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Allows slice to work with variable starts, ends, and axes input
Outputs a dynamic shape even with a static shape data input when the starts and ends are variable

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

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".

Using not and or improves readability. The cppcheck rule will help ensure we are doing it consistently.

Reduce header inclusion in op headers

Updated each source file in the repo with the existing license.

* Normalize compute functions

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* Save normalization flag to the file

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* Remove tuned functions

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* Use in_index
Co-authored-by: Shucai Xiao <shucai@gmail.com>
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

* add a pass to normalize ops

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* add unit tests

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* code backup

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* code backup

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* add support for slice in the normalize_op function

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* add operation method api for whether we need to call normalize_op

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* fix review comments

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* rename a function namejJ

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* change compute_shape to normalize_compute_shape for corresponding operators

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* remove unnecessary code

* fix various issues

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* add attributes to operators having axis attributes

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* fixed jenkins build error

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* fix a bug related to slice

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* code backup

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* code backup

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* rename a file

* fix cppcheck error

* some code refinement

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* change attributes to enum

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* refine the enum

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* remove unnecessary code

* add unit tests for more code coverage and fixed a bug

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* remove unnecessary changes

* change normalize_axes to normalize

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* revert back the changes in broadcast.hpp

* rename normalize_axes to normalize

* fix review comments

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* Add flag to enable cpu backend

* Make buffers shared

* Enable optimizations

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* Try to avoid ambiguous assign in value class

* fixed a build error

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* add the normalize_ops pass to the ref target

* refactor program to module to normalize_ops pass
Co-authored-by: Paul <pfultz2@yahoo.com>
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

* Register ops for main migraphx

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* Register cpu ops

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* Show list of operators in the driver

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* Simplify regiter

* Try to register gpu ops

* Fix compiler errors

* Register rest of the gpu operators

* Add some tests

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* Fix gcc compiler warnings

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* Fix tidy warnings

* Fix compile error

* Use correct op name

* Register layer norm

* Use const ref

* Make run const

* refine slice implementation

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* fix cppcheck error

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* fix a bug in parsing slice

* add unit tests for slice operator

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* fix cppcheck error

* add the numpy package in the Dockerfile

* add missing onnx file

* fix cppcheck error

* fix cppcheck error

* add one more unit test related to slice and split

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Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>