Fixed bugs that occured when using bitwise operators on floating point type expressions. Further crash when using ops <<, >>, %. Finally added regression tests for both types of bug. (#4892)

- Move the related files to tvm.te
- Move build_module.py to tvm.driver

* Fix bug in re-processing call node

* Add test

* Add to main

* temp changes to work from another machine

* fix rest of tests

* fix test_reuse_call_merge

* fix merge

Co-authored-by: Jon Soifer <jonso@microsoft.com>

various minor editorial updates - style, grammar, typos.

* add additional switch to handle nested call node

* Fix VM compiler for while loop with free var

- Do not emit __shared__ etc. as part of type for casting

- Fix fp16 reduction kernels with compiler errors:

  "no operator "+" matches these operands, volatile half + volatile half

  This patch inserts casts to remove volatile type qualifier following
  volatile loads (fp16 only). CUDA fp16 library headers should add
  volatile member functions.

- Update have_fp16 to include compute 6.1 GPUs, which do support fp16,
  although their fp16 throughput is low. Updated tests.

Signed-off-by: Wei Pan <weip@nvidia.com>

* Support range in index based tuners

* Address comments

* Remove __*state__

* trigger CI

* add test case for per channel dense

* add unit arg in tflite frontend

* update qnn legalize test

* fix output dim index

* [QNN] Doc fix on quantize and convolution

* update test

- This allows to better utilize the memory bandwidth

- Note that not all cases are vectorized for fp16 datatype. For
  instance, when the size is not a multiple of 1024, the inner loop
  may be an expression that cannot be vectorized. In this case, a
  small inner loop is still benefical for latency hidding.

Signed-off-by: Wei Pan <weip@nvidia.com>

- Move related files into the corresponding location as in C++
- Keep the top-level TVM API backward compatible to make minimum changes in topi

Co-Authored-By: Wei Chen <ipondering.weic@gmail.com>

Co-Authored-By: Wei Chen <ipondering.weic@gmail.com>

Add tuneable conv3d_ndhwc schedule

* [FRONTEND][TFLITE] Add support for TFLite_Detection_PostProcess

This adds support for the custom operator
TFLite_Detection_PostProcess which is commonly used in
object detection networks such as SSD Mobilenet. It
only adds support for when use_regular_nms = False.

Change-Id: I819b253c0eb6f0fa55da65d2634e09359b888828

* Added a test for the tflite custom op

Change-Id: Ie5baa092deae9a8bcffd2ebd9f6d346b90e58afd

* Removed trailing comma

Change-Id: Ib08f02b5f1a59a883048bfb36e4321152cd2e7f2

* Added spaces between divide

Change-Id: If1171fc03d211a809cedeb800804394972af4060

* Formatted comment

Change-Id: I3ce7e69b8d2c73aec57369c1c64ea1eec07f087b

* Reduced line length in test

Change-Id: I49eaafc3369070f8f3e85fbb965ad20972096c68

* Set random seed for test

Change-Id: I542a787d11422ea83c52147b2cb1144fcef0dd77

* Fixes to style

Change-Id: I2971b8ecebe08c882b2481a99f67cfbe515e0b1f

* Assert for incorrect number of inputs

Change-Id: I393f3b3b62be73e427498d98456fb1d5a214e0af

* Change comparison to pass linting

The linter was updated, so I needed to fix
a small style issue as a result.

Change-Id: Ia3c954565a00de92e7fb1912eae9ed9875d60c7c

Move the related target modules into tvm.target.

API change:
- tvm.target.current_target -> tvm.target.Target.current
- tvm.datatype -> tvm.target.datatype

* [REFACTOR][PY][API-CHANGE] establish tvm.ir, migrate corresponding relay files.

This PR establishes tvm.ir and migrates the corresponding relay
files into the new folder.

API Change:
- relay.Module -> tvm.IRModule

* Update with ADT

* Migrate transform

* address comments

* Migrate module

* Migrate json_compact

* Migrate attrs

* Move LoweredFunc to stmt temporarily

* temp migrate container

* Finish migrate container

* Fix onnx import bugs

Fix onnx attributes of string type incorrect handling
Merge symmetric padding of Conv to symmetric form

* Only merge symmetric padding for conv2d

* [TFLite] Using real image for QNN testing.

