Merge pull request #24613 from WanliZhong:softmax_default_axis

WanliZhong · web-flow · commit 6ae1709c6a16 · 2023-12-15T10:41:42.000+03:00
Make default axis of softmax in onnx "-1" without opset option #24613 Try to solve problem: #24476 (comment) **ONNX** `opset <= 11` use 1 `else` use -1 **TensorFlow** `TF version = 2.x` use -1 `else` use 1 **Darknet, Caffe, Torch** use 1 by definition
diff --git a/modules/dnn/src/caffe/caffe_importer.cpp b/modules/dnn/src/caffe/caffe_importer.cpp
@@ -499,6 +499,11 @@ class CaffeImporter
             {
                 type = "Convolution";
             }
+            else if (type == "Softmax"){
+                // set default axis to 1
+                if(!layerParams.has("axis"))
+                    layerParams.set("axis", 1);
+            }
 
             int id = dstNet.addLayer(name, type, layerParams);
 
diff --git a/modules/dnn/src/darknet/darknet_io.cpp b/modules/dnn/src/darknet/darknet_io.cpp
@@ -314,6 +314,9 @@ namespace cv {
                     cv::dnn::LayerParams softmax_param;
                     softmax_param.name = "Softmax-name";
                     softmax_param.type = "Softmax";
+                    // set default axis to 1
+                    if(!softmax_param.has("axis"))
+                        softmax_param.set("axis", 1);
                     darknet::LayerParameter lp;
 
                     std::string layer_name = cv::format("softmax_%d", layer_id);
diff --git a/modules/dnn/src/layers/softmax_layer.cpp b/modules/dnn/src/layers/softmax_layer.cpp
@@ -76,7 +76,7 @@ class SoftMaxLayerImpl CV_FINAL : public SoftmaxLayer
 
     SoftMaxLayerImpl(const LayerParams& params)
     {
-        axisRaw = params.get<int>("axis", 1);
+        axisRaw = params.get<int>("axis", -1);
         logSoftMax = params.get<bool>("log_softmax", false);
         setParamsFrom(params);
     }
diff --git a/modules/dnn/src/onnx/onnx_importer.cpp b/modules/dnn/src/onnx/onnx_importer.cpp
@@ -2788,10 +2788,10 @@ void ONNXImporter::parseSoftMax(LayerParams& layerParams, const opencv_onnx::Nod
 {
     const std::string& layer_type = node_proto.op_type();
     int axis;
-    if (layerParams.has("opset") && layerParams.get<int>("opset") > 11) {
-        axis = layerParams.get<int>("axis", -1);
-    } else {
+    if (onnx_opset != 0 && onnx_opset <= 11) {
         axis = layerParams.get<int>("axis", 1);
+    } else {
+        axis = layerParams.get<int>("axis", -1);
     }
     layerParams.set<int>("axis", axis);
     layerParams.type = "Softmax";
@@ -3962,7 +3962,7 @@ void ONNXImporter::buildDispatchMap_ONNX_AI(int opset_version)
     dispatch["Concat"] = &ONNXImporter::parseConcat;
     dispatch["Resize"] = &ONNXImporter::parseResize;
     dispatch["Upsample"] = &ONNXImporter::parseUpsample;
-    dispatch["SoftMax"] = dispatch["LogSoftmax"] = &ONNXImporter::parseSoftMax;
+    dispatch["SoftMax"] = dispatch["Softmax"] = dispatch["LogSoftmax"] = &ONNXImporter::parseSoftMax;
     dispatch["DetectionOutput"] = &ONNXImporter::parseDetectionOutput;
     dispatch["CumSum"] = &ONNXImporter::parseCumSum;
     dispatch["SpaceToDepth"] = dispatch["DepthToSpace"] = &ONNXImporter::parseDepthToSpace;
@@ -3981,7 +3981,7 @@ void ONNXImporter::buildDispatchMap_ONNX_AI(int opset_version)
 
