* [RELAY][FRONTEND] Tensorflow frontend support.

* 	* LSTM removed for a while.

* 	* basic ops are good.

* 	* nn wip

* 	* wip

* 	* python2.7 corrections.

* * NN ops are good.

* * e2e models working good

* 	* all good except LSTM

* 	* rebase, tutorials and CI trigger.

* 	* CI errors.

* 	* enable opt_level=3

* 	* Docstrings cleanup. testing.tf utils moved to relay from nnvm.

* 	* tutorials update.

* 	* LSTM work good now.

* 	* Rebase

* 	* CI error

* 	* enable PTB.

* 	* rebase.

* 	* tutorials

* Update python/tvm/relay/frontend/tensorflow.py

Co-Authored-By: srkreddy1238 <sivar.b@huawei.com>

* 	* review comments.

* 	CI fix.

* 	* review comments.

* Enable reverse in reshape

* Fix lint and typo

* Put reverse_reshape into a separate op

* Fix pylint

* [Relay][Frontend] Add Caffe2 Support

* [Relay][Frontend] Add Caffe2 Support (fix unsed import)

* [Relay][Frontend] Add Caffe2 Support (fix caffe2 model import)

* [Relay][Frontend] Add Caffe2 Support (fix model install and reflect code reviews)

* [Relay][Frontend] Add Caffe2 Support (fix caffe2 model import)

* [Relay][Frontend] Add Caffe2 Support (fix caffe2 model import)

* [Relay][Frontend] Add Caffe2 Support (fix caffe2 model import)

* [Relay][Frontend] Add Caffe2 Support (fix caffe2 frontend import)

* [Relay][Frontend] Add Caffe2 Support (rename function name in test_forward)

* [Relay][Frontend] Add Caffe2 Support (fix caffe2 model import)

* [Relay][Frontend] Add Caffe2 Support (fix caffe2 model import)

* [Doc] Caffe2 frontend tutorial

* [Doc] Caffe2 frontend tutorial

* [Doc] Caffe2 frontend tutorial

* [Relay][Frontend] Add Caffe2 Support (remove unsed file)

* [QUANTIZE] Quantization implementation.

* Update.

* Update.

* Update.

* Update.

[TFLite][Python 2] Solve TFLite frontend python 2 compatibility and Modify TFLite whl files path (#2529)

* [Relay][Frontend] Add CoreML Support

* pip install six in CI

* remove triggering nnvm coreml test

* set opt_level=2 for nnvm coreml test case

* [AUTOTVM] typo

* trigger CI

* Support TFLite FP32 Relay frontend.

* Fix lint issue

* Remove unnecessary variables and packages

* Add method doc string

* Fix capital letter of method doc string

* Add TFLite FP32 Relay frontend based on latest code

* Merge the latest code

* Solve cython issue with relay type inference

* Modify code based on suggestions

* use IPV6 instead of IPV4

* backward compatible

* add error report

* fix linter

* more linter

* fix the python2 api

* Avoid runtime exception when file doesn't exist

* Update the check based on feedback

* Revert the old fix

* on the way to enable hybrid schedule

* I think I am done with imperfect loop split?

* copyright watermark

* loop annotation

* fix lint

* fix lint 1

* shit!

* loop reorder supported

* support bind to add some tests

* fused tested

* imperfect loop testcase

* fix lint

* add bind testcase

* fix doc

* fix online edit typo

* resolve @mercymercy review

* fix indent

* i should convince myself it is not flaky test first

* fix test hybrid

* how many flaky test are you expecting; i ball ball u to let me pass

* rebase halide...

* init

staging on

final save before staging

save

init ver

init ver

ll stuff

save

add failing test

add file

pass test

fix error

huh?

save

Add test changes

Fix fusion with nested tuples

Fix reverse mode test

More hacking

Clean up AD

Hacking on reverse mode

Fix issue in reverse

save

fix lint

fix lint

fix lint

save

save

fix

support neg

address some comment

add back file

save

save

* save

* save

* save

* lint

* fix lint

* save

* fix

* Add GEMM autotvm template for x86

* Fix tophub link

* Disable RPC server logging file delete

* Update dense autotvm template

* Fix tests

* Fix lint

* tweak

* Register two templates with different tags

* Add support for passing arguments by args and kwargs when using executor

* Fix linting

* Update comment, and add arity checking

* Small tweak to error message

Add trace call expr to allow trace Tensor data
at the runtime. By default the default handler
is enabled which prints a tracing data to stdout,
otherwise user should specify a call_back as
global_function (aka @tvm.register_func).

The issue is related to:
https://discuss.tvm.ai/t/idea-trace-expression/945