[WebNN EP] Make sure optional input is provided (microsoft#19686)

Some optional input is presented as empty string, we should not only check if the input size is correct, but also check if the optional input is not empty. e.g. Pad node has empty optional input in sam-b-encoder.onnx model: <img width="514" alt="image" src="https://github.com/microsoft/onnxruntime/assets/3271201/cc3b06fe-46b9-4ee7-aca5-157bdf112856">
zz002 · Mar 7, 2024 · ed01070 · ed01070
1 parent 99f8f91
commit ed01070
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Showing 4 changed files with 6 additions and 6 deletions.
diff --git a/onnxruntime/core/providers/webnn/builders/impl/pad_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/pad_op_builder.cc
@@ -88,15 +88,15 @@ Status PadOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
     const auto& pads_tensor = *initializers.at(input_defs[1]->Name());
     ORT_RETURN_IF_NOT(ReadIntArrayFrom1DTensor(pads_tensor, pads, logger), "Error while read pads tensor");
 
-    // Constant value and axes are optional.
-    if (input_defs.size() >= 3) {
+    // Constant value and axes are optional. Make sure they are not empty.
+    if (!GetTensorName(input_defs, 2).empty()) {
       const auto value_tensor = *initializers.at(input_defs[2]->Name());
       emscripten::val value = emscripten::val::object();
       ORT_RETURN_IF_NOT(ReadScalarTensorData(value_tensor, value, logger), "Cannot read constant value");
       options.set("value", value);
     }
 
-    if (input_defs.size() == 4) {
+    if (!GetTensorName(input_defs, 3).empty()) {
       const auto input_rank = input_shape.size();
       std::vector<int64_t> axes;
       const auto& axes_tensor = *initializers.at(input_defs[3]->Name());

diff --git a/onnxruntime/core/providers/webnn/builders/impl/reduction_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/reduction_op_builder.cc
@@ -65,7 +65,7 @@ Status ReductionOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
   if (opset >= 18 || (op_type == "ReduceSum" && opset >= 13)) {
     // 'axes' is an optional input.
     const auto noop_with_empty_axes = helper.Get("noop_with_empty_axes", 0);
-    if (input_defs.size() > 1) {
+    if (!GetTensorName(input_defs, 1).empty()) {
       // Optional input axes is provided, use axes initializer data.
       const auto& initializers(model_builder.GetInitializerTensors());
       const auto& axes_tensor = *initializers.at(input_defs[1]->Name());

diff --git a/onnxruntime/core/providers/webnn/builders/impl/split_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/split_op_builder.cc
@@ -57,7 +57,7 @@ Status SplitOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
   axis = SafeInt<int32_t>(HandleNegativeAxis(axis, rank));
   options.set("axis", axis);
 
-  if (input_defs.size() == 2) {
+  if (!GetTensorName(input_defs, 1).empty()) {
     // Inputs contains optional 'split' input
     std::vector<int32_t> splits;
     const auto& initializers(model_builder.GetInitializerTensors());

diff --git a/onnxruntime/core/providers/webnn/builders/impl/squeeze_unsqueeze_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/squeeze_unsqueeze_op_builder.cc
@@ -58,7 +58,7 @@ Status SqueezeUnsqueezeOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_buil
   std::vector<int32_t> axes_data;
   auto rank = input_rank;
 
-  if (node.SinceVersion() >= 13 && input_defs.size() > 1) {
+  if (node.SinceVersion() >= 13 && !GetTensorName(input_defs, 1).empty()) {
     // Input axes is provided, use axes initializer data.
     const auto& initializers = model_builder.GetInitializerTensors();
     const auto& axes_tensor = *initializers.at(input_defs[1]->Name());