     std::vector<std::string> simpleLayers{"Acos", "Acosh", "Asin", "Asinh", "Atan", "Atanh", "Ceil", "Celu", "Cos",
                                           "Cosh", "Dropout", "Erf", "Exp", "Floor", "HardSigmoid", "HardSwish",
-                                          "Identity", "Log", "Round", "Reciprocal", "Selu", "Sign", "Sigmoid", "Sin", "Sinh", "Softmax",
+                                          "Identity", "Log", "Round", "Reciprocal", "Selu", "Sign", "Sigmoid", "Sin", "Sinh",
                                           "Softplus", "Softsign", "Shrink", "Sqrt", "Tan", "ThresholdedRelu", "Gelu",
                                           "GeluApproximation"};
     for (const auto& name : simpleLayers)
diff --git a/modules/dnn/src/tensorflow/tf_importer.cpp b/modules/dnn/src/tensorflow/tf_importer.cpp
@@ -2300,6 +2300,12 @@ void TFImporter::parseSoftmax(tensorflow::GraphDef& net, const tensorflow::NodeD
     CV_CheckGT(num_inputs, 0, "");
     if (hasLayerAttr(layer, "axis"))
         layerParams.set("axis", getLayerAttr(layer, "axis").i());
+    // if tf version is 2.x, use axis -1 as default
+    else if(netBin.has_versions() && (int)netBin.versions().producer() >= 2)
+        layerParams.set("axis", -1);
+    // else use axis 1 as default
+    else
+        layerParams.set("axis", 1);
 
     int id = dstNet.addLayer(name, "Softmax", layerParams);
     layer_id[name] = id;
diff --git a/modules/dnn/src/torch/torch_importer.cpp b/modules/dnn/src/torch/torch_importer.cpp
@@ -874,6 +874,9 @@ struct TorchImporter
             {
                 newModule->apiType = "Softmax";
                 layerParams.set("log_softmax", nnName == "LogSoftMax");
+                // set default axis to 1
+                if(!layerParams.has("axis"))
+                    layerParams.set("axis", 1);
                 curModule->modules.push_back(newModule);
             }
             else if (nnName == "SpatialCrossMapLRN")
diff --git a/modules/dnn/test/test_onnx_conformance_layer_filter_opencv_all_denylist.inl.hpp b/modules/dnn/test/test_onnx_conformance_layer_filter_opencv_all_denylist.inl.hpp
@@ -43,15 +43,13 @@
 "test_castlike_STRING_to_FLOAT_expanded",
 "test_concat_1d_axis_negative_1",
 "test_div_uint8",  // output type mismatch
-"test_logsoftmax_default_axis",
 "test_maxpool_2d_dilations",
 "test_maxpool_2d_same_lower",
 "test_maxpool_2d_uint8",  // output type mismatch
 "test_maxpool_with_argmax_2d_precomputed_pads",
 "test_maxpool_with_argmax_2d_precomputed_strides",
 "test_maxunpool_export_with_output_shape",  // exception during net.forward() call
 "test_mul_uint8",  // output type mismatch
-"test_softmax_default_axis",
 "test_sub_bcast",
 "test_sub_uint8",  // output type mismatch
 "test_upsample_nearest",

Original file line number	Diff line number	Diff line change
`@@ -499,6 +499,11 @@ class CaffeImporter`
`499`	`499`	`{`
`500`	`500`	`type = "Convolution";`
`501`	`501`	`}`
	`502`	`+ else if (type == "Softmax"){`
	`503`	`+ // set default axis to 1`
	`504`	`+ if(!layerParams.has("axis"))`
	`505`	`+ layerParams.set("axis", 1);`
	`506`	`+ }`
`502`	`507`
`503`	`508`	`int id = dstNet.addLayer(name, type, layerParams);`
`504`	`509`
Original file line number	Diff line number	Diff line change
`@@ -76,7 +76,7 @@ class SoftMaxLayerImpl CV_FINAL : public SoftmaxLayer`
`76`	`76`
`77`	`77`	`SoftMaxLayerImpl(const LayerParams& params)`
`78`	`78`	`{`
`79`		`- axisRaw = params.get<int>("axis", 1);`
	`79`	`+ axisRaw = params.get<int>("axis", -1);`
`80`	`80`	`logSoftMax = params.get<bool>("log_softmax", false);`
`81`	`81`	`setParamsFrom(params);`
`82`	`82`	`}`
Original file line number	Diff line number	Diff line change
`@@ -874,6 +874,9 @@ struct TorchImporter`
`874`	`874`	`{`
`875`	`875`	`newModule->apiType = "Softmax";`
`876`	`876`	`layerParams.set("log_softmax", nnName == "LogSoftMax");`
	`877`	`+ // set default axis to 1`
	`878`	`+ if(!layerParams.has("axis"))`
	`879`	`+ layerParams.set("axis", 1);`
`877`	`880`	`curModule->modules.push_back(newModule);`
`878`	`881`	`}`
`879`	`882`	`else if (nnName == "SpatialCrossMapLRN")`