GitLab

Updated Multibroadcast op to have a two input version for dynamic shapes
Current dynamic shape broadcasting logic
dynamic_dimensions must be the same or one of them is {1, 1, 0} or {1, 1, 1}
Works for dyn-dyn, dyn-static, and static-static shape combinations
Changed common.cpp for multibroadcasting for binary ops with dynamic shapes
Extended binary.hpp for dynamic shapes to test the new common.cpp stuff

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

Rewrites the BatchNormalization ONNX operator into other MIGX operators
- Added handling of 1D input tensor case (edge case in ONNX spec)
Removes the spatial and per_activation functionality (not in the ONNX spec)
- Did not remove the batch_norm_inference related code as the TensorFlow parser still uses it
- Can remove that code when the TF version is updated

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

* Load op when serializing

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* Add missing clip field

* Use make_op almost everywhere

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* More make ops for rnns

* Get rid of spaces

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* Remove operators headers

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* Remove unused op headers

* Increase line threshold

* Refactor onnx_parser class

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* Add op_parser

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* Remove old onnx drivers

* Use file GLOB

* Parse arg ops

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* Add pooling

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* Add parse_natchnorm

* Add more operators

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* Add more operators

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* Add more operators

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* Add more operators

* Add rnn operators

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* Fix tidy issues

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* Add back missing param

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* Fix shadow variable

* Fix shadow in declaration

* Make global constant

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* Add generic op

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* Add binary op

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* Add variadiac op

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* Remove unused fields and functions

* Set default values

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* Remove unused member variable

* Add add literal overload

* Use info.add_literal

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* Call add_instruction through info class

* Fix tidy issues

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