IVGCVSW-7170 Add Concat support to TOSA Reference Backend
* Change comment for the unique tensor names in all tosa common operators
Signed-off-by: Kevin May <kevin.may@arm.com>
Change-Id: I247b4b2365d5f0173218c5dfd11fba12d2399959
diff --git a/src/backends/backendsCommon/test/ConcatEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/ConcatEndToEndTestImpl.hpp
index c8d20da..2614523 100644
--- a/src/backends/backendsCommon/test/ConcatEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/ConcatEndToEndTestImpl.hpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2017,2022 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
@@ -112,7 +112,7 @@
std::map<int, std::vector<T>> inputTensorData = {{ 0,inputData }, { 1,inputData }};
std::map<int, std::vector<T>> expectedOutputData = {{ 0,expectedOutput }};
- EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends);
+ EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(net), inputTensorData, expectedOutputData, backends);
}
template<armnn::DataType ArmnnType>
@@ -174,7 +174,7 @@
std::map<int, std::vector<T>> inputTensorData = {{ 0,inputData }, { 1,inputData }};
std::map<int, std::vector<T>> expectedOutputData = {{ 0,expectedOutput }};
- EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends);
+ EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(net), inputTensorData, expectedOutputData, backends);
}
template<armnn::DataType ArmnnType>
@@ -236,7 +236,7 @@
std::map<int, std::vector<T>> inputTensorData = {{ 0,inputData }, { 1,inputData }};
std::map<int, std::vector<T>> expectedOutputData = {{ 0,expectedOutput }};
- EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends);
+ EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(net), inputTensorData, expectedOutputData, backends);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
@@ -297,7 +297,7 @@
std::map<int, std::vector<T>> inputTensorData = {{ 0,inputData }, { 1,inputData }};
std::map<int, std::vector<T>> expectedOutputData = {{ 0,expectedOutput }};
- EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends);
+ EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(net), inputTensorData, expectedOutputData, backends);
}
} // anonymous namespace
diff --git a/src/backends/tosaCommon/TosaMappings.cpp b/src/backends/tosaCommon/TosaMappings.cpp
index 7ecf726..1452e4a 100644
--- a/src/backends/tosaCommon/TosaMappings.cpp
+++ b/src/backends/tosaCommon/TosaMappings.cpp
@@ -27,6 +27,11 @@
{
return ConvertAdditionToTosaOperator(layer, inputs, outputs);
}
+ case LayerType::Concat:
+ {
+ auto concatDesc = PolymorphicDowncast<const OriginsDescriptor*>(&descriptor);
+ return ConvertConcatToTosaOperator(layer, inputs, outputs, concatDesc);
+ }
case LayerType::Constant:
{
return ConvertConstantToTosaOperator(layer, outputs);
diff --git a/src/backends/tosaCommon/operatorMappings/AdditionOperator.cpp b/src/backends/tosaCommon/operatorMappings/AdditionOperator.cpp
index 20ba146..7014886 100644
--- a/src/backends/tosaCommon/operatorMappings/AdditionOperator.cpp
+++ b/src/backends/tosaCommon/operatorMappings/AdditionOperator.cpp
@@ -18,14 +18,14 @@
// using the previous and following layers so the graph is connected correctly. For validation this doesn't matter.
if(layer != nullptr)
{
- // Get the layers connected to the input slots and determine unique layer names.
+ // Get the layers connected to the input slots and determine unique tensors names.
Layer& connectedLayer0 = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer();
input0Name = GenerateUniqueName(connectedLayer0, 0);
Layer& connectedLayer1 = layer->GetInputSlot(1).GetConnectedOutputSlot()->GetOwningLayer();
input1Name = GenerateUniqueName(connectedLayer1, 1);
- // Get the layer connected to the output slot and determine unique layer name.
