Add @1.2::IPreparedModel::executeSynchronously() and corresponding VTS tests.

Bug: 119274127

Test: all of the following, with the appropriate android.hardware.neuralnetworks@1.${X}::IDevice/sample-all
    VtsHalNeuralnetworksV1_0TargetTest
    VtsHalNeuralnetworksV1_0TargetTest
    VtsHalNeuralnetworksV1_1CompatV1_0TargetTest
    VtsHalNeuralnetworksV1_1CompatV1_0TargetTest
    VtsHalNeuralnetworksV1_1TargetTest
    VtsHalNeuralnetworksV1_1TargetTest
    VtsHalNeuralnetworksV1_2CompatV1_0TargetTest
    VtsHalNeuralnetworksV1_2CompatV1_0TargetTest
    VtsHalNeuralnetworksV1_2CompatV1_1TargetTest
    VtsHalNeuralnetworksV1_2CompatV1_1TargetTest
    VtsHalNeuralnetworksV1_2TargetTest
    VtsHalNeuralnetworksV1_2TargetTest

Change-Id: Iedfa485b4008d9cec3b81ff4c0ce3ebc0b83c823
(cherry picked from commit 49e41678f5781230b9f7bf02cc4886fee9891b71)
diff --git a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
index ab524c2..7c5b0bc 100644
--- a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
+++ b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
@@ -88,11 +88,22 @@
                                                 sp<ExecutionCallback>& callback) {
     return preparedModel->execute_1_2(request, callback);
 }
+static Return<ErrorStatus> ExecutePreparedModel(sp<V1_0::IPreparedModel>&, const Request&) {
+    ADD_FAILURE() << "asking for synchronous execution at V1_0";
+    return ErrorStatus::GENERAL_FAILURE;
+}
+static Return<ErrorStatus> ExecutePreparedModel(sp<V1_2::IPreparedModel>& preparedModel,
+                                                const Request& request) {
+    return preparedModel->executeSynchronously(request);
+}
+enum class Synchronously { NO, YES };
+const float kDefaultAtol = 1e-5f;
+const float kDefaultRtol = 1e-5f;
 template <typename T_IPreparedModel>
 void EvaluatePreparedModel(sp<T_IPreparedModel>& preparedModel, std::function<bool(int)> is_ignored,
                            const std::vector<MixedTypedExample>& examples,
-                           bool hasRelaxedFloat32Model = false, float fpAtol = 1e-5f,
-                           float fpRtol = 1e-5f) {
+                           bool hasRelaxedFloat32Model = false, float fpAtol = kDefaultAtol,
+                           float fpRtol = kDefaultRtol, Synchronously sync = Synchronously::NO) {
     const uint32_t INPUT = 0;
     const uint32_t OUTPUT = 1;
 
@@ -185,19 +196,31 @@
         inputMemory->commit();
         outputMemory->commit();
 
-        // launch execution
-        sp<ExecutionCallback> executionCallback = new ExecutionCallback();
-        ASSERT_NE(nullptr, executionCallback.get());
-        Return<ErrorStatus> executionLaunchStatus = ExecutePreparedModel(
-            preparedModel, {.inputs = inputs_info, .outputs = outputs_info, .pools = pools},
-            executionCallback);
-        ASSERT_TRUE(executionLaunchStatus.isOk());
-        EXPECT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(executionLaunchStatus));
+        if (sync == Synchronously::NO) {
+            SCOPED_TRACE("asynchronous");
 
-        // retrieve execution status
-        executionCallback->wait();
-        ErrorStatus executionReturnStatus = executionCallback->getStatus();
-        EXPECT_EQ(ErrorStatus::NONE, executionReturnStatus);
+            // launch execution
+            sp<ExecutionCallback> executionCallback = new ExecutionCallback();
+            ASSERT_NE(nullptr, executionCallback.get());
+            Return<ErrorStatus> executionLaunchStatus = ExecutePreparedModel(
+                preparedModel, {.inputs = inputs_info, .outputs = outputs_info, .pools = pools},
+                executionCallback);
+            ASSERT_TRUE(executionLaunchStatus.isOk());
+            EXPECT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(executionLaunchStatus));
+
+            // retrieve execution status
+            executionCallback->wait();
+            ErrorStatus executionReturnStatus = executionCallback->getStatus();
+            EXPECT_EQ(ErrorStatus::NONE, executionReturnStatus);
+        } else {
+            SCOPED_TRACE("synchronous");
+
+            // execute
+            Return<ErrorStatus> executionStatus = ExecutePreparedModel(
+                preparedModel, {.inputs = inputs_info, .outputs = outputs_info, .pools = pools});
+            ASSERT_TRUE(executionStatus.isOk());
+            EXPECT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(executionStatus));
+        }
 
         // validate results
         outputMemory->read();
@@ -215,6 +238,13 @@
         }
     }
 }
+template <typename T_IPreparedModel>
+void EvaluatePreparedModel(sp<T_IPreparedModel>& preparedModel, std::function<bool(int)> is_ignored,
+                           const std::vector<MixedTypedExample>& examples,
+                           bool hasRelaxedFloat32Model, Synchronously sync) {
+    EvaluatePreparedModel(preparedModel, is_ignored, examples, hasRelaxedFloat32Model, kDefaultAtol,
+                          kDefaultRtol, sync);
+}
 
 static void getPreparedModel(sp<PreparedModelCallback> callback,
                              sp<V1_0::IPreparedModel>* preparedModel) {
@@ -362,7 +392,9 @@
     ASSERT_NE(nullptr, preparedModel.get());
 
     EvaluatePreparedModel(preparedModel, is_ignored, examples,
-                          model.relaxComputationFloat32toFloat16);
+                          model.relaxComputationFloat32toFloat16, Synchronously::NO);
+    EvaluatePreparedModel(preparedModel, is_ignored, examples,
+                          model.relaxComputationFloat32toFloat16, Synchronously::YES);
 }
 
 }  // namespace generated_tests