[WebNN] Fix bug in SkipSimplifiedLayerNormalization (#23236)

The input should be added by skip and bias (if it exits) firstly.
microsoft · Jan 7, 2025 · 519fae0 · 519fae0
1 parent 655b3ef
commit 519fae0
Showing 1 changed file with 19 additions and 17 deletions.
diff --git a/onnxruntime/core/providers/webnn/builders/impl/normalization_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/normalization_op_builder.cc
@@ -76,8 +76,6 @@ Status NormalizationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder
   options.set("epsilon", epsilon);
 
   emscripten::val output = emscripten::val::undefined();
-  // SkipSimplifiedLayerNormalization's output: input_skip_bias_sum.
-  emscripten::val input_skip_bias_sum = emscripten::val::undefined();
   if (op_type == "BatchNormalization") {
     ORT_RETURN_IF_NOT(input_defs.size() == 5, "BatchNormalization requires five inputs.");
     emscripten::val mean = model_builder.GetOperand(input_defs[3]->Name());
@@ -107,14 +105,31 @@ Status NormalizationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder
                 |          |           |                |      |       |
                Y:2        axis     B:epsilon           A:X  A:scale  B:bias
 
-      If it is SkipSimplifiedLayerNormalization and its output input_skip_bias_sum exists,
+      If it is SkipSimplifiedLayerNormalization, X should be input_skip_bias_sum:
       input_skip_bias_sum = X + skip + bias (if it exists)
       */
 
       int32_t input_type;
       ORT_RETURN_IF_NOT(GetType(*input_defs[0], input_type, logger), "Cannot get input type");
       emscripten::val common_options = emscripten::val::object();
 
+      // If it is SkipSimplifiedLayerNormalization, add the skip and bias (if it exists) to the input.
+      if (op_type == "SkipSimplifiedLayerNormalization") {
+        emscripten::val skip = model_builder.GetOperand(input_defs[1]->Name());
+        common_options.set("label", node.Name() + "_add_skip");
+        input = model_builder.GetBuilder().call<emscripten::val>("add", input, skip, common_options);
+        if (!bias.isUndefined()) {
+          common_options.set("label", node.Name() + "_add_skip_bias");
+          input = model_builder.GetBuilder().call<emscripten::val>("add", input, bias, common_options);
+        }
+
+        // Add SkipSimplifiedLayerNormalization's output input_skip_bias_sum if it exists.
+        // Now input equals to input_skip_bias_sum.
+        if (TensorExists(output_defs, 3)) {
+          model_builder.AddOperand(output_defs[3]->Name(), input);
+        }
+      }
+
       // Pow
       emscripten::val pow_constant = model_builder.CreateOrGetConstant<float>(input_type, 2);
       common_options.set("label", node.Name() + "_pow");
@@ -146,24 +161,11 @@ Status NormalizationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder
       common_options.set("label", node.Name() + "_mul");
       output = model_builder.GetBuilder().call<emscripten::val>("mul", scale, div, common_options);
 
-      // Add (if bias exits)
+      // Add (if bias exists)
       if (!bias.isUndefined()) {
         common_options.set("label", node.Name() + "_add_bias");
         output = model_builder.GetBuilder().call<emscripten::val>("add", output, bias, common_options);
       }
-
-      // SkipSimplifiedLayerNormalization's output input_skip_bias_sum is the sum of input, skip, and bias.
-      if (op_type == "SkipSimplifiedLayerNormalization" && TensorExists(output_defs, 3)) {
-        emscripten::val skip = model_builder.GetOperand(input_defs[1]->Name());
-        common_options.set("label", node.Name() + "_add_skip");
-        input_skip_bias_sum = model_builder.GetBuilder().call<emscripten::val>("add", input, skip, common_options);
-        if (!bias.isUndefined()) {
-          common_options.set("label", node.Name() + "_add_skip_bias");
-          input_skip_bias_sum = model_builder.GetBuilder().call<emscripten::val>(
-              "add", input_skip_bias_sum, bias, common_options);
-        }
-        model_builder.AddOperand(output_defs[3]->Name(), std::move(input_skip_bias_sum));
-      }
     }
   } else if (op_type == "InstanceNormalization") {
     // WebNN spec only supports 4D input for instanceNormalization.