Add GELU layer for vision transformers

* add gelu and gelu approximation

* drop setKernelParams

dnn: add layer normalization for vision transformers

* add layer norm onnx parser, impl and tests

* add onnx graph simplifier for layer norm expanded

* handle the case when constants are of type Initializer

* add test case for layer norm expanded with initializers

* use CV_Assert & CV_CheckType in place of CV_Assert_N; use forward_fallback for OCL_FP16

* use const ref / ref in parameters of invoker::run; extract inner const if from nested loop; use size_t in place of ull

* template hasBias

* remove trailing whitespace

* use pointer parameter with null check; move normSize division & mean_square division outside of loop; use std::max to ensure positive value before std::sqrt

* refactor implementation, optimize parallel_for

* disable layer norm expanded

* remove the removal of layer norm optional outputs

Reimplementation of Element-wise layers with broadcasting support

* init

* semi-working initial version

* add small_vector

* wip

* remove smallvec

* add nary function

* replace auto with Mat in lambda expr used in transform

* uncomment asserts

* autobuffer shape_buf & step_buf

* fix a missing bracket

* fixed a missing addLayer in parseElementWise

* solve one-dimensional broadcast

* remove pre_broadcast_transform for the case of two constants; fix missing constBlobsExtraInfo when addConstant is called

* one autobuffer for step & shape

* temporal fix for the missing original dimension information

* fix parseUnsqueeze when it gets a 1d tensor constant

* support sum/mean/min/max with only one input

* reuse old code to handle cases of two non-constant inputs

* add condition to handle div & mul of two non-constant inputs

* use || instead of or

* remove trainling spaces

* enlarge buf in binary_forward to contain other buffer

* use autobuffer in nary_forward

* generate data randomly and add more cases for perf

* add op and, or & xor

* update perf_dnn

* remove some comments

* remove legacy; add two ONNX conformance tests in filter

* move from cpu_denylist to all_denylist

* adjust parsing for inputs>=2
Co-authored-by: Nfengyuentau <yuantao.feng@opencv.org.cn>

Add acos, acosh, asin, asinh, atan, atanh, cos, cosh, erf, hardswish, sin, sinh, softplus, softsign, tan layers

dnn : int8 quantized layers support in onnx importer

* added quantized layers support in onnx importer

* added more cases in eltwise node, some more checks

* added tests for quantized nodes

* relax thresholds for failed tests, address review comments

* refactoring based on review comments

* added support for unsupported cases and pre-quantized resnet50 test

* relax thresholds due to int8 resize layer

* Support cumsum layer for onnx

* Add unit tests

* Address review comments

* Add initialization and inference for GRU layer

* fix issues found on review

backport of commit: 61119358
partial backport of commit: dd597616

Support FlowNet2 model

* Support DataAugmentation layer

* Fix warnings

* Fix comments

* Support Correlation layer

* TEST

* Support Correlation layer

* Supported Accum and FlowWarp layers

* Supported ChannelNorm layer

* Supported Resample with inputs.size() > 1

* Fixed comments

* Refactoring

* Added tests

* Add resample test

* Added asserts in resize layer

* Updated DataAugmentation layer

* Update convolution layer

* Refactoring

* Fix data augmentation layer

* Fix caffe importer

* Fix resize

* Switch to Mat ptr

* Remove useless resize type

* Used ResizeLayer in Accum

* Split ChannelNormLayer

* Delete duplicate assert

* Add sample

* Fix sample

* Added colormap

* Added Swish and Mish activations

* Fixed whitespace errors

* Kernel implementation done

* Added function for launching kernel

* Changed type of 1.0

* Attempt to add test for Swish and Mish

* Resolving type mismatch for log

* exp from device

* Use log1pexp instead of adding 1

* Added openCL kernels

- differ from 3.4 branch

* Added ResizeBilinear op for tf

Combined ResizeNearestNeighbor and ResizeBilinear layers into Resize (with an interpolation param).

Minor changes to tf_importer and resize layer to save some code lines

Minor changes in init.cpp

Minor changes in tf_importer.cpp

* Replaced implementation of a custom ResizeBilinear layer to all layers

* Use Mat::ptr. Replace interpolation flags