* 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.

This file was added before the variable with TVM/RT was initialized.
The initialization overwrote the addition.

Default annotations were incorrectly being named 'defualt'
which results in them not being removed in PartitionGraph.

Signed-off-by: windclarion <windclarion@gmail.com>

* [RELAY][BYOC] Register pattern tables from external codegens

This adds utility functions to support registering
and retrieving pattern tables used by MergeComposite for
external codegens.

Change-Id: I5be165a321440e48b15ff6aff4970e0c67496aaa

* Updated DNNL tests to use pattern table mechanism

* Removed pattern table standalone test

* Change reg to _op

- Changes most of the relay docs to use autosummary.
- Bring relay API docs to the top-level flat view for easier discovery
- Removed a few cases of re-exports.

* add pytorch tutorial code and doc stub

* add more docs

* formatting, more docs

* typo fix

* try make sphinx happy

* add performance section

* type and nit fix

* format fix

* Fix duplicate output in partitiongraph

* Add test case

* Fix test_annotated_regions with duplicate compiler_end outputs

* Revert "Fix duplicate output in partitiongraph"

This reverts commit e1f8ef3f4ca5b2aaa31ace6fa968bb50e5e4d1fa.

* Prevent duplicate outputs in Tuple in PartitionGraph

* Fix lint

* Add another test case for when regions are merged, and when TupleGetItem was duplicated

* Pull GetFunctionOutput out of branch, improve description of GetFunctionOutput

* Use std::move for GetFunctionOutput. Fix typo with testcase name

* Use tvm.transform.Sequential

* [TIR] Remove ProducerConsumer and AllocateNode::new_expr

This PR removes two legacy IR parts in TIR that are deprecated.

ProducerConsumer node only serves as a hint markup and may no longer be
informative after extensive transformations in the pass.
If necessary, we can add related info via AttrStmt.

The new_expr field in the AllocateNode is deprecated since it can just be
replaced by a LetStmt.

- Remove dependencies of passes on ProducerConsumer.
- Remove ProducerConsumer from the IR.
- Remove the deprecated fields (new_expr, free_function) from AllocateNode.

* Fix additional testcases

* get_valid_count updated to have correct results

* speedup nms

* update nms

* revert back nms

* recover one test for get_valid_count