- Remove operator bool from base object ref macro
  - Raitionale: operator bool can be dangerous for sub-classes
    that also overloads other operators(e.g. ==).
  - If bool is still needed, use explicit operator bool.
- Use absolute include when necessary
- Move type related util to data_type
- Isolate stackvm code from compiler

* [Docs] Convert Layout pass.

* Address comments. Section 3 massaging.

* Address comments.

* [REFACTOR] introduce top - Tensor Operation DSL.

Historically we put Tensor, Schedule and compute under the root tvm namespace.
This is no longer a good idea as the project's scope grows larger
than the tensor operation DSL.

This PR introduces top -- a namespace for tensor operational
DSL concepts such as schedule, tensor, compute.
We moved the related files to the new top subfolder.

* Move relevant files into include/tvm/top and src/top

* BYOC tutorial: codegen C

* Address comments

* Address comments

* Add build option

* Address comments

* Use TVM_DLL_EXPORT_TYPED_FUNC

Spread the arithmetic.h into several components and move
into arith subfolder.

The arith namespace will be used for arithmetic expression
pattern detections and simplifications.

* [Relay][Frontend][TFLite] Add parser support for squared difference

* fix some error

* fix exp_type

* add comment

* [arith] add ShapeVar representing non-neg valued variable in a tensor shape

* bounder remover; deal with div in int_set differently

* fix bounder_remover

* migrate unittest to use shape_var

* use tvm.shape_var in integration & relay tests

* add test case; fix Var register

* fix lint

* fix lint again

* add default ShapeVar visitor in Relay

* fix override

* fix ShapeVar visit bug

* revert IntervalSet for shape_var

* remove bound_remover

* remove is_var; use constructor for shapevar/var instead

* ShapeVar -> SizeVar; add constructor comments

* shape_var -> size_var in doc

* tindex -> size

As part of Unified IR infra.
Introduce target folder to store all the compilation target related information.

This PR introduces more clear naming prefix for C API type codes
to avoid conflict with other packages.

We also removed TVMArray and TVMType to directly use DLTensor and DLDataType.

* [REFACTOR] Move support related code to include/tvm/support

- tvm/logging.h -> tvm/support/logging.h
- remove tvm/base.h, move with into tvm/support/with.h

* src/common -> src/support

This PR moves attrs.h into the ir folder as it
can serve as a common infra for building ir dats structures.

We also moved common container(FloatImm) into ir/expr.h

* [Relay][Frontend][TFLite] Add constant input support for elemwise ops

* modify in tflite.py

This reverts commit dcf7fbf1.

* [REFACTOR][IR] Unify IntImm and UIntImm

This PR unifies UIntImm and IntImm to simplify the codebase.
Unsigned integer constants will also be stored as IntImm.

For uint constant that does not fit into int64(rare case), we introduced
an intrinsic tvm_big_uint_imm to construct such intgers by its
lower and higher 32bits.

* [REFACTOR][IR] Remove UIntImm to use IntImm

* rename big->large

- Use consistent constructor style to construct objects.
- Move env_func to ir as it is mainly used to construct IRs.
- Make docs consistent.

* [relay] Relay annotation and partitioning for codegen

* Add fusion unit test

* fix comments

* Update include/tvm/relay/attrs/annotation.h

Co-Authored-By: 雾雨魔理沙 <lolisa@marisa.moe>

* rebase

* remove annotation helper

* rebase again

Co-authored-by: Cody Yu <comaniac0422@gmail.com>
Co-authored-by: 雾雨魔理沙 <lolisa@marisa.moe>

Move the relay's pass Infra to ir.
Keep FunctionPass in relay as it is local to the dialect.

We will use a single ErrorReporter to report errors during
program transformations.

This PR brings relay::Module as the unified IRModule structure.
IRModule will be used as the basic unit for transformations
through out the stack.

