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4d918ba40b
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 |
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| .. | ||
| perf_caffe.cpp | ||
| perf_common.cpp | ||
| perf_convolution.cpp | ||
| perf_convolution1d.cpp | ||
| perf_convolution3d.cpp | ||
| perf_layer.cpp | ||
| perf_main.cpp | ||
| perf_net.cpp | ||
| perf_precomp.hpp | ||
| perf_recurrent.cpp | ||