+ // Determine unique output tensor name.
outputName = GenerateUniqueOutputName(*layer, 0);
}
diff --git a/src/backends/tosaCommon/operatorMappings/AvgPool2DIgnoreValueOperator.cpp b/src/backends/tosaCommon/operatorMappings/AvgPool2DIgnoreValueOperator.cpp
index d268c2f..61de0ae 100644
--- a/src/backends/tosaCommon/operatorMappings/AvgPool2DIgnoreValueOperator.cpp
+++ b/src/backends/tosaCommon/operatorMappings/AvgPool2DIgnoreValueOperator.cpp
@@ -19,11 +19,11 @@
// using the previous and following layers so the graph is connected correctly. For validation this doesn't matter.
if(layer != nullptr)
{
- // Get the layers connected to the input slots and determine unique layer names.
+ // Get the layers connected to the input slots and determine unique tensors names.
Layer& connectedInputLayer = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer();
padInputName = GenerateUniqueName(connectedInputLayer, 0);
- // Get the layer connected to the output slot and determine unique layer name.
+ // Determine unique output tensor name.
poolOutputName = GenerateUniqueOutputName(*layer, 0);
}
diff --git a/src/backends/tosaCommon/operatorMappings/CMakeLists.txt b/src/backends/tosaCommon/operatorMappings/CMakeLists.txt
index 90c1a4f..2443dc0 100644
--- a/src/backends/tosaCommon/operatorMappings/CMakeLists.txt
+++ b/src/backends/tosaCommon/operatorMappings/CMakeLists.txt
@@ -8,6 +8,8 @@
AdditionOperator.cpp
AvgPool2DIgnoreValueOperator.hpp
AvgPool2DIgnoreValueOperator.cpp
+ ConcatOperator.hpp
+ ConcatOperator.cpp
ConstantOperator.hpp
ConstantOperator.cpp
Conv2dOperator.hpp
diff --git a/src/backends/tosaCommon/operatorMappings/ConcatOperator.cpp b/src/backends/tosaCommon/operatorMappings/ConcatOperator.cpp
new file mode 100644
index 0000000..8c651be
--- /dev/null
+++ b/src/backends/tosaCommon/operatorMappings/ConcatOperator.cpp
@@ -0,0 +1,81 @@
+//
+// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ConcatOperator.hpp"
+
+TosaSerializationBasicBlock* ConvertConcatToTosaOperator(const Layer* layer,
+ const std::vector<const TensorInfo*>& inputs,
+ const std::vector<const TensorInfo*>& outputs,
+ const OriginsDescriptor* concatDescriptor)
+{
+ auto numInputs = inputs.size();
+ std::vector<std::string> inputNames;
+ inputNames.reserve(numInputs);
+ std::string outputName = std::string("output0_");
+ std::string blockName = std::string("Op_CONCAT_block_") + GetUniqueTosaMappingID();
+
+ // Set input names for validation purposes only.
+ if (layer == nullptr)
+ {
+ for (uint32_t i = 0; i < numInputs; ++i)
+ {
+ inputNames.push_back("input"+ std::to_string(i) +"_");
+ }
+ }
+ // If a layer is present then the block will be used for execution, so input and output names need to be determined
+ // using the previous and following layers so the graph is connected correctly. For validation this doesn't matter.
+ else
+ {
+ // Get the layers connected to the input slots and determine unique tensor names.
+ for (uint32_t i = 0; i < numInputs; ++i)
+ {
+ Layer& connectedLayer = layer->GetInputSlot(i).GetConnectedOutputSlot()->GetOwningLayer();
+
+ std::string inputName = GenerateUniqueName(connectedLayer, i);
+ inputNames.push_back(inputName);
+ }
+
+ // Determine unique output tensor name.
+ outputName = GenerateUniqueOutputName(*layer, 0);
+ }
+
+ auto axis = static_cast<int32_t>(concatDescriptor->GetConcatAxis());
+ TosaAxisAttribute attribute(axis);
+
+ TosaSerializationOperator* op = new TosaSerializationOperator(Op_CONCAT,
+ Attribute_AxisAttribute,
+ &attribute,
+ inputNames,
+ {outputName});
+
+ std::vector<TosaSerializationTensor*> tensors;
+ tensors.reserve(numInputs);
+
+ for (uint32_t i = 0; i < numInputs; ++i)
+ {
+ // Only add input tensors for validation or when the connected layer is an input layer.
