[WebNN] Always create a new constant for zero_points (microsoft#25286)

MatMulNBits is a decomposed op in WebNN EP. Previously, we share the
WebNN constant of zero_points if they have the same value and data type.
However, this brings a lot of complexity for developers to fuse it back
to MatMulNBits in the underlying WebNN implementation in Chromium.

In this PR, we will always create a new constant for zero_points.

Author: Honry

onnxruntime/core/providers/webnn/builders/impl/matMulNBits_op_builder.cc

@@ -100,20 +100,25 @@ Status MatMulNBitsBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
   // x_zero_point has the same shape as x_scale
   const bool has_zero_points = TensorExists(input_defs, 3);
   emscripten::val x_zero_point = emscripten::val::undefined();
+  emscripten::val zero_points_desc = emscripten::val::object();
+  zero_points_desc.set("dataType", emscripten::val("uint4"));
+  zero_points_desc.set("shape", x_scale_shape_array);
+  zero_points_desc.set("dimensions", x_scale_shape_array);
   if (has_zero_points) {
     // zero_points is an initializer with data type 'uint8', we need to register it as 'uint4' WebNN constant
     const auto zero_points_tensor = *initializers.at(input_defs[3]->Name());
-    emscripten::val zero_points_desc = emscripten::val::object();
-    zero_points_desc.set("dataType", emscripten::val("uint4"));
-    zero_points_desc.set("shape", x_scale_shape_array);
-    zero_points_desc.set("dimensions", x_scale_shape_array);
     ORT_RETURN_IF_ERROR(model_builder.RegisterConstant(zero_points_tensor, x_zero_point, zero_points_desc, logger));
   } else {
     // zero_points' default value is 8, referred from CPU EP
     const int8_t default_zero_point = 8;
-    x_zero_point = model_builder.CreateOrGetConstant<int8_t>(ONNX_NAMESPACE::TensorProto_DataType_UINT4,
-                                                             default_zero_point,
-                                                             x_scale_shape);
+    // Always create a new WebNN constant for zero_points to facilitate MatMulNBits fusion in Chromium
+    auto num_elements = (Product(x_scale_shape) + 1) / 2;
+    emscripten::val default_zero_point_buffer = emscripten::val::global("Uint8Array").new_(num_elements);
+    default_zero_point_buffer.call<void>("fill",
+                                         emscripten::val(PackInt8ToUint8DoubledNibbles(
+                                             default_zero_point, ONNX_NAMESPACE::TensorProto_DataType_UINT4)));
+    x_zero_point =
+        model_builder.GetBuilder().call<emscripten::val>("constant", zero_points_desc, default_zero_point_buffer);
   }
 
   // DequantizeLinear