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Merge branch 'dynamic_reduce' of https://github.com/ROCmSoftwarePlatform/AMDMIGraphX into dynamic_reduce

Refactored reduce_op::normalize_compute_shape() handling of dynamic shapes to set reduced dimensions to {1,1} instead of removing them.
Updated shape tests for reduce ops.
Spurious change to reduce_mean.cpp reverted.

Merge branch 'dynamic_reduce' of https://github.com/ROCmSoftwarePlatform/AMDMIGraphX into dynamic_reduce

dynamic shape support for reduce_XXX operations.  One test in ref_ops_test; one test in op_shape_test

dynamic shape support for reduce_XXX operations.  One test in ref_ops_test; one test in op_shape_test

Local Threads of multiples 32 were introduced in #1348
But LocalThreads that are not multiple of 64 are causing correctness issues.

Upgraded Dockerfiles and fixed tidy issues to make Ubuntu 20.04 and ROCm 5.3.0 the default 

updated GPU pad to now use JIT version.
added range functions for JIT kernels.

Fixes an observed regression error on certain Frozen Protobuf models due to PR 1280

use_dynamic_same_auto_pad was removed from convolution, but the driver models still retain the fields. This PR regenerates the files so that they are compatible again.

Reiterate the assertion on the standard shape but relax it for the multibroadcast ops deliberately inserted to explicit the broadcast.

Refactor dynamic compute
- add a compute_output_shape object that implicitly converts to a new dyn_output or shape object
- dyn_output object can handle computing the static output shape of an operator given the input arguments shapes
  change an operator's compute function to argument compute(const dyn_output& dyn_out, std::vector<argument> args) to 
  use dyn_output object

Dynamic ref unary functions
-  Included these changes to have an example of the refactored dynamic compute being used
-  Changes to unary base class to handle dynamic shapes
-  Changed elu and leaky_relu to use unary base class and pointwise JIT

Merge branch 'refactor_dynamic_compute' of github.com:ROCmSoftwarePlatform/AMDMIGraphX into refactor_dynamic_compute

* use find2.0 for the convolution
Co-authored-by: Vasilii Filippov <DrizztDoUrden@users.noreply.github.com>
Co-authored-by: Chris Austen <causten@users.noreply.github.com>

* Enable non-standard shape
* Use perfdb for non xdlops
* Fix transpose+broadcast strides
Co-authored-by: jungpark-mlir <jungwook.park@amd.com>

hipMemset is causing random failure.
hipMemsetAsync is doing the correct synchronization.

Allows for rank 2 tensors into batchnorm.  Specifically when spatial dimensions are all 1 and removed

Removes use_dynamic_same_auto_pad
Change padding_mode to be used for dynamic padding
Move compute_padded_shape to pad_calc.cpp as it will be used in other dynamic padding cases
Fix same_lower compute_padded_shape bug and add a test.

Rewrites the TF batch norm like operators to other MIGX operators
Removes the code related to batch_norm_inference

Merge branch 'refactor_auto_pad_conv' of github.com:ROCmSoftwarePlatform/AMDMIGraphX into refactor_dynamic_compute

Simplified algebraic operations (x*1), x*(-1), x/1, 0+x & x+0,  x-0, 0-x, 0*x, x*0, and 0/x operations

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