IVGCVSW-2325 Reduce duplication in LayerTests by reusing the ElementwiseTestHelper
* Refactored tests for element-wise operations to use ElementwiseTestHelper
* Moved the etasts for each operation in a separate file under backendsCommon/test/layerTests
Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Change-Id: Icefb6b35df78b9619f69378229789505bf92670e
diff --git a/src/backends/backendsCommon/test/layerTests/MinimumTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/MinimumTestImpl.cpp
new file mode 100644
index 0000000..eabad8f
--- /dev/null
+++ b/src/backends/backendsCommon/test/layerTests/MinimumTestImpl.cpp
@@ -0,0 +1,196 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "MinimumTestImpl.hpp"
+
+#include "ElementwiseTestImpl.hpp"
+
+template<>
+std::unique_ptr<armnn::IWorkload> CreateWorkload<armnn::MinimumQueueDescriptor>(
+ const armnn::IWorkloadFactory& workloadFactory,
+ const armnn::WorkloadInfo& info,
+ const armnn::MinimumQueueDescriptor& descriptor)
+{
+ return workloadFactory.CreateMinimum(descriptor, info);
+}
+
+LayerTestResult<float, 4> MinimumBroadcast1ElementTest1(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+ unsigned int shape0[] = { 1, 2, 2, 2 };
+ unsigned int shape1[] = { 1, 1, 1, 1 };
+
+ std::vector<float> input0 = { 1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f };
+
+ std::vector<float> input1 = { 2.f };
+
+ std::vector<float> output = { 1.f, 2.f, 2.f, 2.f, 2.f, 2.f, 2.f, 2.f };
+
+ return ElementwiseTestHelper<4, armnn::MinimumQueueDescriptor, armnn::DataType::Float32>(
+ workloadFactory,
+ memoryManager,
+ shape0,
+ input0,
+ shape1,
+ input1,
+ shape0,
+ output);
+}
+
+LayerTestResult<float, 4> MinimumBroadcast1ElementTest2(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+ unsigned int shape0[] = { 1, 2, 2, 2 };
+ unsigned int shape1[] = { 1, 1, 1, 1 };
+
+ std::vector<float> input0 = { 1.f, 6.f, 3.f, 2.f, 8.f, 9.f, 1.f, 10.f };
+
+ std::vector<float> input1 = { 5.f };
+
+ std::vector<float> output = { 1.f, 5.f, 3.f, 2.f, 5.f, 5.f, 1.f, 5.f };
+
+ return ElementwiseTestHelper<4, armnn::MinimumQueueDescriptor, armnn::DataType::Float32>(
+ workloadFactory,
+ memoryManager,
+ shape0,
+ input0,
+ shape1,
+ input1,
+ shape0,
+ output);
+}
+
+LayerTestResult<uint8_t, 4> MinimumBroadcast1DVectorUint8Test(
+ armnn::IWorkloadFactory & workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager)
+{
+ const unsigned int shape0[] = { 1, 2, 2, 3 };
+ const unsigned int shape1[] = { 1, 1, 1, 3 };
+
+ std::vector<uint8_t> input0 =
+ {
+ 1, 2, 3, 3, 2, 1,
+ 7, 1, 2, 3, 4, 5
+ };
+
+ std::vector<uint8_t> input1 = { 1, 2, 3 };
+
+ std::vector<uint8_t> output =
+ {
+ 1, 2, 3, 1, 2, 1,
+ 1, 1, 2, 1, 2, 3
+ };
+
+ return ElementwiseTestHelper<4, armnn::MinimumQueueDescriptor, armnn::DataType::QuantisedAsymm8>(
+ workloadFactory,
+ memoryManager,
+ shape0,
+ input0,
+ shape1,
+ input1,
+ shape0,
+ output);
+}
+
+LayerTestResult<int16_t, 4> MinimumInt16Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+ unsigned int shape[] = { 2, 2, 2, 2 };
+
+ std::vector<int16_t> input0 =
+ {
+ 1, 1, 1, 1, 6, 6, 6, 6,
+ 3, 3, 3, 3, 4, 4, 4, 4
+ };
+
+ std::vector<int16_t> input1 =
+ {
+ 2, 2, 2, 2, 3, 3, 3, 3,
+ 4, 4, 4, 4, 5, 5, 5, 5
+ };
+
+ std::vector<int16_t> output
+ {
+ 1, 1, 1, 1, 3, 3, 3, 3,
+ 3, 3, 3, 3, 4, 4, 4, 4
+ };
+
+ return ElementwiseTestHelper<4, armnn::MinimumQueueDescriptor, armnn::DataType::QuantisedSymm16>(
+ workloadFactory,
+ memoryManager,
+ shape,
+ input0,
+ shape,
+ input1,
+ shape,
+ output);
+}
+
+LayerTestResult<int16_t, 4> MinimumBroadcast1ElementInt16Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+ const unsigned int shape0[] = { 1, 2, 2, 3 };
+ const unsigned int shape1[] = { 1, 1, 1, 1 };
+
+ std::vector<int16_t> input0 =
+ {
+ 1, 2, 3, 4, 5, 6,
+ 7, 8, 9, 10, 11, 12
+ };
+
+ std::vector<int16_t> input1 = { 2 };
+
+ std::vector<int16_t> output =
+ {
+ 1, 2, 2, 2, 2, 2,
+ 2, 2, 2, 2, 2, 2
+ };
+
+ return ElementwiseTestHelper<4, armnn::MinimumQueueDescriptor, armnn::DataType::QuantisedSymm16>(
+ workloadFactory,
+ memoryManager,
+ shape0,
+ input0,
+ shape1,
+ input1,
+ shape0,
+ output);
+}
+
+LayerTestResult<int16_t, 4> MinimumBroadcast1DVectorInt16Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+ const unsigned int shape0[] = { 1, 2, 2, 3 };
+ const unsigned int shape1[] = { 1, 1, 1, 3 };
+
+ std::vector<int16_t> input0 =
+ {
+ 1, 2, 3, 4, 5, 6,
+ 7, 8, 9, 10, 11, 12
+ };
+
+ std::vector<int16_t> input1 = { 1, 10, 3 };
+
+ std::vector<int16_t> output =
+ {
+ 1, 2, 3, 1, 5, 3,
+ 1, 8, 3, 1, 10, 3
+ };
+
+ return ElementwiseTestHelper<4, armnn::MinimumQueueDescriptor, armnn::DataType::QuantisedSymm16>(
+ workloadFactory,
+ memoryManager,
+ shape0,
+ input0,
+ shape1,
+ input1,
+ shape0,
+ output);
+}