Merge pull request #27809 from abhishek-gola:softmax_cross_entropy

Added support for SCE and NLL losses #27809

This pull request adds the support for Negative Log-Likelihood loss and Softmax Cross-Entropy loss in new DNN engine.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake

modules/dnn/include/opencv2/dnn/all_layers.hpp

@@ -1311,6 +1311,33 @@ CV__DNN_INLINE_NS_BEGIN
         static Ptr<Resize2Layer> create(const LayerParams& params);
     };
 
+    // Shared reduction enum for DNN loss layers
+    enum LossReduction
+    {
+        LOSS_REDUCTION_NONE = 0,
+        LOSS_REDUCTION_MEAN = 1,
+        LOSS_REDUCTION_SUM = 2
+    };
+
+    class CV_EXPORTS NegativeLogLikelihoodLossLayer : public Layer
+    {
+    public:
+        LossReduction reduction;
+        int ignoreIndex;
+
+        static Ptr<NegativeLogLikelihoodLossLayer> create(const LayerParams& params);
+    };
+
+    class CV_EXPORTS SoftmaxCrossEntropyLossLayer : public Layer
+    {
+    public:
+        static Ptr<SoftmaxCrossEntropyLossLayer> create(const LayerParams& params);
+        LossReduction reduction;
+        int ignoreIndex;
+        float labelSmoothing;
+        bool softLabel;
+    };
+
     /**
      * @brief Bilinear resize layer from https://github.com/cdmh/deeplab-public-ver2
      *