use SimpleValue instead of EngineOrFactory

1 files changed, 8 insertions, 7 deletions

diff --git a/streamingvisitors/src/tests/hitcollector/hitcollector_test.cpp b/streamingvisitors/src/tests/hitcollector/hitcollector_test.cpp
index e2c47da6997..087a3be86d3 100644
--- a/streamingvisitors/src/tests/hitcollector/hitcollector_test.cpp
+++ b/streamingvisitors/src/tests/hitcollector/hitcollector_test.cpp
@@ -6,9 +6,10 @@
 #include <vespa/searchlib/fef/matchdata.h>
 #include <vespa/searchlib/fef/feature_resolver.h>
 #include <vespa/searchvisitor/hitcollector.h>
-#include <vespa/eval/eval/value.h>
+#include <vespa/eval/eval/simple_value.h>
 #include <vespa/eval/eval/tensor_spec.h>
-#include <vespa/eval/eval/engine_or_factory.h>
+#include <vespa/eval/eval/value.h>
+#include <vespa/eval/eval/value_codec.h>
 #include <vespa/vespalib/objects/nbostream.h>
 
 using namespace document;
@@ -17,10 +18,11 @@ using namespace vespalib;
 using namespace vdslib;
 using namespace vsm;
 using vespalib::nbostream;
-using vespalib::eval::EngineOrFactory;
-using vespalib::eval::Value;
 using vespalib::eval::DoubleValue;
+using vespalib::eval::SimpleValue;
 using vespalib::eval::TensorSpec;
+using vespalib::eval::Value;
+
 
 namespace streaming {
 
@@ -252,7 +254,7 @@ public:
     ~MyRankProgram();
     virtual void run(uint32_t docid, const std::vector<search::fef::TermFieldMatchData> &) override {
         _boxed_double = std::make_unique<DoubleValue>(docid + 30);
-        _tensor = EngineOrFactory::get().from_spec(TensorSpec("tensor(x{})").add({{"x", "a"}}, docid + 20));
+        _tensor = SimpleValue::from_spec(TensorSpec("tensor(x{})").add({{"x", "a"}}, docid + 20));
         _fooValue.as_number = docid + 10;
         _barValue.as_object = *_boxed_double;
         _bazValue.as_object = *_tensor;
@@ -307,9 +309,8 @@ HitCollectorTest::testFeatureSet()
         EXPECT_TRUE(!f[2].is_double());
         EXPECT_TRUE(f[2].is_data());
         {
-            auto engine = EngineOrFactory::get();
             nbostream buf(f[2].as_data().data, f[2].as_data().size);
-            auto actual = engine.to_spec(*engine.decode(buf));
+            auto actual = spec_from_value(*SimpleValue::from_stream(buf));
             auto expect = TensorSpec("tensor(x{})").add({{"x", "a"}}, 23);
             EXPECT_EQUAL(actual, expect);
         }