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Diffstat (limited to 'src/armnn/test/optimizations/Fp32NetworkToFp16ConverterTests.cpp')
-rw-r--r--src/armnn/test/optimizations/Fp32NetworkToFp16ConverterTests.cpp288
1 files changed, 287 insertions, 1 deletions
diff --git a/src/armnn/test/optimizations/Fp32NetworkToFp16ConverterTests.cpp b/src/armnn/test/optimizations/Fp32NetworkToFp16ConverterTests.cpp
index 0a4a4fafde..90f94bccbf 100644
--- a/src/armnn/test/optimizations/Fp32NetworkToFp16ConverterTests.cpp
+++ b/src/armnn/test/optimizations/Fp32NetworkToFp16ConverterTests.cpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
@@ -7,6 +7,12 @@
#include <Optimizer.hpp>
+#if defined(ARMNNREF_ENABLED)
+#include <CommonTestUtils.hpp>
+#include <GraphUtils.hpp>
+#include <backendsCommon/test/mockBackend/MockImportBackend.hpp>
+#endif
+
#include <doctest/doctest.h>
TEST_SUITE("Optimizer")
@@ -50,4 +56,284 @@ TEST_CASE("Fp32NetworkToFp16OptimizationTest")
CHECK(floor->GetOutputSlot(0).GetTensorInfo().GetDataType() == armnn::DataType::Float16);
}
+#if defined(ARMNNREF_ENABLED)
+TEST_CASE("ReduceFp32ToFp16EnabledBackendHasFp16SupportTest")
+{
+ using namespace armnn;
+ IRuntime::CreationOptions options;
+ IRuntimePtr runtime(IRuntime::Create(options));
+
+ // Builds up the structure of the network.
+ INetworkPtr net(INetwork::Create());
+
+ IConnectableLayer* input0 = net->AddInputLayer(0, "input0");
+ IConnectableLayer* input1 = net->AddInputLayer(1, "input1");
+ IConnectableLayer* input2 = net->AddInputLayer(2, "input2");
+ IConnectableLayer* add = net->AddElementwiseBinaryLayer(BinaryOperation::Add, "add");
+ IConnectableLayer* sub = net->AddElementwiseBinaryLayer(BinaryOperation::Sub, "sub");
+ IConnectableLayer* output = net->AddOutputLayer(0, "output");
+
+ input0->GetOutputSlot(0).Connect(add->GetInputSlot(0));
+ input1->GetOutputSlot(0).Connect(add->GetInputSlot(1));
+ input2->GetOutputSlot(0).Connect(sub->GetInputSlot(0));
+ add->GetOutputSlot(0).Connect(sub->GetInputSlot(1));
+ sub->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+
+ TensorInfo info = TensorInfo({ 1, 2, 4, 2 }, DataType::Float32);
+
+ input0->GetOutputSlot(0).SetTensorInfo(info);
+ input1->GetOutputSlot(0).SetTensorInfo(info);
+ input2->GetOutputSlot(0).SetTensorInfo(info);
+ add->GetOutputSlot(0).SetTensorInfo(info);
+ sub->GetOutputSlot(0).SetTensorInfo(info);
+
+ std::vector<BackendId> backends = { Compute::CpuRef };
+
+ // optimize the network
+ OptimizerOptionsOpaque optOptions;
+ optOptions.SetReduceFp32ToFp16(true);
+ IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec(), optOptions);
+
+ Graph& graph = GetGraphForTesting(optNet.get());
+
+ // Layers are added to convert the inputs to FP16
+ CHECK(CheckSequence(graph.cbegin(), graph.cend(), &IsLayerOfType<armnn::InputLayer>,
+ &IsLayerOfType<armnn::InputLayer>,
+ &IsLayerOfType<armnn::InputLayer>,
+ &IsLayerOfType<armnn::ConvertFp32ToFp16Layer>,
+ &IsLayerOfType<armnn::ConvertFp32ToFp16Layer>,
+ &IsLayerOfType<armnn::ConvertFp32ToFp16Layer>,
+ &IsLayerOfType<armnn::ElementwiseBinaryLayer>,
+ &IsLayerOfType<armnn::ElementwiseBinaryLayer>,
+ &IsLayerOfType<armnn::ConvertFp16ToFp32Layer>,
+ &IsLayerOfType<armnn::OutputLayer>));
+
+ Layer* const addLayer = GetFirstLayerWithName(graph, "add");
+ Layer* const subLayer = GetFirstLayerWithName(graph, "sub");
+
+ CHECK(addLayer->GetDataType() == armnn::DataType::Float16);
+ CHECK(addLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo().GetDataType()
+ == armnn::DataType::Float16);
+ CHECK(addLayer->GetOutputSlot(0).GetTensorInfo().GetDataType() == armnn::DataType::Float16);
+
+ CHECK(subLayer->GetDataType() == armnn::DataType::Float16);
+ CHECK(subLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo().GetDataType()
+ == armnn::DataType::Float16);
+ CHECK(subLayer->GetOutputSlot(0).GetTensorInfo().GetDataType() == armnn::DataType::Float16);
+}
+
+TEST_CASE("ReduceFp32ToFp16EnabledBackendNoFp16SupportTest")
+{
+ using namespace armnn;
+
+ // Create a mock backend without FP16 support
+ MockImportBackendInitialiser initialiser; // Register the Mock Backend
+ auto backendObjPtr = CreateBackendObject(MockImportBackendId());
+ CHECK((backendObjPtr != nullptr));
+
+ BackendIdSet backendIds = BackendRegistryInstance().GetBackendIds();
+ if (backendIds.find("MockRef") == backendIds.end())
+ {
+ std::string message = "Cannot load MockRef";
+ FAIL(message);
+ }
+
+ IRuntime::CreationOptions options;
+ IRuntimePtr runtime(IRuntime::Create(options));
+
+ // Builds up the structure of the network.
