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

1 files changed, 196 insertions, 0 deletions

diff --git a/src/backends/backendsCommon/test/layerTests/MinimumTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/MinimumTestImpl.cpp
new file mode 100644
index 0000000000..eabad8f852
--- /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);
+}