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, 350 insertions, 0 deletions

diff --git a/src/backends/backendsCommon/test/layerTests/DivisionTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/DivisionTestImpl.cpp
new file mode 100644
index 0000000000..0316ea185b
--- /dev/null
+++ b/src/backends/backendsCommon/test/layerTests/DivisionTestImpl.cpp
@@ -0,0 +1,350 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "DivisionTestImpl.hpp"
+
+#include "ElementwiseTestImpl.hpp"
+
+template<>
+std::unique_ptr<armnn::IWorkload> CreateWorkload<armnn::DivisionQueueDescriptor>(
+    const armnn::IWorkloadFactory& workloadFactory,
+    const armnn::WorkloadInfo& info,
+    const armnn::DivisionQueueDescriptor& descriptor)
+{
+    return workloadFactory.CreateDivision(descriptor, info);
+}
+
+LayerTestResult<float, 4> DivisionByZeroTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int width        = 2u;
+    const unsigned int height       = 2u;
+    const unsigned int channelCount = 2u;
+    const unsigned int batchSize    = 2u;
+
+    unsigned int shape[] = { batchSize, channelCount, height, width };
+
+    std::vector<float> input0 =
+    {
+         1.f,  1.f,  1.f,  1.f,  0.f, 0.f, 0.f, 0.f,
+        -1.f, -1.f, -1.f, -1.f,  5.f, 5.f, 5.f, 5.f
+    };
+
+    std::vector<float> input1 =
+    {
+        0.f, 0.f, -0.f, -0.f,  0.f, 0.f, -0.f, -0.f,
+        0.f, 0.f, -0.f, -0.f,  5.f, 5.f,  5.f,  5.f
+    };
+
+    std::vector<float> output =
+    {
+         INFINITY,  INFINITY, -INFINITY, -INFINITY,  NAN,  NAN, -NAN, -NAN,
+        -INFINITY, -INFINITY,  INFINITY,  INFINITY,    1,    1,    1,    1
+    };
+
+    return ElementwiseTestHelper<4, armnn::DivisionQueueDescriptor, armnn::DataType::Float32>(
+        workloadFactory,
+        memoryManager,
+        shape,
+        input0,
+        shape,
+        input1,
+        shape,
+        output);
+}
+
+LayerTestResult<float, 4> DivisionTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int width        = 2u;
+    const unsigned int height       = 2u;
+    const unsigned int channelCount = 2u;
+    const unsigned int batchSize    = 2u;
+
+    unsigned int shape[] = { batchSize, channelCount, height, width };
+
+    std::vector<float> input0 =
+    {
+        2.f, 2.f, 2.f, 2.f, 3.f, 3.f, 3.f, 3.f,
+        4.f, 4.f, 4.f, 4.f, 5.f, 5.f, 5.f, 5.f
+    };
+
+    std::vector<float> input1 =
+    {
+        1.f, 1.f, 1.f, 1.f, 2.f, 2.f, 2.f, 2.f,
+        4.f, 4.f, 4.f, 4.f, 4.f, 4.f, 4.f, 4.f
+    };
+
+    std::vector<float> output =
+    {
+        2.f, 2.f, 2.f, 2.f, 1.50f, 1.50f, 1.50f, 1.50f,
+        1.f, 1.f, 1.f, 1.f, 1.25f, 1.25f, 1.25f, 1.25f
+    };
+
+    return ElementwiseTestHelper<4, armnn::DivisionQueueDescriptor, armnn::DataType::Float32>(
+        workloadFactory,
+        memoryManager,
+        shape,
+        input0,
+        shape,
+        input1,
+        shape,
+        output);
+}
+
+LayerTestResult<float, 4> DivisionBroadcast1ElementTest(
+    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({ 2, 4, 6, 8, 10, 12, 14, 16});
+
+    std::vector<float> input1({ 2 });
+
+    std::vector<float> output({ 1, 2, 3, 4, 5, 6, 7, 8});
+
+    return ElementwiseTestHelper<4, armnn::DivisionQueueDescriptor, armnn::DataType::Float32>(
+        workloadFactory,
+        memoryManager,
+        shape0,
+        input0,
+        shape1,
+        input1,
+        shape0,
+        output);
+}
+
+LayerTestResult<float, 4> DivisionBroadcast1DVectorTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    unsigned int shape0[] = { 1, 3, 3, 2 };
+    unsigned int shape1[] = { 1, 1, 1, 2 };
+
+    std::vector<float> input0 =
+    {
+         1.f,  4.f,  3.f,  8.f,  5.f, 12.f,
+         7.f, 16.f,  9.f, 20.f, 11.f, 24.f,
+        13.f, 28.f, 15.f, 32.f, 17.f, 36.f
+    };
+
+    std::vector<float> input1 = { 1.f, 2.f };
+
+    std::vector<float> output =
+    {
+         1.f,  2.f,  3.f,  4.f,  5.f,  6.f,
+         7.f,  8.f,  9.f, 10.f, 11.f, 12.f,
+        13.f, 14.f, 15.f, 16.f, 17.f, 18.f
+    };
+
+    return ElementwiseTestHelper<4, armnn::DivisionQueueDescriptor, armnn::DataType::Float32>(
+        workloadFactory,
+        memoryManager,
+        shape0,
+        input0,
+        shape1,
+        input1,
+        shape0,
+        output);
+}
+
+LayerTestResult<uint8_t, 4> DivisionUint8Test(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int width        = 2u;
+    const unsigned int height       = 2u;
+    const unsigned int channelCount = 2u;