+ // As there can't be duplicate tensors and intermediate or constant tensors are created separately.
+ if(inputNames[i].find("input") != std::string::npos)
+ {
+ std::vector<int32_t> inputShape = GetTosaTensorShape(inputs[i]->GetShape());
+ DType inputDType = ArmNNToDType(inputs[i]->GetDataType());
+ tensors.push_back(new TosaSerializationTensor(inputNames[i], inputShape, inputDType, {}));
+ }
+ }
+
+ std::vector<int32_t> outputShape0 = GetTosaTensorShape(outputs[0]->GetShape());
+ DType outputDType0 = ArmNNToDType(outputs[0]->GetDataType());
+
+ TosaSerializationTensor* outputTensor0 = new TosaSerializationTensor(outputName, outputShape0, outputDType0, {});
+ tensors.push_back(outputTensor0);
+
+ // operatorInputNames/operatorOutputNames ends up being the same as
+ // blockInputNames/blockOutputNames for one-to-one ArmNN to TOSA mappings
+ return new TosaSerializationBasicBlock(blockName, // name
+ {op}, // operators
+ tensors, // tensors
+ inputNames, // inputs
+ {outputName}); // outputs
+}
\ No newline at end of file
diff --git a/src/backends/tosaCommon/operatorMappings/ConcatOperator.hpp b/src/backends/tosaCommon/operatorMappings/ConcatOperator.hpp
new file mode 100644
index 0000000..e6094ce
--- /dev/null
+++ b/src/backends/tosaCommon/operatorMappings/ConcatOperator.hpp
@@ -0,0 +1,20 @@
+//
+// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <Layer.hpp>
+
+#include <tosa_serialization_handler.h>
+
+#include "TosaOperatorUtils.hpp"
+
+using namespace armnn;
+using namespace tosa;
+
+TosaSerializationBasicBlock* ConvertConcatToTosaOperator(const Layer* layer,
+ const std::vector<const TensorInfo*>& inputs,
+ const std::vector<const TensorInfo*>& outputs,
+ const OriginsDescriptor* concatDescriptor);
diff --git a/src/backends/tosaCommon/operatorMappings/Conv2dOperator.cpp b/src/backends/tosaCommon/operatorMappings/Conv2dOperator.cpp
index 6fc1678..a7af083 100644
--- a/src/backends/tosaCommon/operatorMappings/Conv2dOperator.cpp
+++ b/src/backends/tosaCommon/operatorMappings/Conv2dOperator.cpp
@@ -24,21 +24,21 @@
inputNames.emplace_back("input2_");
}
}
+ // If a layer is present then the block will be used for execution, so input and output names need to be
+ // determined using the previous and following layers so the graph is connected correctly.
+ // For validation this doesn't matter.
else
{
- // If a layer is present then the block will be used for execution, so input and output names need to be
- // determined using the previous and following layers so the graph is connected correctly.
- // For validation this doesn't matter.
+ // Get the layer connected to the input slot and determine unique tensor names.
for (uint32_t i = 0; i < inputs.size(); ++i)
{
- // Get the layer connected to the input slot and determine unique layer name.
Layer& connectedLayer = layer->GetInputSlot(i).GetConnectedOutputSlot()->GetOwningLayer();
std::string inputName = GenerateUniqueName(connectedLayer, i);
inputNames.push_back(inputName);
}
- // Get the layer connected to the output slot and determine unique layer name.
