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

update multibroadcast shape tests

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

* 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>

also adding limitations on broadcasting dynamic shapes

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

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

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

convolution revert

* doesn't make much sense to make broadcast use two inputs or handle
dynamic shapes
* compute the common shape for dynamic multibroadcast in the
multibroadcast op
* multibroadcast all combinations of the dynamic inputs

Constructs a dynamic shape from three vectors of lengths,
the minimums, maximums, and optimals

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>