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This will enable MLIR by default for these cases:

Any convolution fusion
Any int8 gemm fusion
All Navi3 standalone convolutions
With a flag(ie MIGRAPHX_ENABLE_MLIR) to enable MLIR for floating-point gemm fusions
Except:

3x3 winnograd convolutions fusions (except on Navi)
K > 2048 on gemm (as CK)
Also there is MIGRAPHX_DISABLE_MLIR to disable MLIR completely.

Currently, we see MLIR partition candidates recieving non-standard shape due to not fusing in squeeze, flatten and unsqueeze ops. These ops could be canonicalized to reshape without introducing additional ops as long as MLIR backend is concerned.

Currently, the is_mlir_conv predicate wasn't being used when
offloading standalone convolutions to MLIR on Navi3x, which caused
failures relating to being unable to construct the MLIR program when a
3D convlolution was passed in.

This commit amends the standalone lowering to use said predicate, as
well as to include quant_convolution and quant_dot into the set of
operations that get a standalone lowering.

In addition, since the bug in the sigmoid test is resolved, also uncomment that temporary disable.

Bump MLIR commit to include latest supported pointwise ops.
Expand the MLIR approve list 
Ensure that operations such as tanh() that don't have integer implementations (at least in MLIR) aren't used within MLIR modules.
Add additional tests.

Add mlir quant_dot operator support

Adds support for slice,transpose,contigous and reshape fusions into input tensors for a fused mlir kernel.

Exposed the mlir_enabled() call the decide for lowering pipeline's enablement
Disabled the rewrite quantization pipeline in mlir compilation
Added quant convolution as anchor ops
Fixed the return type expectations
Added the fall back hip implementation for quantizelinear and dequantizelinear
Will need advises to improve the implementation for quantizelinear

* [MLIR] add dot offloads with manual tuning support
* This commit adds dot + pointwise fusion support
along with manual tuning using rocMLIR.

* [MLIR] Adds a runtime switch to trigger MLIR

* Enable non-standard shape
* Use perfdb for non xdlops
* Fix transpose+broadcast strides
Co-authored-by: jungpark-mlir <jungwook.park@amd.com>

Compute mean and variance in same reduction
Set block size to numbers divisible by 32 instead powers of 2
Global is also set exactly instead of being divisible by block size
More exact matching of global/local can help get rid of branching/loops
Reduce vectors first before doing dpp_reduce
Explicitly vectorize array operators since the compiler doesnt always vectorize them
Still uses old for loop when its computing at compile-time since the reinterpret_cast nor the all the vector types is supported

* Add mlir c api

* Formatting

* Create a type attribute

* Formatting

* Parse module

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* Add mlir dump function

* Add test case

* Formatting

* Fix tidy issues

* Update mlit version

* Update to newer mlir

* Format

* Move mlir to the gpu and update the test

* Formatting

* Fix bug when appending module

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* Remove old cmake flag

* Update message

* Add return

* Format

* Add mlir_compile

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* Register dialect

* Handle unsinged integers

* Dont provide output for return instruction

* Format

* Add code to insert memrefs

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* Add mlir verification

* Formatting

* Enable pointwise_fusion

* Disable eliminate_data_type

* Set kernal name

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* Fix device name

* Formatting

* Fix output arg

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* Updates

* Upate hash

* Add fuse_mlir pass

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* Add fuse mlir

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* Update mlir

* Sort parameter names

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* Reenable disabled passes

* Remove old mlir conv

* Remove asym default padding

* Add more verbose tracing

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* Fix compilation errors

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* Whitelist operators

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* Add namespace

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* Update triple

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* Use func dialect

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* Use func.return

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* Upgrade mlir version

* Add comment

* Handle symetrical padding

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* Cleanup debug output

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* List failed tests

* Move mlir compile to jit pipeline

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* Update version

* Add source locations

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* Correctly add module

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* Update failed tests

* Fix failures when mlir is disabled

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* Update mlir version

* Check type for fp32

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* Remove failed test

* Update mlir in driver

* Tidy fixes

* Foramt

* Tidy fixes

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* Fix const

* Remove from requirements

* Fix cmake version

* Fix tidy warning

* Use another ifdef

* Fix tidy

* Other tidy fix

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* Update hash

* Add missing license files

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* Fix fnction name