it fuse ocl kernels to reduce kernel enqueue
Signed-off-by: Li Peng <peng.li@intel.com>

Signed-off-by: Li Peng <peng.li@intel.com>

Signed-off-by: Li Peng <peng.li@intel.com>

cut one ocl kernel if normVariance is disabled,
also use native_powr for performance reason.
Signed-off-by: Li Peng <peng.li@intel.com>

Signed-off-by: Li Peng <peng.li@intel.com>

Add layer forward interface with InputArrayOfArrays and
OutputArrayOfArrays parameters, it allows UMat buffer to be
processed and transferred in the layers.
Signed-off-by: Li Peng <peng.li@intel.com>

* another round of dnn optimization:
* increased malloc alignment across OpenCV from 16 to 64 bytes to make it AVX2 and even AVX-512 friendly
* improved SIMD optimization of pooling layer, optimized average pooling
* cleaned up convolution layer implementation
* made activation layer "attacheable" to all other layers, including fully connected and addition layer.
* fixed bug in the fusion algorithm: "LayerData::consumers" should not be cleared, because it desctibes the topology.
* greatly optimized permutation layer, which improved SSD performance
* parallelized element-wise binary/ternary/... ops (sum, prod, max)

* also, added missing copyrights to many of the layer implementation files

* temporarily disabled (again) the check for intermediate blobs consistency; fixed warnings from various builders

https://github.com/opencv/opencv_contrib/tree/e6f63c7a38ca40c5dc33e38736e3027e3528d6cb/modules/dnn

Made all STL usages explicit to be able automatically find all usages of
particular class or function.