- Rename relay::Module -> IRModule
- Move relay/module.h -> ir/module.h
- ModuleNode::FromExpr -> IRModule::FromExpr
- FromText -> IRModule::FromText

* GitHub Action lint Python code for syntax errors

https://flake8.pycqa.org/en/latest/user/error-codes.html

On the flake8 test selection, this PR does _not_ focus on "_style violations_" (the majority of flake8 error codes that [__psf/black__](https://github.com/psf/black) can autocorrect).  Instead these tests are focus on runtime safety and correctness:
* E9 tests are about Python syntax errors usually raised because flake8 can not build an Abstract Syntax Tree (AST).  Often these issues are a sign of unused code or code that has not been ported to Python 3.  These would be compile-time errors in a compiled language but in a dynamic language like Python they result in the script halting/crashing on the user.
* F63 tests are usually about the confusion between identity and equality in Python.  Use ==/!= to compare str, bytes, and int literals is the classic case.  These are areas where __a == b__ is True but __a is b__ is False (or vice versa).  Python >= 3.8 will raise SyntaxWarnings on these instances.
* F7 tests logic errors and syntax errors in type hints
* F82 tests are almost always _undefined names_ which are usually a sign of a typo, missing imports, or code that has not been ported to Python 3.  These also would be compile-time errors in a compiled language but in Python a __NameError__ is raised which will halt/crash the script on the user.

* Force a retest

* Rename start_rpc_server_to_tracker.py to start_rpc_server_to_tracker.sh

This is a bash file, not a Python file.

* added conv1d operators to topi.

* Started to add python testing.

* Added python conv1d implementation for testing.

* Wrote test but need to add cuda schedule :(

* Cuda schedules working for both conv1d layouts.

* All topi tests passing.

* Formatting topi.

* Removed pad_method option as its probably overkill.

* Added relay op definition of conv1d.

* End2end conv1d working with onnx.

* Lint fixes.

* Formatting fixes.

* Rebase fix.

* Switched to array based attributes for consistency across convs.

* Improved onnx parsing and testing for convolutions.

* lint fix

* Tiny tweak.

* Bug fix

* Rebase fix.

* Add group ignore to onnx conv1d frontend.

* Unified MakeConv and fixed documentation.

* improved autopadding

* Addressed feedback and simplified onnx frontend.

* Format fix.

* Basic X86 NCW schedule working.

* Added nwc schedule.

* fixed name

* Added more tests and basic x86 schedules.

* Format fix.

* Added non power of two shape tests.

This PR migrates relay's Op into the ir folder.
Op and its registry provides an useful mechanism to
store any attribute meta-data of an operator include
function signatures, lowering rules, side effect etc.

These features are not only useful for Relay, but also needed in the low-level IR.
At the current moment, intrinsic functions in the low-level IR are simply
represented by a string. This means we cannot type-check the low-level IR
when the type does not meet the constraint, nor can we obtain further
information such as side-effect and read write relation of these intrinsics
wrt to arguments.

Op will be used as the way to handle primitive ops(in DL terminology)
(builtin intrinsics or in compiler terminology).
We will perform follow-up refactors to make low-level CallNode
take Op as the function argument.

* [Tutorial] Deploy Quantized Model on CUDA

* update

* update

* address comments

This is a shell file, not a Python file.

Under the unified IR. We will allow a single IRModule
to store different function variants, such as relay::Function,
ExternFunc, and low-level function.

This PR changes relay::Function -> BaseFunc in the module file
to support multiple function variants.

Identity is not the same thing as equality in Python so use ==/!= to compare str, bytes, and int literals. In Python >= 3.8, these instances will raise __SyntaxWarnings__ so it is best to fix them now. https://docs.python.org/3.8/whatsnew/3.8.html#porting-to-python-3-8

% __python__
```
>>> dtype = "float"
>>> dtype += "16"
>>> dtype == "float16"
True
>>> dtype is "float16"
False
>>> 0 == 0.0
True
>>> 0 is 0.0
False
```

#4682 Tried to fix a Python syntax error but did not go far enough because there are _three sets_ of embedded quotes.
This PR solves the syntax error by using Python's triple quoted strings on the outside and then double quotes in the middle and then single quotes on the inside.

* [TOPI][RELAY][OP] add op crop_and_resize

* fix pylint

* incorporate comments

* fix ci

This PR moves a few base types from relay and low-level Expr into the ir sub-folder.
These classes will serve as a common type system across the stack.

Rationale:

- PrimExpr for low-level expressions
- RelayExpr for advanced features, including Function definition.
- Introduce BaseFunc to host all functions, including future PrimFunc(low-level expr functions, subject to discussion).

This is a minimum change we can do to unify the classes into a common hierarchy.
The main data structure that are variant specific will still be kept in the sub-namespaces.
We only include classes that is needed to allow a common Module class.
- BaseFunc
- GlobalVar
- Type definition part of ADT

We will only need the BaseFunc and their checked_type to decide the calling convention
across the function variants.

* replace TensorObj and TensorValue with NDArray

* NodeBase to Object in Python

* rebase