+    const unsigned int batchSize    = 2u;
+
+    unsigned int shape[] = { batchSize, channelCount, height, width };
+
+    std::vector<uint8_t> input0 =
+    {
+        2, 2, 2, 2,  3, 3, 3, 3,
+        4, 4, 4, 4,  5, 5, 5, 5
+    };
+
+    std::vector<uint8_t> input1 =
+    {
+        1, 1, 1, 1,  2, 2, 2, 2,
+        4, 4, 4, 4,  4, 4, 4, 4
+    };
+
+    std::vector<uint8_t> output =
+    {
+        8, 8, 8, 8,  6, 6, 6, 6,
+        4, 4, 4, 4,  5, 5, 5, 5
+    };
+
+    return ElementwiseTestHelper<4, armnn::DivisionQueueDescriptor, armnn::DataType::QuantisedAsymm8>(
+        workloadFactory,
+        memoryManager,
+        shape,
+        input0,
+        shape,
+        input1,
+        shape,
+        output,
+        0.25f,
+        0);
+}
+
+LayerTestResult<uint8_t, 4> DivisionBroadcast1ElementUint8Test(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    unsigned int shape0[] = { 1, 2, 2, 2 };
+    unsigned int shape1[] = { 1, 1, 1, 1 };
+
+    std::vector<uint8_t> input0 = { 2, 4, 6, 8, 10, 12, 14, 16};
+
+    std::vector<uint8_t> input1 = { 2 };
+
+    std::vector<uint8_t> output = { 1, 2, 3, 4, 5, 6, 7, 8};
+
+    return ElementwiseTestHelper<4, armnn::DivisionQueueDescriptor, armnn::DataType::QuantisedAsymm8>(
+        workloadFactory,
+        memoryManager,
+        shape0,
+        input0,
+        shape1,
+        input1,
+        shape0,
+        output);
+}
+
+LayerTestResult<uint8_t, 4> DivisionBroadcast1DVectorUint8Test(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    unsigned int shape0[] = { 1, 3, 3, 2 };
+    unsigned int shape1[] = { 1, 1, 1, 2 };
+
+    std::vector<uint8_t> input0 =
+    {
+        1,  4,    3,  8,    5, 12,
+        7, 16,    9, 20,   11, 24,
+       13, 28,   15, 32,   17, 36
+    };
+
+    std::vector<uint8_t> input1 = { 1, 2 };
+
+    std::vector<uint8_t> output =
+    {
+        1,  2,    3,  4,    5,  6,
+        7,  8,    9, 10,   11, 12,
+       13, 14,   15, 16,   17, 18
+    };
+
+    return ElementwiseTestHelper<4, armnn::DivisionQueueDescriptor, armnn::DataType::QuantisedAsymm8>(
+        workloadFactory,
+        memoryManager,
+        shape0,
+        input0,
+        shape1,
+        input1,
+        shape0,
+        output);
+}
+
+LayerTestResult<int16_t,4> DivisionInt16Test(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    unsigned int shape[] = { 2, 2, 2, 2 };
+
+    std::vector<int16_t> input0 =
+    {
+        2, 2, 2, 2,  3, 3, 3, 3,
+        4, 4, 4, 4,  5, 5, 5, 5
+    };
+
+    std::vector<int16_t> input1 =
+    {
+        1, 1, 1, 1,  2, 2, 2, 2,
+        4, 4, 4, 4,  4, 4, 4, 4
+    };
+
+    std::vector<int16_t> output =
+    {
+        8, 8, 8, 8,  6, 6, 6, 6,
+        4, 4, 4, 4,  5, 5, 5, 5
+    };
+
+    return ElementwiseTestHelper<4, armnn::DivisionQueueDescriptor, armnn::DataType::QuantisedSymm16>(
+        workloadFactory,
+        memoryManager,
+        shape,
+        input0,
+        shape,
+        input1,
+        shape,
+        output,
+        0.25f,
+        0);
+}
+
+LayerTestResult<int16_t, 4> DivisionBroadcast1ElementInt16Test(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    unsigned int shape0[] = { 1, 2, 2, 2 };
+    unsigned int shape1[] = { 1, 1, 1, 1 };
+
+    std::vector<int16_t> input0 = { 2, 4, 6, 8, 10, 12, 14, 16};
+
+    std::vector<int16_t> input1 = { 2 };
+
+    std::vector<int16_t> output = { 1, 2, 3, 4, 5, 6, 7, 8};
+
+    return ElementwiseTestHelper<4, armnn::DivisionQueueDescriptor, armnn::DataType::QuantisedSymm16>(
+        workloadFactory,
+        memoryManager,
+        shape0,
+        input0,
+        shape1,
+        input1,
+        shape0,
+        output);
+}
+
+LayerTestResult<int16_t, 4> DivisionBroadcast1DVectorInt16Test(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    unsigned int shape0[] = { 1, 3, 3, 2 };
+    unsigned int shape1[] = { 1, 1, 1, 2 };
+
+    std::vector<int16_t> input0 =
+    {
+         1,  4,    3,  8,    5, 12,
+         7, 16,    9, 20,   11, 24,
+        13, 28,   15, 32,   17, 36
+    };
+
+    std::vector<int16_t> input1 = { 1, 2 };
+
+    std::vector<int16_t> output =
+    {
+         1,  2,    3,  4,    5,  6,
+         7,  8,    9, 10,   11, 12,
+        13, 14,   15, 16,   17, 18
+    };
+
+    return ElementwiseTestHelper<4, armnn::DivisionQueueDescriptor, armnn::DataType::QuantisedSymm16>(
+        workloadFactory,
+        memoryManager,
+        shape0,
+        input0,
+        shape1,
+        input1,
+        shape0,
+        output);
+}