* [DOCS] Migrate some markdowns to rst, fix sphinx3 warnings

* Add note block

* Migrate Tensorflow and TFLite in the CI up to 1.15.2

The latest stable version of Tensorflow and Tensorflow lite
in the 1.x series is 1.15.2. The tflite frontend is receiving
support for versions of tflite > 1.14 but there is no consistent
testing.

There are 2 failures already in the source base with tf 1.15
and I'm concerned this will just get exacerbated over time
if we don't have CI picking this up and I view this as a stepping
stone towards stepping CI to TF2.x.

The test failures that I have commented will get issues raised
for them as issues to be fixed.

* Comment out run of qnn_mobilenet_v3_net

This is another test that fails with TFlite 1.15.2

* Skip the qnn_mobilenet_v3 test in the pytest fashion.

* Switch docker versions to support Tensorflow 2.1.0

* Fix up pytest imports and usage.

* Skip these tests currently for Tensorflow 2.1.0

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

* [RUNTIME][CONTRIB] CoreML Runtime

* fix lint

* fix CI

* use xcrun to compile coreml model

This PR removes ir_pass(old style pass functions) in favor
of analysis/transform(new style pass manager).

* Use atexit to remove TempDirectory before interpreter shutdown.
 * Can't rely on complex functions from __del__ anyway.
 * Fixes warning message on my box:
       Exception ignored in: <function TempDirectory.__del__ at 0x12be10680>
       Traceback (most recent call last):
        File ".../tvm/python/tvm/contrib/util.py", line 55, in __del__
        File ".../tvm/python/tvm/contrib/util.py", line 51, in remove
        File "/usr/local/opt/python/Frameworks/Python.framework/Versions/3.7/lib/python3.7/shutil.py", line 509, in rmtree
        AttributeError: 'NoneType' object has no attribute 'path'

This function has recently been removed from LLVM 11. Use alternative
way to obtain vector element count (VectorType::getNumElements) which
works for all LLVM versions.

* Customize SI prefix in logging

* Include unit test

Substitute now takes a std::function to customize more replacing behaviors.

Co-authored-by: Siyuan Feng <hzfengsy@sjtu.edu.cn>

Co-authored-by: Siyuan Feng <hzfengsy@sjtu.edu.cn>

* Restructure imports in tflite frontend.

These python modules are needed for every tflite file parsed.
Factorize out imports of the common most ones.

Now that the import of operator is common, asserts can be commonized.

Loses 473 lines of duplication.

* Only restrict to tflite.Operator

This switch was made in LLVM 11. Previously this function was expecting
mask indices of type uint32_t. This variant is now deprecated.

* Fix oversight in importing tf.compat.v1 as tf.

* Actually disable test for lstm in TF2.1

Since the testing framework actually uses pytest, the version
check needs to be moved.

* The void return type is not None/nullptr, it's VoidType or
   TupleType([]).

* [Topi, ARM] Disbale Winograd for quantized tensors.

* Relaxing float

The legacy Simplify/CanonicalSimplify are now a thin wrapper around the Analyzer.
This PR removes these functions and migrated every place that requires
simplification to enforce Analyzer creation.
The new API would encourage more Analyzer sharing and potentially enable
context-aware analyzer-based simplification.

Rationale: inline is a transformation used in te to
rewrite its internal expressions. It is not a formal IRModule->IRModule transform pass.

Also removed the python test as the test is covered by stage.compute_inline.

* [TIR][REFACTIR] RewriteForTensorCore -> te/schedule

RewriteForTensor depends on the schedule information, which makes it differ
from a typical pass(which should get all the information from the input TIR).

As a result, we refactor it as a SchedulePostProc step for now.
We should revisit it later as we introduce more support for tensor core patterns in the TIR.

* Fix VTA to fit the new IR Pattern

* [TIR][REFACTOR] Remove te::Tensor dependencies from TIR passes.

te::Tensor is an useful object for tensor expression, but brings
un-necessary reverse dependency in TIR nodes such as Provide and Realize.

This PR is a first step to remove this dependency. We will use Buffer in all the places
where the te::Tensor was used. The rough correspondence are:

- Provide -> BufferStore
- Realize -> BufferRealize
- HalideCall -> BufferLoad.

After this change, we can not use IRModule of PrimFuncs cleanly to represent TIR
at any point of the optimizations. Buffer will serve as the abstraction for the TIR data
models to represent the intermediate storages and their constraints.

We still keep Realize/HalideCall and Provide as TIR nodes for now to make the change minimum.
Right after ScheduleOps, we call SchedulePostProcToPrimFunc to canonicalize the temporary IR
generated by TE(which contains these nodes) to the TIR.

The TIR optimizations are now mostly migrated to to the pass manager.
Followup PRs are needed to migrate the remaining few passes.

* Fix dev tutorial

* fix recursion in lower_warp_memory

* post-order mutation

- Migrate BoundCheckers and Simplify
- Migrate RewriteUnsafeSelect and RemoveNoOp
- Migrate UnrollLoop and StorageRewrite
- Migrate InjectDoubleBuffer and InjectVirtualThread
- Migrate LoopPartition and Vectorize
- Migrate CoProcSync, LiftAttrScope, InjectCopyIntrin

We still keep ir_pass registerations for now.
Need a separate PR to refactor the parts before the StorageFlatten.

* [RUNTIME] FastRPC interface for Hexagon runtime

Co-authored-by: Ravishankar Kolachana <quic_rkolacha@quicinc.com>
Co-authored-by: Krzysztof Parzyszek <kparzysz@quicinc.com>

* Explain store offset in a comment in launcher

Co-authored-by: Abhikrant Sharma <quic_abhikran@quicinc.com>
Co-authored-by: Ravishankar Kolachana <quic_rkolacha@quicinc.com>

Change-Id: Ia15c3c8f41f75423814e559f6fdb062098f19464

* support extent(threadIdx.x) < warp_size in lower_warp_memory

* more docs for lower_warp_memory

* [TOPI-ARM] Do not alter layout if layout is NHWC

* Add test.