commit bb8d7591a35bd95480b39001f8b7e41a6671f3a6
author Tracy Narine <tracy.narine@arm.com> Thu Jul 13 16:50:54 2023 +0100
committer Tracy Narine <tracy.narine@arm.com> Mon Jul 17 14:19:36 2023 +0100
tree abf2871aa1bb86378f423df405164b0d4521db3f
parent 688268328c69e7d4181cdd31fe4717c80a6d1685

IVGCVSW-7879 Change REVERSE_V2 from LayerWithParameters with 1 input, to Layer with 2 inputs

  * Changing ReverseV2 to use two inputs
  * This is required by the backends
  * The ReverseV2Descriptor was removed
  * Tests updated
  * Added a Run<> templatefor inputs with different data types

Signed-off-by: Tracy Narine <tracy.narine@arm.com>
Change-Id: I22f947de829b4b3da6bda3a74f4ffdef4052cc25

src/armnnDeserializer/test/ParserFlatbuffersSerializeFixture.hpp

diff --git a/src/armnnDeserializer/test/ParserFlatbuffersSerializeFixture.hpp b/src/armnnDeserializer/test/ParserFlatbuffersSerializeFixture.hpp
index 31ff026..0b717bc 100644
--- a/src/armnnDeserializer/test/ParserFlatbuffersSerializeFixture.hpp
+++ b/src/armnnDeserializer/test/ParserFlatbuffersSerializeFixture.hpp
@@ -1,5 +1,5 @@
 //
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2019-2023 Arm Ltd. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
 
@@ -150,6 +150,18 @@
                  const std::map<std::string, std::vector<InputDataType>>& inputData,
                  const std::map<std::string, std::vector<OutputDataType>>& expectedOutputData);
 
+    template<std::size_t NumOutputDimensions,
+            armnn::DataType ArmnnInputType0,
+            armnn::DataType ArmnnInputType1,
+            armnn::DataType ArmnnOutputType,
+            typename InputDataType0 = armnn::ResolveType<ArmnnInputType0>,
+            typename InputDataType1 = armnn::ResolveType<ArmnnInputType1>,
+            typename OutputDataType = armnn::ResolveType<ArmnnOutputType>>
+    void RunTest(unsigned int layersId,
+                 const std::map<std::string, std::vector<InputDataType0>>& inputData0,
+                 const std::map<std::string, std::vector<InputDataType1>>& inputData1,
+                 const std::map<std::string, std::vector<OutputDataType>>& expectedOutputData);
+
     void CheckTensors(const TensorRawPtr& tensors, size_t shapeSize, const std::vector<int32_t>& shape,
                       armnnSerializer::TensorInfo tensorType, const std::string& name,
                       const float scale, const int64_t zeroPoint)
@@ -246,3 +258,68 @@
         CHECK_MESSAGE(result.m_Result, result.m_Message.str());
     }
 }
+
+template<std::size_t NumOutputDimensions,
+        armnn::DataType ArmnnInputType0,
+        armnn::DataType ArmnnInputType1,
+        armnn::DataType ArmnnOutputType,
+        typename InputDataType0,
+        typename InputDataType1,
+        typename OutputDataType>
+void ParserFlatbuffersSerializeFixture::RunTest(
+        unsigned int layersId,
+        const std::map<std::string, std::vector<InputDataType0>>& inputData0,
+        const std::map<std::string, std::vector<InputDataType1>>& inputData1,
+        const std::map<std::string, std::vector<OutputDataType>>& expectedOutputData)
+{
+    auto ConvertBindingInfo = [](const armnnDeserializer::BindingPointInfo& bindingInfo)
+    {
+        return std::make_pair(bindingInfo.m_BindingId, bindingInfo.m_TensorInfo);
+    };
+
+    // Setup the armnn input tensors from the given vectors.
+    armnn::InputTensors inputTensors;
+    for (auto&& it : inputData0)
+    {
+        armnn::BindingPointInfo bindingInfo = ConvertBindingInfo(
+            m_Parser->GetNetworkInputBindingInfo(layersId, it.first));
+        bindingInfo.second.SetConstant(true);
+        armnn::VerifyTensorInfoDataType(bindingInfo.second, ArmnnInputType0);
+        inputTensors.push_back({ bindingInfo.first, armnn::ConstTensor(bindingInfo.second, it.second.data()) });
+    }
+
+    for (auto&& it : inputData1)
+    {
+        armnn::BindingPointInfo bindingInfo = ConvertBindingInfo(
+            m_Parser->GetNetworkInputBindingInfo(layersId, it.first));
+        bindingInfo.second.SetConstant(true);
+        armnn::VerifyTensorInfoDataType(bindingInfo.second, ArmnnInputType1);
+        inputTensors.push_back({ bindingInfo.first, armnn::ConstTensor(bindingInfo.second, it.second.data()) });
+    }
+
+    // Allocate storage for the output tensors to be written to and setup the armnn output tensors.
+    std::map<std::string, std::vector<OutputDataType>> outputStorage;
+    armnn::OutputTensors outputTensors;
+    for (auto&& it : expectedOutputData)
+    {
+        armnn::BindingPointInfo bindingInfo = ConvertBindingInfo(
+            m_Parser->GetNetworkOutputBindingInfo(layersId, it.first));
+        armnn::VerifyTensorInfoDataType(bindingInfo.second, ArmnnOutputType);
+        outputStorage.emplace(it.first, std::vector<OutputDataType>(bindingInfo.second.GetNumElements()));
+        outputTensors.push_back(
+            { bindingInfo.first, armnn::Tensor(bindingInfo.second, outputStorage.at(it.first).data()) });
+    }
+
+    m_Runtime->EnqueueWorkload(m_NetworkIdentifier, inputTensors, outputTensors);
+
+    // Compare each output tensor to the expected values
+    for (auto&& it : expectedOutputData)
+    {
+        armnn::BindingPointInfo bindingInfo = ConvertBindingInfo(
+            m_Parser->GetNetworkOutputBindingInfo(layersId, it.first));
+        auto outputExpected = it.second;
+        auto result = CompareTensors(outputExpected, outputStorage[it.first],
+                                     bindingInfo.second.GetShape(), bindingInfo.second.GetShape());
+        CHECK_MESSAGE(result.m_Result, result.m_Message.str());
+    }
+}