Add control flow support to NNAPI VTS tests
See change I98a3edd1.
Bug: 148077633
Bug: 148601177
Bug: 136735929
Test: VtsHalNeuralnetworksV1_0TargetTest
Test: VtsHalNeuralnetworksV1_1TargetTest
Test: VtsHalNeuralnetworksV1_2TargetTest
Test: VtsHalNeuralnetworksV1_3TargetTest
Change-Id: I1e436cdba404b68026a45797ac4fb3a34f8be76a
Merged-In: I1e436cdba404b68026a45797ac4fb3a34f8be76a
(cherry picked from commit 1f98e2e9292faf4c2a28a4558a303492d4f7eefe)
diff --git a/neuralnetworks/1.3/vts/functional/QualityOfServiceTests.cpp b/neuralnetworks/1.3/vts/functional/QualityOfServiceTests.cpp
index 76d133a..8271135 100644
--- a/neuralnetworks/1.3/vts/functional/QualityOfServiceTests.cpp
+++ b/neuralnetworks/1.3/vts/functional/QualityOfServiceTests.cpp
@@ -239,12 +239,13 @@
// If the model output operands are fully specified, outputShapes must be either
// either empty, or have the same number of elements as the number of outputs.
- ASSERT_TRUE(outputShapes.size() == 0 || outputShapes.size() == testModel.outputIndexes.size());
+ ASSERT_TRUE(outputShapes.size() == 0 ||
+ outputShapes.size() == testModel.main.outputIndexes.size());
// Go through all outputs, check returned output shapes.
for (uint32_t i = 0; i < outputShapes.size(); i++) {
EXPECT_TRUE(outputShapes[i].isSufficient);
- const auto& expect = testModel.operands[testModel.outputIndexes[i]].dimensions;
+ const auto& expect = testModel.main.operands[testModel.main.outputIndexes[i]].dimensions;
const std::vector<uint32_t> actual = outputShapes[i].dimensions;
EXPECT_EQ(expect, actual);
}