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* Add is_supported to the target
* Add get_target_assignments
* Rename assignment to target_assignments
* Add ref target header to test
* Add fpga target
* Make context const in compute

Adding this to make sure we're covering this case as well as codecov is flagging this as uncovered.

C++ API is not printing thrown exception string. this improves on it.

Dynamic shape handling in shape object

Doing this allows for things to be university across all our targets without neededing an op for each ref.

TODO. breaks right now. Reusing tests from previous iteration with some tweaks. Need to get back to this once I get better train of thought

Depends on #1199

Adds ONNX parser functionality for dynamic input shapes.
Uses options parameter in parse_onnx()

Conversion works, just issues with predicate right now.

Fix min_test.onnx generation as well as add a proper check to the parse program vs the expect program.
Adding this in to fix test converge for the min case.

This will ensure that migraphx.h can be included from a C compiler, and check that the C API can be called. This includes stdbool.h which is needed when using bool from C.

I may need additional checks for this, or to somehow find the matching division
by zero, and cause a dangling reference so this gets flagged correctly at compile time.
Current attempt inserts a divzero instruction that would later get picked up at the verify stage
during compile. Not sure if this is correct incase we run into operator collisions down the road

This reverts commit fcc84214.

Added is_supported and get_target_assignments methods to the target and program, respectively, to eventually support multi-target compilation and execution.

Initial sketch for changes to shape to handle dynamic dimensions

Instead of just unsqueezing to an axis of 1 a step can be set to use instead. So instead of unsqueezing {3, 12} to {3, 1, 12} a step of 2 will unsqeeze to {3, 2, 6} instead

*In the verification tests, check that saving and reloading the program is the same program. This also fixes serialization to always load instructions in the same order. There is also fixes for deconv and quant_conv which didn't save the solution id, and was broken for serialization.

This reorders the transposes across slice to improve horizontal fusion for contiguous. This also improves eliminate_contiguous to remove contiguous better across splits.

Making things more maintainable by splitting the unit tests that shared the baseline program for validation which resulted in an & case that was a bit more cumbersome to debug.

* Add mlir c api

* Formatting

* Create a type attribute

* Formatting

* Parse module

* Formatting

* 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

* Format

* Remove old cmake flag

* Update message

* Add return

* Format

* Add mlir_compile

* Format

* Register dialect

* Handle unsinged integers

* Dont provide output for return instruction

* Format

* Add code to insert memrefs

* Format

* Add mlir verification

* Formatting

* Enable pointwise_fusion

* Disable eliminate_data_type

* Set kernal name

* Format

* Fix device name

* Formatting

* Fix output arg

* Format

* Updates

* Upate hash

* Add fuse_mlir pass

* Format

* Add fuse mlir

* Format

* Update mlir

* Sort parameter names

* Format

* Reenable disabled passes

* Remove old mlir conv

* Remove asym default padding

* Add more verbose tracing

* Format

* Fix compilation errors

* Format

* Whitelist operators

* Format

* Add namespace

* Format

* Update triple

* Format

* Use func dialect

* Format

* Use func.return

* Format

* Upgrade mlir version

* Add comment

* Handle symetrical padding

* Format

* Cleanup debug output

* Format

* List failed tests

* Move mlir compile to jit pipeline

* Format

* Update version

* Add source locations

* Format

* Correctly add module

* Format

* Update failed tests

* Fix failures when mlir is disabled

* Format

* Update mlir version

* Check type for fp32

* Format

* Remove failed test

* Update mlir in driver

* Tidy fixes

* Foramt

* Tidy fixes

* Format

* Fix const

* Remove from requirements

* Fix cmake version

* Fix tidy warning

* Use another ifdef

* Fix tidy

* Other tidy fix

* Format

* Update hash

* Add missing license files

* Format

* Format

* Fix fnction name

Throw an exception when this occurs to indicate our simpliciation passes resulted in a singularity somewhere. Related to #1236

Simplify addition zero multiplication and divide operations. Added approrpiate test cases with returns and replacing the instruction and operand to just return zero.

Using the unit/neg unit matchers to handle subtraction operations in the same steps. Added unit tests for both cases.

Part of changes that go wtih #1236. Reverts -1 divide operations to a simple negation of the parameter

Added test case and code to simplify zero additions between paremeters and literals during simplifications.  In reference to issue #1236

Done to satisfy simplifications specified by #1236 .  Just replace every  parameter divided by 1 with itself. It's assumed that the eliminate_identity() pass will handle generated identity operators in our run_pass()

Save a multiply operation with that of a negation of  input parameter x. Suggested improvement via #1236

Original use case of having a literal 1, instead of any other number in simplify_mul_add, resulted in the find_unit_mult_const function to optimize away the literal 1 causing this test to fail. on the final check. Switched the constant to a non zero & one value, and now correctly passes.

Commit for the day, work in progress as I'm failing one of our unit tests outside of the change

This is an extension to insert_module_instructions, but instead of just inserting from a module, it can insert a range or a vector of instructions.

Allows PyTorch converted version of SSD-resnet34 to work

* Jit contiguous