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* Update instal_prereqs.sh to handle 22.04 defines

Needed to run containers with 22.04

* Add Dockerfile for Ubuntu 22.04 and ROCm 5.5

Updated dockerfile to use ROCm 5.5 and Ubuntu 22.04 for use with building MIGraphX
Able to run make -j$(nproc) check successfully with this

* Clean this up since its breaking CI

* cleanup install preq some more.

-use one protobuf version
-remove extra python3.8 installs from 3.10 case

* Move comment for protobuf comment

* Move Dockerfile for 22.04 to Dockerfiles/ folder

* Move and rename 2204 docker file

remove Docker_** from the name. Move these to tools/docker

* Add pip3 installs to be shared between python versions

* Add Package pin from repo.radeon.com

* Add CMAKE_ARG ONNX_USE_PROTOBUF_SHARED_LIBS for every default python dist

Set this to be default as part of installing prereqs

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Co-authored-by: Charlie Lin <charlie.lin@amd.com>
Co-authored-by: Umang Yadav <29876643+umangyadav@users.noreply.github.com>
Co-authored-by: kahmed10 <15948690+kahmed10@users.noreply.github.com>

Co-authored-by: kahmed10 <15948690+kahmed10@users.noreply.github.com>

Co-authored-by: kahmed10 <15948690+kahmed10@users.noreply.github.com>

Co-authored-by: causten <causten@users.noreply.github.com>
Co-authored-by: Ted Themistokleous <107195283+TedThemistokleous@users.noreply.github.com>

* Add trace for SIMPLIFY_ALGEBRA matches

* Fix format

* handle review comments from Umang

-int to size_t for trace
-move env arg to top of simplify_algebra.cpp
-handle overload beter for find_matches

* Rename trace_mod param to trace_pass

More representative naming for what this trace flag does

* Add initial ck_gemm code

* Format

* Add additional src files

* Format

* Add include

* Simplify fuse_ck

* Format

* Rename var

* Enable pass

* Update ck version

* Fix include

* Add group stride

* Disable warnings for ck headers

* Format

* Add unpack array

* Add interface to enable tuning

* Format

* Update compile_ops to handle tuning config

* Format

* Add some comments

* Move time_op to migraphx_gpu

* Add banchmarking

* Refactor

* Format

* Add lift class macro

* Use device name

* Format

* Generate configs

* Format

* Pass tuning parameter

* Move data type to is_ck_gemm matcher

* Format

* Add problem_cache to avoid retuning same configs

* Format

* Format

* Mark the problems

* Format

* Use is_null

* Format

* Resize vector

* Only tune with exaustive tuning

* Format

* Use assert

* FOrmat

* Tidy fixes

* More tidy fixes

* Format

* Add license to missing files

* Format

* Use transform

* Format

* Fix tidy

* Format

* Fix cppcheck issues

* Format

* Add static_assert

* Add ops header

* Add assertion in batcher

* Format

* Improve the batch fold check

* Format

* Add where op workaround for CK

* Skip if any input is not a supported ck type

* Format

* Check batch is standard

* Format

* Remove redundant static keyword

* Update commit hash

* Fix error when running without --exhaustive-tune

* Formatting

* Formatting

* Remove fuse_ck_gemm_softmax_gemm

* Update ck hash

* Correct spelling mistake

* Remove commented out logic from fuse_ck

* Remove unused include and add comment

* Formatting

* Remove redundant get_shape and remove ck_gemm from names

* Formatting

* Allow for mixed types with int8 gemms

* Formatting

* Add back find_package from merge

* Update CK commit hash and add gfx940 to fuse_ops supported archs

* Formatting

* Update CK hash

* Fix convert for the NaNs

* NaNs can't be compared, use std::isnan()

* formatting

* formatting

* formatting

* add extra tests

* initial

* Added tests and new functionality

* Update optimals handling

* Simplify conditionals

* Ref test, update docs

* Remove comment, suggestion unclear

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Co-authored-by: Umang Yadav <29876643+umangyadav@users.noreply.github.com>

* fix parse_instancenorm to create broadcast and multibroadcast instructions with two dynamic shape arguments instead of 1.  Their make_op() functions don't support dynamic shapes when called with one input.  This caused an error when parsing an ONNX 3duunet model

* Use add_common_op() to create multibroadcast op.

* add verification and parsing test for instance_norm with dynamic input.  Parse test doesn't pass.

* fix for test; still doesn't pass

* another fix for test; still doesn't pass

* work in progress, instance_norm_dyn_batch_test works but instance_norm_test doesn't

* fix onnx instancenorm tests to match parser changes.  Passes all check tests

* Updated comments explaining usage of add_common_op()

* hand-merged conflicts with develop

* fix instance_norm_half_test after merge

* add Onnx test instance_norm_dyn_batch_half_test

* add shape test cases broadcast_1in_dyn_error and multibroadcast_1in_dyn_error_0

* add fix for the trace_eval

* Add throw for the debug builds

* Formatting

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

#1791 Added hash function for value class. It uses the Visit function and has specialization for the bool_type and <vector> type but was missing specialization for the nullptr. Nullptr caused compilation issues for RHEL, SLES and CentOS.

Enable with MIGRAPHX_ENABLE_CK=1 and --exhaustive-tune tune flag

Sigmoid approximation for GeLU was introduced in #1299 for Fp16. The sigmoid approximation is known to get better perf but lower accuracy. https://arxiv.org/pdf/1606.08415.pdf

Changed the doc for find_permutation(shape) to be more clear that it is finding the permutation that would make the shape standard

By converting to fp32 : fp16 3d-unet model accuracy comes out the same as FP32 accuracy.

By using reduce_sum method on Fp16 : accuracy comes out ~0.9% lower compared to fp32 while keeping entire model in fp16.

partially solves #1656
This PR only handles compilation part of multitarget.

Use generate_argument instead of generate_literal for python output as generate_literal doesnt exists
Shorten the names for variables from the main module
Use prefix p_ for parameters
Use shorter variable m for main module in python

* Allow quantizing for both int8 and fp16

Use std::numeric_limits::min/max() functions plus the appropriate value to encode -inf/inf 

Enable retrieving the code object to do tuning in the future.

Refactor supported gfx archs

back out changes for rocm-5.5

* use half hip functions to compute max and min
* add verify test for min and max