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instancenorm parser always creates literal of type float which would fail in type check while creating binary ops if model is fp16.

* Add in changes for onnx Mod operator

Initial operator for mod implementation and test cases for integer and floating based types.

Need to use fmod from stdlib for floating point types. half_float::half thankfully is specced to the use the existing std::fmod() call when looking at the half.hpp implementation.

fmod_flag should mirror the onnx fmod attribute. Right now using a floating point type without setting that on the user side to true will result in an exception.

Ref ticket #1283 

Fix min_test.onnx generation as well as add a proper check to the parse program vs the expect program.
Adding this in to fix test converge for the min case.

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

As described in #1196, the ONNX mean parser does not work correctly for integral types. This update fixes the issue by handling integral types separately, where summation is performed before division. Additional test cases have also been added for handling integral types.

Add ref and gpu implementations for ONNX op GatherND

Resolves #1032

Implements the ReverseSequence ONNX operator as a parser.

This parser can only handle a constant sequence_lens input. This is the same as what is handled for TensorRT as far as I can tell.
We could handle a variable sequence_lens input; that would require ref and GPU implementations of the operator.
The ONNX backend tests are disabled because this does not handle variable sequence_lens.

Refactored the reference implementation of pooling to something like what was done for roialign. Moved the reference implementation of pooling from targets/ref/lowering.cpp to pooling.hpp.
Removed cpu_pooling, instead using reference pooling in pooling.hpp
Added reference implementation of Lp Norm pooling and the global version
Added tests for the Lp Norm Pooling

Change the "scatter" struct and op to a base/child set of three: scatter_none, scatter_add, scatter_mul to mirror Onnx' ScatterElements op. and its three reduction options. (Onnx Scatter op is deprecated and is equivalent to scatter_none.)

Provides both a reference op. and update to Onnx parsing. Tests updated and new test case added.

* LpNormalization ONNX parser

Add Celu ONNX operator

* Implement size ONNX operator and tests

add_common_op for parse_clip
Should fix #1119

Adds EyeLike ONNX parser and unit tests.

Add onnx parser and ref and gpu implementations of ONNX op ScatterND

Implements the IsNaN operator, ref, gpu, and onnx parser.

* use the parse_resize to parse the upsample operator

* Add mean op onnx parser and unit tests
* Refactor parse_mean to use add_broadcastable_binary_op

Add HardSwish to HardSigmoid parser

HardSwish formula is y = x * HardSigmoid<alpha=1/6, beta=0.5>(x)
HardSigmoid parser sets alpha to 1/6 and adds the mul instruction if op name is HardSwish

Resolves #1062

Add onnx parser for operator GreaterOrEqual

Add onnx parser and unit tests for Softsign

* Add onnx parser and unit test

Add HardSigmoid onnx parser and unit tests
Produces mathematical equivalent to ONNX operator through combination of existing pointwise ops.
Resolves #1028

Fix bug caused by casting time seed to float

This PR is the ref implementation of the nonmaxsuppression operator. It always returns the max possible output shape, which is the problem tracked in issue #948.

Implementation of the roialign operator. For now, we have only the ref implementation. When we run a model on the GPU, we fall back the execution to use the ref implementation.

Inverse of DepthToSpace op
Co-authored-by: Shucai Xiao <shucai@gmail.com>

This PR is for the nonzero operator with static output shape.  
Co-authored-by: Paul Fultz II <pfultz2@yahoo.com>
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

Add multinomial op to onnx parser with ref and GPU implementations.

The onnx parser inserts a literal of shape {batch_size, sample_size} with random values in the range [0, 1) and inserts existing ops to compute the cumulative density function. The multinomial operator multiplies the random values by the sum of the CDF and returns the index of the first element of the CDF that is greater than the result, representing samples randomly drawn from [0, class_size) that follow the log-probability distribution.

Resolves #821
Co-authored-by: Shucai Xiao <shucai@gmail.com>