+ // Determine unique output tensor name.
outputName = GenerateUniqueOutputName(*layer, 0);
}
diff --git a/src/backends/tosaCommon/operatorMappings/Pooling2DOperator.cpp b/src/backends/tosaCommon/operatorMappings/Pooling2DOperator.cpp
index ee02425..444d99a 100644
--- a/src/backends/tosaCommon/operatorMappings/Pooling2DOperator.cpp
+++ b/src/backends/tosaCommon/operatorMappings/Pooling2DOperator.cpp
@@ -21,11 +21,11 @@
// using the previous and following layers so the graph is connected correctly. For validation this doesn't matter.
if(layer != nullptr)
{
- // Get the layers connected to the input slots and determine unique layer names.
+ // Get the layers connected to the input slots and determine unique tensor names.
Layer& connectedInputLayer = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer();
input0Name = GenerateUniqueName(connectedInputLayer, 0);
- // Get the layer connected to the output slot and determine unique layer name.
+ // Determine unique output tensor name.
outputName = GenerateUniqueOutputName(*layer, 0);
}
diff --git a/src/backends/tosaCommon/operatorMappings/ReshapeOperator.cpp b/src/backends/tosaCommon/operatorMappings/ReshapeOperator.cpp
index 3027e2e..10670ec 100644
--- a/src/backends/tosaCommon/operatorMappings/ReshapeOperator.cpp
+++ b/src/backends/tosaCommon/operatorMappings/ReshapeOperator.cpp
@@ -18,11 +18,11 @@
// using the previous and following layers so the graph is connected correctly. For validation this doesn't matter.
if(layer != nullptr)
{
- // Get the layers connected to the input slots and determine unique layer names.
+ // Get the layers connected to the input slots and determine unique tensor names.
Layer& connectedLayer = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer();
inputName = GenerateUniqueName(connectedLayer, 0);
- // Get the layer connected to the output slot and determine unique layer name.
+ // Determine unique output tensor name.
outputName = GenerateUniqueOutputName(*layer, 0);
}
diff --git a/src/backends/tosaCommon/operatorMappings/SliceOperator.cpp b/src/backends/tosaCommon/operatorMappings/SliceOperator.cpp
index 742ba88..b98576f 100644
--- a/src/backends/tosaCommon/operatorMappings/SliceOperator.cpp
+++ b/src/backends/tosaCommon/operatorMappings/SliceOperator.cpp
@@ -18,11 +18,11 @@
// using the previous and following layers so the graph is connected correctly. For validation this doesn't matter.
if(layer != nullptr)
{
- // Get the layers connected to the input slots and determine unique layer names.
+ // Get the layers connected to the input slots and determine unique tensor names.
Layer& connectedLayer = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer();
inputName = GenerateUniqueName(connectedLayer, 0);
- // Get the layer connected to the output slot and determine unique layer name.
+ // Determine unique output tensor name.
outputName = GenerateUniqueOutputName(*layer, 0);
}
diff --git a/src/backends/tosaCommon/operatorMappings/TosaCommonOperators.hpp b/src/backends/tosaCommon/operatorMappings/TosaCommonOperators.hpp
index 1a9d6be..052c54c 100644
--- a/src/backends/tosaCommon/operatorMappings/TosaCommonOperators.hpp
+++ b/src/backends/tosaCommon/operatorMappings/TosaCommonOperators.hpp
@@ -6,6 +6,7 @@
#pragma once
#include "AdditionOperator.hpp"
+#include "ConcatOperator.hpp"
#include "ConstantOperator.hpp"
#include "Conv2dOperator.hpp"
#include "AvgPool2DIgnoreValueOperator.hpp"
diff --git a/src/backends/tosaCommon/operatorMappings/TransposeConv2dOperator.cpp b/src/backends/tosaCommon/operatorMappings/TransposeConv2dOperator.cpp
index 1ad8c95..c8af5c2 100644
--- a/src/backends/tosaCommon/operatorMappings/TransposeConv2dOperator.cpp
+++ b/src/backends/tosaCommon/operatorMappings/TransposeConv2dOperator.cpp
@@ -22,9 +22,11 @@
// using the previous and following layers so the graph is connected correctly. For validation this doesn't matter.
if(layer != nullptr)
{
+ // Get the layers connected to the input slots and determine unique tensor names.
