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Added dynamic input handling to multinomial.hpp.  Tests don't pass because it still requires both a random uniform, and dynamic-friendly prefix_scap operations to accept dynamic inputs

Needed to run multi-targeted program where "main" isn't the only root module. There could be many root modules other than main.

Updates ref version of clip to work with dynamic shapes
Encountered in agentmodel

Fixes #1852  Fixes #1847

* 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

* 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

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

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

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

Move CI to support the rocm5.5 release

Adding support for broadcasted scalars to unsqueeze op.

Specifying steps other than 1 is disallowed in this implementation since we want the output the always be a tensor. We can support varying step sizes if we allow a broadcasted scalar output from this op.

add option to print tf supported ops
sort both onnx and tf ops alphabetically

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

Updates the hip::copy_to_gpu and hip::copy_from_gpu operators to work with dynamic shapes

Allows for offload_copy to be used with dynamic batch

Changed assert in select_module because the argument might now be smaller with how offload_copy will work with dynamic batch. (maximum buffer size will be used)

This fixes #1700

Solves #1311

Ensure that we don't have empty inputs when computing shape for pointwise function

Adds a matcher to split_single_dyn_dim to find all broadcast or multibroadcast with two static shape inputs and replaces the instruction with the one input version.
Sorts the get_output_parameters() list to ensure the correct ordering. (Was getting an error for some models.)

Converts can be inserted when the scales and input differ in the onnx file(we are already doing this implicit conversion in the ref implementation). This will also improve the compile-time of quantizelinear.hpp since we can remove the nested visit method.

Examples..

bin/driver verify /codes/onnx_models/resnet50-v1-7/resnet50-v1-7.onnx --split-single-dyn-dim --batch 3 --dyn-input-dim @data "[{min:1, max:4}, 3, 224, 224]"

bin/driver compile /codes/onnx_models/resnet50-v1-7/resnet50-v1-7.onnx --split-single-dyn-dim --default-dyn-dim "{min:1, max:10}" --output resnet50_batch1-10.mxr

bin/driver perf resnet50_batch1-10.mxr --batch 4

Automatically fuse multiple reductions and pointwise operations.

* Add MIGRAPHX_VALIDATE_MATCHES env variable to validate each matcher