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Makes the optimals into a std::set<std::size_t>
Changes shape object functions to handle the opts change
Changes to convolution, flatten, pooling, and convolution in that they no longer calculate the output optimal dimensions. Instead returns empty opts. Will need to change this in the future if we want to support dynamic shapes fully.
Many changes to tests and shape calls with respect to the new optimals

Adds the promote_literals compiler pass that moves literals from the submodules to the main module.
With the eliminate_common_subexpression pass, it will remove copies of literals created during split_single_dyn_dim.
Pass is enabled with the split_single_dyn_dim compile option.

Adds a new GPU compiler pass split_single_dyn_dim that handles when one input parameter has a single non-fixed dynamic_dimension.
commonly occurs for dynamic batch or BERT sequence length
Splits the dynamic shape into several submodules will static input parameters to handle all of the cases in the dynamic_dimension range.
Essentially does what I manually did for the select_module verify tests
Adds a compile option split_single_dyn_dim that toggles the pass on/off. Defaults to false.
Updates verify_program.hpp and run_verify.cpp to allow for the tests to change the compile_options

* Add hiprtc driver

* Remove version from check_context and bump program version

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

Co-authored-by: Chris Austen <causten@users.noreply.github.com>

prevent dynamically loading the target library that is not compiled with the same version of MIGraphX core lib.

Refactor to have select_module use output parameters
Disable select_module verify tests on cpu

Recent changes #1608 removed migraphx_all_target lib from driver and that led to missing compile time definitions.
Missing compile definitions led to change of default target in driver.

Fixes #1595

This is the original testcase that sparked the error with missing proper const
folding. Pushing changes up to this branch and closing out the PR #1622

* [MLIR] Adds a runtime switch to trigger MLIR

fallback to msgpack for older msgpack versions

* NMS improvements

resolve half info messages while building 

Add additional documentation to explain the passes.

Creates the select_module operator that selects one of the submodules passed to it to run based on the submodule parameters.  The submodule is selected by having the exact same static shapes for the arguments to select_module as the parameters in the submodule

Avoids double global loads.  Strided loops are unrolled which lets store results in array which compiler will use registers for since the index access is constant.   Updated to handle large reductions so which results with a better stable diffusion result

* deprecate HCC

* Add driver flag "--exhaustive-tune" to enable tuning, add support for the same in C/C++ and python API

Add dynamic shape support to slice operator.

First draft of this feature doesn't support ops slicing non-fixed, dynamic axes. Resulting shape in such cases is not guaranteed.* Also, onnx parsing doesn't support any arguments other than "axes".

Currently, we default to device 0 when loading programs. Updating this to use hipGetDevice to set the device for the loaded program.

Expands on the documentation and corrects default option documentation error.

* Add serialization of tuples and optional types

Using add_instruction for the neg op was causing issues on replace_instruction. Changed to use insert_instruction.  Tests and added a new one that is failing without the change.

* add dynamic shape support to concat operator.  Includes new op_shape_test and ref_ops_test cases

dyn shape support for Where operator.  Includes shape test, ref_ops test, onx_test. 

* Fuse layernorm with different patterns
* Only match when using the last axis
Co-authored-by: kahmed10 <15948690+kahmed10@users.noreply.github.com>
Co-authored-by: kahmed10 <15948690+kahmed10@users.noreply.github.com>

Refactors memory coloring to only handle allocation instructions. It also handles allocations for tuple shapes.

* Implement dynamic shapes for scatterND operators.

Dynamic shape support for gathernd op.