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This resolves an edge case found in multiple huggingface models  in some cases the find_split_reshape matcher will match with reshape2, but vec_rsp will consist of reshape1 dims causing a shape mismatch error. Solution is to include rsp when checking all reshapes are the same.

let the user know which targets migraphx was built for and how to build migraphx for their gpu.

Implements a fill operator that sets the values in an output buffer to a given value
Will be used when parsing ONNX ConstantOfShape
Can also be used when a buffer needs to be filled with a value that is determined at runtime

New op that populates a shape with random numbers with a uniform distribution. The rand_uniform op. can implement the Onnx RandomUniform instruction, and can also create the random number sequence necessary to implement Multinomial. (At this time, our Onnx Multinomial parsing generates a random sequence of numbers when parsing as a workaround, so that the resulting program uses the same "random" set every time.)

Arguments: shape, seed. Shape is required; can be static or dynamic. Seed is still optional in this version. If it's not given at inference time, use the value in the creation attribute seed. Update: deleted A boolean use_auto_seed causes any given seed to be ignored.

Added case to skip test_limits<int,long> while running tests on Windows since int and long have same min and max values

Makes a version of allocate that takes in dimensions and allocates a buffer
Going to create a simplify_dynamic_ops compiler pass that will use the use_shape_attr flag
The ONNX op ConstantOfShape needs the buffer to be filled with a specific value, so going to make another PR for that and a fill operator

Re-organizes ref tests to improve the speed of compilation 

Adds support for dynamic input shape in pooling operator along with auto-padding. This combination requires that the padding (and therefore the output shape) can't be computed until runtime.

Allows slice to work with variable starts, ends, and axes input
Outputs a dynamic shape even with a static shape data input when the starts and ends are variable

This PR constitutes the MIGraphX-side changes needed to not break the build in the presence of
ROCmSoftwarePlatform/rocMLIR#1136 , and updates what data is sent in to MLIR during the kernel generation and tuning process.

* add quant_dot fusion, clip literal opt

* use implicit deps for the sorting
* use BFS for sorting program

* Use shape of Instruction (instead of a default) in add_return()

* Instruction validation fix: not to use a default shape value for comparison

* Fix instruction::replace() to recompute shape for "@return"

* handle the case of missing shape in an Instruction related Test

* use compute_shape() to get op shapes + test case for tuple_type

* add test case shape_test/return_shape_tuple

* Add test for @return to check for half type

* Move @return unit-tests around..; Address review comments

* Broken comparison fix: comparison to a (default) shape of tuple_type

* Test cases: (add) return_shape_empty & (modify) return_shape_tuple

* modify the assert() statement

* Add initial tuning support

* Format

* Add extra param

* Format

* Use exauhstive flag

* Format

* Set expected shapes

* Format

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* Fix missing symbol

* Format

* Add missing license header

* Format

* Update src/targets/gpu/include/migraphx/gpu/mlir.hpp

* Improve performance of pointwise/reduction kernels when using NHWC layouts

* Format

* Add nhwc test

* Format

* Remove inline namespace

* Add reduce test

The --py output can be loaded back in the driver. This will embed the migraphx interperter so we can execute the python directly. There is a migraphx_py library which will dynamically load the version of the library for python version is available on the system.

* rename function 'near' to 'make_near'

* try disabling vega10 machine