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

* [PYTORCH]take, topk op support

* Ci Failure fix

* Windows Support for cpp_rpc

* Add missing patches that fix crashes under Windows

* On Windows, use python to untar vs wsl

* remove some CMakeLists.txt stuff

* more minor CMakeLists.txt changes

* Remove items from CMakeLists.txt

* Minor CMakeLists.txt changes

* More minor CMakeLists.txt changes

* Even more minor CMakeLists.txt changes

* Modify readme

[Runtime][Relay][Cleanup] Clean up for memory pass to enable heterogenous execution support. (#5324)

* Cleanup type pack and unpack for tuples.

* Clean up the memory_pass using common helpers

* Clean up memory.cc

* Refactor pass

* Add doc strings

* Fix CPPlint

* Fix PyLint

* Fix

* Apply suggestions from code review

Co-Authored-By: Zhi <5145158+zhiics@users.noreply.github.com>

* Fix typo

Co-authored-by: Zhi <5145158+zhiics@users.noreply.github.com>

* when passing --net=host to build.sh it needs to be also
   sent as --network=host to "docker build", so that both
   build and run will use the same network configuration

The older variants of CreateCall have been deprecated and were recently
removed from LLVM. This caused compilation failures.

Previously MakePackedAPI was in the target independent stage,
but never the less requires the device_type information that will be
binded at a later target dependent stage.

The previous implementation was due to the limitation of LoweredFunc
which can not carry buffer_map info(so they have to be lowered right away).
This is no longer the case after the unified IR refactor.

This PR migrates MakePackedAPI to a target dependent stage
and removes the un-necessary BindDevice pass.

* [RELAY][PYTORCH]isNan, isinf, isfinite, ceil, clamp, round ops

* Review comments

* MXNet swap axis

* MXNet swap axis

* swap axis review comment

* swap axis review comment

* Fix high-low bit bug in __pack_half2

* Fix vector load

* Add unit8 support for PrintVecElemLoadExpr and BroadcastNode

* Remove duplicated output args

* address comment

* fix codegen c

* improve comment

* VisitExprDefault_

* deduce type

* [RUNTIME] Allow non-nullable ObjectRef, introduce Optional<T>.

We use ObjectRef and their sub-classes extensively throughout our codebase.
Each of ObjectRef's sub-classes are nullable, which means they can hold nullptr
as their values.

While in some places we need nullptr as an alternative value. The implicit support
for nullptr in all ObjectRef creates additional burdens for the developer
to explicitly check defined in many places of the codebase.

Moreover, it is unclear from the API's intentional point of view whether
we want a nullable object or not-null version(many cases we want the later).

Borrowing existing wisdoms from languages like Rust. We propose to
introduce non-nullable ObjectRef, and Optional<T> container that
represents a nullable variant.

To keep backward compatiblity, we will start by allowing most ObjectRef to be nullable.
However, we should start to use Optional<T> as the type in places where
we know nullable is a requirement. Gradually, we will move most of the ObjectRef
to be non-nullable and use Optional<T> in the nullable cases.

Such explicitness in typing can help reduce the potential problems
in our codebase overall.

Changes in this PR:
- Introduce _type_is_nullable attribute to ObjectRef
- Introduce Optional<T>
- Change String to be non-nullable.
- Change the API of function->GetAttr to return Optional<T>

* Address review comments

* Upgrade all compiler flags to c++14

* Update as per review comment

* one weird trick.

* Added schedule knob for different workloads.

* Initial conv3d tensorcore working.

* Added conv3d tensorcore strategy.

* Added layout conversion to tensorcore friendly format for conv2d and conv3d.

* Add target name check.

* Fixed bad names and depthwise check.

* Removed duplicated attribute assignment.

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

* [PYTORCH]Reduce_ops support added

* Review comments updated

* typo bug in qnn test

* use funcs from prelude, pass around convert_map

* get relay input type from user ishape

* handle tuple unpack

* experimenting with static tensor array

* use prelude concat instead of cons + rev

* minor clean up

* fix layer norm conversion bug, unwrap tensor array

* add infer shape on tensor array

* pass around prelude for now

* compile worked but runtime error

* fix tensor array wrapping

* begin list dynamic test

* is_list_dynamic first version

* finish dynamic list test

* a few fix

* use shape_of function if Any is found

* improve size conversion

* working on adding free vars to loop block

* fixed inlined inner loop issue

* clean up free var handling

* add support for tensor array concat

* adding ta concat on last axis

* fix concat, but got runtime error

* disable concat on axis -1 for now

* add lstm tests

* revert unrelated change

* fix stacked bidir test

* minor fix to test

* relax tol a bit, revert dnnl change to avoid conflict

* simplify infer type, use input tensor shape rather than concat shape

* more shape fix

* [Intrinsic] Add log1p, ldexp, atan2, hypot, nextafter, copysign

* Lint

* Adding Cast back to Int32 in FixedPointMultiply.

* Removing extra clip.

* Fix space.

* Retrigger.

* Retrigger.

This PR enables the copy on write optimizations passes:
- Enable COW for IRModule both TIR and relay passes.
- Enabled COW for PrimFunc in TIR passes.

Need more thoughts into whether/how to enable COW
for relay::Function, due to some function passes depend
on the presence of IRModule for context information,
and the std::move of the related function to nullptr
might affect the related behavior.

* [PYTHON]Abs, Arange, Softplus ops

* Review comments updated