Minor modification to allow relaxed precision test (760089b0) · Commits · e / os / android_hardware_interfaces

neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp

+6 −3

Original line number	Diff line number	Diff line
		@@ -66,7 +66,8 @@ void copy_back(MixedTyped* dst, const std::vector<RequestArgument>& ra, char* sr
		// Top level driver for models and examples generated by test_generator.py
		// Test driver for those generated from ml/nn/runtime/test/spec
		void EvaluatePreparedModel(sp<IPreparedModel>& preparedModel, std::function<bool(int)> is_ignored,
		const std::vector<MixedTypedExampleType>& examples) {
		const std::vector<MixedTypedExampleType>& examples,
		float fpRange = 1e-5f) {
		const uint32_t INPUT = 0;
		const uint32_t OUTPUT = 1;

		@@ -174,7 +175,7 @@ void EvaluatePreparedModel(sp<IPreparedModel>& preparedModel, std::function<bool
		MixedTyped filtered_test = filter(test, is_ignored);

		// We want "close-enough" results for float
		compare(filtered_golden, filtered_test);
		compare(filtered_golden, filtered_test, fpRange);
		}
		}

		@@ -274,7 +275,9 @@ void Execute(sp<V1_1::IDevice>& device, std::function<V1_1::Model(void)> create_
		}
		ASSERT_NE(nullptr, preparedModel.get());

		EvaluatePreparedModel(preparedModel, is_ignored, examples);
		// If in relaxed mode, set the error range to be 5ULP of FP16.
		float fpRange = !model.relaxComputationFloat32toFloat16 ? 1e-5f : 5.0f * 0.0009765625f;
		EvaluatePreparedModel(preparedModel, is_ignored, examples, fpRange);
		}

		} // namespace generated_tests