* 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.

* [DOCKER] Fix missing apt https transport support

* [DOCKER] Drop superflous explicit sudo's

* add build gcn tutorial

* add dgl to docker file

* add dgl to docker file

* Apply suggestions from code review

Co-Authored-By: 雾雨魔理沙 <lolisa@marisa.moe>

* add dgl to docker file

* rerun checks

* Revert "add build gcn tutorial"

This reverts commit dbe8b5f0e02a13fdd586a9faa58fd1326653afb0.

* resolve git issue

* resolve git issue

* resolve git issue

* apply marisa's comment

* Add LayerNorm op

* update

* fix

* Add mean_std and mean_variance

* add std and update doc

* add license

* x

* lint

* x

* fix

* fix doc

* Fix mxnet converter for hybrid block

* tweak

* fix rebase

* fix

* add test

* [Relay] Rewrite pass.

This pass transforms an expression to other expression.

This pass has many usecases
 * Replace a expr to another expr, if the other expr has faster performance.
 * For ASICs, we might want to modify the inputs to adapt to the HW support.
 * Alter op layout can work in conjunction with this pass.

The supporting usecase is the Intel i8 x i8 conv. Intel HW supports u8 x i8 conv
in HW. Using this pass, we can replace an i8 x i8 conv to a sequence of
operators where one of the operators is now u8 x i8 conv. This will also help
automatic quantizaion performance.

* Better API name.

* Removing the conv2d legalization for x86. Will send a separate PR.

* Test name changes.

* Registering one funtion to register FTVMLegalize.

* Better comments.

* Fix the tile_rx and tile_ry issue.

    Note that this patch depends on pull request #9 in tvm-distro.

This includes changes to build TVM runtime for Hexagon.

* clean up tf frontend

* fix get_relay_op

* fix

* fix interpreter

* add build gcn tutorial

* add transpose operator for square sparse matrices

* remove extra files

* change loop tag

* comply with lint

* comply with lint -- line too long

* comply with lint

* lint check

* lint check

* lint check

* apply marisa and theirry's reviews

* save

lint some

lint

lint

add charrnn

save

save

save

remove debug

remove debug

remove space

refactor

save

rewrite dce

* reset files

* join -> meet

* lint

* address review comment

* wordsmith

* Update Softmax compute and CPU schedule

* Add C++ compute

* Fix schedule

* Update CUDA and OpenGL schedules

* Fix log_softmax

* Fix hls and opengl schedules

* Fix CUDA schedule

* Fix gather_nd in Relay

* Add test cases for gather_nd.

* added wholething

* changed build and makefile

* fix

* lint

* [AutoTVM] Fix hang/crash issues on feature extraction

* Update xgboost_cost_model.py

* fix lint

* add dgl to docker file

* add dgl to docker file

* [TOPI] Memoize winograd matrix

* lint

* Fix name

* [Relay][Quantization] Support floating-point scale

* [Relay][Quantization] KL-divergence calibration on dataset

* Fix unhandled LeftShift case in QuantizeRealize

* Fix lint

* drop QBias

* fix lint

* address comments

* address comments

* Update comments

* address comments

* lint

* kQIdentity = 0

* [Relay][VM] Support execution on devices

* Reduce Copy calls

* Cleanup

* Lint

* CR comments

* Merge test into test_vm.py