfactor predicate test, add global bx and tx.

* [CUDA TE TESTS] Add loop partition test for simple rfactor case.

* [bugfix] tvm.scan follow by tvm.compute segfault

* more strict bound condition check

* access k + 1 -> k

* fix scan test

* Revert compile_cmd kwarg name change

* Fix binutil tests

* Improve graph tuner dealing with Tuple

* Add test case

* Move some data out of _base.py

* Fix lint

* aot

* save

* save

* fix test

* remove vta changes

* lint

* use pip3 for python3

* make python3 as default

* reproduce error

* fix

* lint

* lint

* fix

* fixes

* [Relay] [Quantization] WIP - Common files for the qauntization work.

* [Relay] [Quantization] WIP - Prototyping requantize op.

* Requantize operator implementation.

Requantize converts one quantized tensor representation to another quantized
representation. The PR has following implementation features

- Requantize operator defined in qnn namespace - relay.qnn.requantize
- Lowering of the requantize to exisiting Relay operators
- Integer fixed point implementation of requantize
    - Two rounding modes - FE_UPWARDS (round towards infinity) and
    FE_AWAY_FROM_ZERO (std::round behavior)
- Floating point implementation as well, that can act as reference or can be
used for devices when FP32 computation is not used.
- Unit test cases

Relevant Issue - https://github.com/dmlc/tvm/issues/2351

Credit to TFLite and GemmLowp to provide reference implementations.

* Typo and lint fixes.

* Doc fix.

* Uncommenting the lint script (fixing mistake).

* Modifying the unit tests.

* Moving C++ files into src/relay/qnn

* Moving python files to python/tvm/relay/qnn. Some minor fixes.

* Moving the attrs.h inside the include directory.

* Pushing files that I forgot earlier. Changing util location.

* Incorporating comments. API change. Lint fixes.

* Modifying the GetFixedPointMultiplierShift API as per comments.

* Forgot the dialect change.

* Changing rewrite to qnn_lower.

* Renaming Quantize to Qnn for clarity.

* Remove use_int_domain.

* Incorportaing review comments.

* Adding API doc for QNN dialect.

* Move the qnn_lower pass to transform namespace.

* Moving from expr to module. Adding namespace in C++.

* Minor sentence rewrites. Added qnn namespace.

* Added the API doc.

* Chanding default out_dtype to int8. Adding a test with in/out_dtype as uint8.

* Style fixes. Better error messages.

* Adding documentation.

* More documentation fixes.

* Adding out dtype check for requantize.

* Adding corner case for FP32 to fixed point conversion.

* Adding extra line.

* Documentation fix.

* Adding static inline.

* Incorporating jackwish comment. Removed idtype from requantize lowering.

* Removing Quantize/Dequantize code. Restricting Requantize to (u)int8/int32.

* Style fixes.

* Fix the docs.

* Move to Legalize API.