* Setting seed for SSD mobilenet for fixed input.

* Support quantized Pad op.

* Remove unnnecessary line.

* Ina comments.

* [Relay] Added MergeComposite pass

This pass allows for patterns to be wrapped
in a function marked with 'Composite' and a
composite function name. This is intended to be
used with the external codegen for the cases where
an external operator maps to multiple Relay
operators. In that case, the mapping can be expressed
as a pattern and assigned a name.

For more information on this pass and its motivation,
see the RFC:
https://discuss.tvm.ai/t/rfc-external-codegen-defining-composite-relay-operators/5470

Change-Id: Icb1b803a9f0ac57c529143200228f3bb5793afc0

* [Relay] Merge composite tests

Added tests for the merge_composite pass.

Change-Id: I1728b4a05b0c1c36140a40f1afe028fde62185dd

* Merge composite additional test

Change-Id: I9bc7d6053c575e9468ac5abc31214c6ad8507e46

* Support priority order in merge_composite

The order in which the patterns are matched
was currently random as an unordered_map was
used to store the pattern table. This uses
arrays instead so that a distinct priority
order of matching can be defined. Additional
tests have also been added to verify this
behaviour.

Change-Id: Ief347df4262639138d5d9d7c8cee7ef233af7b56

* Improved merge composite docs

Change-Id: Ie3a72045ecc3f13ad3c302fbdf192b7296a306a8

* Removed unused variable

Change-Id: I7814d5fde368ffaf1b3d6d806060c774c7720364

* Remove unnecessary op check

Change-Id: I38e78d2acd5b86cb8e837be72ff9d72cd10bcf33

* Improve styling on composite function creation

Change-Id: I37add1c3134e0b5d5085fe1eb9daf8e06890fa8c

* Comment reword

Change-Id: Ie05872dcbbe0c3e1190b0597083b9a64e6b66c66

* Stylistic changes to avoid std::move

Change-Id: I43a93995bbf10530399900c992aa99dd4ae4575f

* Relax a check in ExtractPattern

Change-Id: I0faef77a66c55f83f09e6e47c561ffaea63dedfa

* Remove new line

Change-Id: Ifdd02c12087a7e1a0a9b54825669bc0de8f13c3d

* Removed MatchPattern from MergeComposite

This is not necessary now that ExtractPattern
can fulfill the same purpose.

Change-Id: I14dc020afa8e50f2df4c0a2efb88a011987f8196

* Removed a new line

Change-Id: I8b50f0c9069aa1bcaccbe68eb421031f01a64842

* Improved docs for merge composite

Change-Id: Ib1959a35c856e7ea5639de2e4ef314a54f44caf5

* Fixed free vars in test

Change-Id: I2b7f273db275964ec0e9820560663f0808adee79

* Handle case where root arg might not be a call

Change-Id: I4eeea3ce723d3ba337d110dcc690377daebe8626

* Removed blank line

Change-Id: I07f5392c0e95cfe3cfa5c333703cc6f82d6034fb

* Change to CHECK_EQ

Change-Id: I5c5d62d3cd57f72508b30b926f72091ae6f0d1cc

* Revised a conditional

Change-Id: I23a7897ca15a7cd076db5039dc653a4b8c27e803

* Improved doc styling

Change-Id: I377f0a1c1ac70f3b8d7584b0c49bddc8c6c134ef

* Fail extraction if vars conflict

Change-Id: I78e36d805e8ed6b55e61d490212a967c857554a4

* Added further merge composite tests

Change-Id: Ib1d800409fca4c1834c7fe0cab5a26ab99a26820

Co-authored-by: lhutton1 <35535092+lhutton1@users.noreply.github.com>

Fixed bug in ExprOp that caused bitwise operators to fail when a basic python type was on the left hand side of the expression. Added regression test for crashing cases. (#4852)