Layer& connectedInputLayer = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer();
input0Name = GenerateUniqueName(connectedInputLayer, 0);
+ // Determine unique output tensor name.
outputName = GenerateUniqueOutputName(*layer, 0);
}
diff --git a/src/backends/tosaCommon/test/OneToOneMappingTests.cpp b/src/backends/tosaCommon/test/OneToOneMappingTests.cpp
index e74c638..b3ab14a 100644
--- a/src/backends/tosaCommon/test/OneToOneMappingTests.cpp
+++ b/src/backends/tosaCommon/test/OneToOneMappingTests.cpp
@@ -56,6 +56,82 @@
basicBlock, inputShape, outputShape, Op_ADD, Attribute_NONE, BaseDescriptor(), LayerType::Addition);
}
+TEST_CASE("GetTosaMapping_ConcatLayer")
+{
+ std::vector<armnn::TensorShape> inputTensorShapes = { { 2, 3, 2, 2 }, { 2, 3, 2, 2 } };
+ armnn::TensorInfo input0Info(inputTensorShapes[0], DataType::Float32);
+ armnn::TensorInfo input1Info(inputTensorShapes[1], DataType::Float32);
+ armnn::TensorInfo outputInfo({ 2, 6, 2, 2 }, DataType::Float32);
+
+ armnn::OriginsDescriptor descriptor;
+ unsigned int concatAxis = 1;
+ descriptor.SetConcatAxis(concatAxis);
+ descriptor = armnn::CreateDescriptorForConcatenation(inputTensorShapes.begin(),
+ inputTensorShapes.end(),
+ concatAxis);
+
+ TosaSerializationBasicBlock* basicBlock =
+ GetTosaMapping(nullptr, LayerType::Concat, {&input0Info,&input1Info}, {&outputInfo}, descriptor);
+
+ std::vector<std::vector<int32_t>> inputShapes = { { 2, 3, 2, 2 }, { 2, 3, 2, 2 }};
+ std::vector<std::vector<int32_t>> outputShape = { { 2, 6, 2, 2 } };
+
+ AssertTosaOneToOneMappingBasicBlock(basicBlock,
+ inputShapes,
+ outputShape,
+ Op_CONCAT,
+ Attribute_AxisAttribute,
+ descriptor,
+ LayerType::Concat);
+}
+
+TEST_CASE("GetTosaMappingFromLayer_ConcatLayer")
+{
+ IRuntime::CreationOptions options;
+ IRuntimePtr runtime(IRuntime::Create(options));
+
+ // Builds up the structure of the network.
+ INetworkPtr net(INetwork::Create());
+
+ armnn::OriginsDescriptor descriptor;
+ unsigned int concatAxis = 1;
+ descriptor.SetConcatAxis(concatAxis);
+ std::vector<armnn::TensorShape> inputTensorShapes = { { 2, 3, 2, 2 }, { 2, 3, 2, 2 } };
+ descriptor = armnn::CreateDescriptorForConcatenation(inputTensorShapes.begin(),
+ inputTensorShapes.end(),
+ concatAxis);
+
+ IConnectableLayer* input0 = net->AddInputLayer(0, "input0");
+ IConnectableLayer* input1 = net->AddInputLayer(1, "input1");
+ IConnectableLayer* concat = net->AddConcatLayer(descriptor, "concat");
+ IConnectableLayer* output = net->AddOutputLayer(0, "output");
+
+ input0->GetOutputSlot(0).Connect(concat->GetInputSlot(0));
+ input1->GetOutputSlot(0).Connect(concat->GetInputSlot(1));
+ concat->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+
+
+ TensorInfo inputInfo0 = TensorInfo(inputTensorShapes[0], DataType::Float32, 0.0f, 0, true);
+ TensorInfo inputInfo1 = TensorInfo(inputTensorShapes[1], DataType::Float32, 0.0f, 0, true);
+ armnn::TensorInfo outputInfo({ 2, 6, 2, 2 }, DataType::Float32);
+
+ input0->GetOutputSlot(0).SetTensorInfo(inputInfo0);
+ input1->GetOutputSlot(0).SetTensorInfo(inputInfo1);
+ concat->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+ std::vector<std::vector<int32_t>> inputShapes = { { 2, 3, 2, 2 }, { 2, 3, 2, 2 }};
+ std::vector<std::vector<int32_t>> outputShape = { { 2, 6, 2, 2 } };
+
+ TosaSerializationBasicBlock* basicBlock = GetTosaMappingFromLayer(PolymorphicDowncast<Layer*>(concat));
+ AssertTosaOneToOneMappingBasicBlock(basicBlock,
+ inputShapes,
+ outputShape,
+ Op_CONCAT,
+ Attribute_AxisAttribute,
+ descriptor,
+ LayerType::Concat);
+}
+
TEST_CASE("GetTosaMapping_ConstantLayer")
{
TensorInfo outputInfo = TensorInfo({ 1, 2, 4, 2 }, DataType::Float32, 0.0f, 0, true);
diff --git a/src/backends/tosaReference/TosaRefLayerSupport.cpp b/src/backends/tosaReference/TosaRefLayerSupport.cpp
index e5427eb..0d0d07a 100644
--- a/src/backends/tosaReference/TosaRefLayerSupport.cpp
+++ b/src/backends/tosaReference/TosaRefLayerSupport.cpp
@@ -43,6 +43,13 @@
inputInfos.push_back(&infos[1]);
outputInfos.push_back(&infos[2]);
break;
+ case LayerType::Concat:
+ for (unsigned int i = 0; i < infos.size() - 1; ++i)
+ {
+ inputInfos.push_back(&infos[i]);
+ }
+ outputInfos.push_back(&infos.back());
+ break;
case LayerType::Constant:
outputInfos.push_back(&infos[0]);
break;
diff --git a/src/backends/tosaReference/test/TosaRefEndToEndTests.cpp b/src/backends/tosaReference/test/TosaRefEndToEndTests.cpp
index 49f2cb7..a377293 100644
--- a/src/backends/tosaReference/test/TosaRefEndToEndTests.cpp
+++ b/src/backends/tosaReference/test/TosaRefEndToEndTests.cpp
@@ -7,6 +7,7 @@
#include "backendsCommon/test/AdditionEndToEndTestImpl.hpp"
#include "backendsCommon/test/Convolution2dEndToEndTestImpl.hpp"
+#include "backendsCommon/test/ConcatEndToEndTestImpl.hpp"
#include "backendsCommon/test/Pooling2dEndToEndTestImpl.hpp"
#include "backendsCommon/test/ReshapeEndToEndTestImpl.hpp"
#include "backendsCommon/test/SliceEndToEndTestImpl.hpp"
@@ -34,6 +35,47 @@
AdditionEndToEndFloat16<DataType::Float16>(tosaDefaultBackends);
}
+// Concat
+TEST_CASE("TosaRefConcatEndToEndDim0TestFloat32")
+{
+ ConcatDim0EndToEnd<armnn::DataType::Float32>(tosaDefaultBackends);
+}
+
+TEST_CASE("TosaRefConcatEndToEndDim0TestInt32")
+{
+ ConcatDim0EndToEnd<armnn::DataType::Signed32>(tosaDefaultBackends);
+}
+
+TEST_CASE("TosaRefConcatEndToEndDim1TestFloat32")
+{
+ ConcatDim1EndToEnd<armnn::DataType::Float32>(tosaDefaultBackends);
+}
+
+TEST_CASE("TosaRefConcatEndToEndDim1TestInt32")
+{
+ ConcatDim1EndToEnd<armnn::DataType::Signed32>(tosaDefaultBackends);
+}
+
+TEST_CASE("TosaRefConcatEndToEndDim2TestFloat32")
+{
+ ConcatDim2EndToEnd<armnn::DataType::Float32>(tosaDefaultBackends);
+}
+
+TEST_CASE("TosaRefConcatEndToEndDim2TestInt32")
+{
+ ConcatDim2EndToEnd<armnn::DataType::Signed32>(tosaDefaultBackends);
+}
+
+TEST_CASE("TosaRefConcatEndToEndDim3TestFloat32")
+{
+ ConcatDim3EndToEnd<armnn::DataType::Float32>(tosaDefaultBackends);
+}
+
+TEST_CASE("TosaRefConcatEndToEndDim3TestInt32")
+{
+ ConcatDim3EndToEnd<armnn::DataType::Signed32>(tosaDefaultBackends);
+}
+
// Conv2d
TEST_CASE("TosaRefConv2dEndtoEndTestFloat32")
{
diff --git a/src/backends/tosaReference/test/TosaRefLayerSupportTests.cpp b/src/backends/tosaReference/test/TosaRefLayerSupportTests.cpp
index 3c3abc2..051965f 100644
--- a/src/backends/tosaReference/test/TosaRefLayerSupportTests.cpp
+++ b/src/backends/tosaReference/test/TosaRefLayerSupportTests.cpp
@@ -61,6 +61,58 @@
CHECK(!supported);
}
+TEST_CASE("IsLayerSupportedTosaReferenceConcat")
+{
+ TensorShape input0Shape = { 2, 3, 2, 2 };
+ TensorShape input1Shape = { 2, 3, 2, 2 };
+ TensorShape outputShape = { 2, 6, 2, 2 };
+ TensorInfo input0Info(input0Shape, DataType::Float32);
+ TensorInfo input1Info(input1Shape, DataType::Float32);
+ TensorInfo outputInfo(outputShape, DataType::Float32);
+
+ OriginsDescriptor descriptor;
+ std::vector<TensorShape> shapes = {input0Shape, input1Shape} ;
+ unsigned int concatAxis = 1;
+ descriptor = CreateDescriptorForConcatenation(shapes.begin(), shapes.end(), concatAxis);
+
+ TosaRefLayerSupport supportChecker;
+ std::string reasonIfNotSupported;
+ auto supported = supportChecker.IsLayerSupported(LayerType::Concat,
+ {input0Info, input1Info, outputInfo},
+ descriptor,
+ EmptyOptional(),
+ EmptyOptional(),
+ reasonIfNotSupported);
+
+ CHECK(supported);
+}
+
+TEST_CASE("IsLayerSupportedTosaReferenceConcatUnsupported")
+{
+ TensorShape input0Shape = { 2, 3, 2, 2 };
+ TensorShape input1Shape = { 2, 3, 2, 2 };
+ TensorShape outputShape = { 2, 6, 2, 2 };
+ TensorInfo input0Info(input0Shape, armnn::DataType::QAsymmU8);
+ TensorInfo input1Info(input1Shape, armnn::DataType::QAsymmU8);
+ TensorInfo outputInfo(outputShape, armnn::DataType::QAsymmU8);
+
+ OriginsDescriptor descriptor;
+ std::vector<armnn::TensorShape> shapes = {input0Shape, input1Shape} ;
+ unsigned int concatAxis = 1;
+ descriptor = armnn::CreateDescriptorForConcatenation(shapes.begin(), shapes.end(), concatAxis);
+
+ TosaRefLayerSupport supportChecker;
+ std::string reasonIfNotSupported;
+ auto supported = supportChecker.IsLayerSupported(LayerType::Concat,
+ {input0Info, input1Info, outputInfo},
+ descriptor,
+ EmptyOptional(),
+ EmptyOptional(),
+ reasonIfNotSupported);
+
+ CHECK(!supported);
+}
+
TEST_CASE("IsLayerSupportedTosaReferenceConstant")
{
TensorInfo outputInfo({1,1,3,4}, DataType::Float32);