+ INetworkPtr net(INetwork::Create());
+
+ IConnectableLayer* input0 = net->AddInputLayer(0, "input0");
+ IConnectableLayer* input1 = net->AddInputLayer(1, "input1");
+ IConnectableLayer* add = net->AddElementwiseBinaryLayer(BinaryOperation::Add, "add");
+ IConnectableLayer* output = net->AddOutputLayer(0, "output");
+
+ input0->GetOutputSlot(0).Connect(add->GetInputSlot(0));
+ input1->GetOutputSlot(0).Connect(add->GetInputSlot(1));
+ add->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+
+ TensorInfo info = TensorInfo({ 1, 2, 4, 2 }, DataType::Float32);
+
+ input0->GetOutputSlot(0).SetTensorInfo(info);
+ input1->GetOutputSlot(0).SetTensorInfo(info);
+ add->GetOutputSlot(0).SetTensorInfo(info);
+
+ std::vector<BackendId> backends = { "MockRef" };
+
+ // optimize the network
+ OptimizerOptionsOpaque optOptions;
+ optOptions.SetReduceFp32ToFp16(true);
+ IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec(), optOptions);
+
+ Graph& graph = GetGraphForTesting(optNet.get());
+
+ // Do not add layers to convert the inputs to FP16
+ CHECK(CheckSequence(graph.cbegin(), graph.cend(), &IsLayerOfType<armnn::InputLayer>,
+ &IsLayerOfType<armnn::InputLayer>,
+ &IsLayerOfType<armnn::ElementwiseBinaryLayer>,
+ &IsLayerOfType<armnn::OutputLayer>));
+
+ // Checks that data type is FP32
+ Layer* const addLayer = GetFirstLayerWithName(graph, "add");
+
+ CHECK(addLayer->GetDataType() == armnn::DataType::Float32);
+ CHECK(addLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo().GetDataType()
+ == armnn::DataType::Float32);
+ CHECK(addLayer->GetOutputSlot(0).GetTensorInfo().GetDataType() == armnn::DataType::Float32);
+}
+
+TEST_CASE("ReduceFp32ToFp16EnabledFirstBackendHasFp16SupportTest")
+{
+ using namespace armnn;
+
+ // Create a mock backend without FP16 support
+ MockImportBackendInitialiser initialiser; // Register the Mock Backend
+ auto backendObjPtr = CreateBackendObject(MockImportBackendId());
+ CHECK((backendObjPtr != nullptr));
+
+ BackendIdSet backendIds = BackendRegistryInstance().GetBackendIds();
+ if (backendIds.find("MockRef") == backendIds.end())
+ {
+ std::string message = "Cannot load MockRef";
+ FAIL(message);
+ }
+ IRuntime::CreationOptions options;
+ IRuntimePtr runtime(IRuntime::Create(options));
+
+ // Builds up the structure of the network.
+ INetworkPtr net(INetwork::Create());
+
+ IConnectableLayer* input0 = net->AddInputLayer(0, "input0");
+ IConnectableLayer* input1 = net->AddInputLayer(1, "input1");
+ IConnectableLayer* input2 = net->AddInputLayer(2, "input2");
+ IConnectableLayer* add = net->AddElementwiseBinaryLayer(BinaryOperation::Add, "add");
+ IConnectableLayer* sub = net->AddElementwiseBinaryLayer(BinaryOperation::Sub, "sub");
+ IConnectableLayer* output = net->AddOutputLayer(0, "output");
+
+ input0->GetOutputSlot(0).Connect(add->GetInputSlot(0));
+ input1->GetOutputSlot(0).Connect(add->GetInputSlot(1));
+ input2->GetOutputSlot(0).Connect(sub->GetInputSlot(0));
+ add->GetOutputSlot(0).Connect(sub->GetInputSlot(1));
+ sub->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+
+ TensorInfo info = TensorInfo({ 1, 2, 4, 2 }, DataType::Float32);
+
+ input0->GetOutputSlot(0).SetTensorInfo(info);
+ input1->GetOutputSlot(0).SetTensorInfo(info);
+ input2->GetOutputSlot(0).SetTensorInfo(info);
+ add->GetOutputSlot(0).SetTensorInfo(info);
+ sub->GetOutputSlot(0).SetTensorInfo(info);
+
+ std::vector<BackendId> backends = { Compute::CpuRef, "MockRef" };
+
+ // optimize the network
+ OptimizerOptionsOpaque optOptions;
+ optOptions.SetReduceFp32ToFp16(true);
+ IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec(), optOptions);
+
+ Graph& graph = GetGraphForTesting(optNet.get());
+
+ // Layers are added to convert the inputs to FP16
+ CHECK(CheckSequence(graph.cbegin(), graph.cend(), &IsLayerOfType<armnn::InputLayer>,
+ &IsLayerOfType<armnn::InputLayer>,
+ &IsLayerOfType<armnn::InputLayer>,
+ &IsLayerOfType<armnn::ConvertFp32ToFp16Layer>,
+ &IsLayerOfType<armnn::ConvertFp32ToFp16Layer>,
+ &IsLayerOfType<armnn::ConvertFp32ToFp16Layer>,
+ &IsLayerOfType<armnn::ElementwiseBinaryLayer>,
+ &IsLayerOfType<armnn::ElementwiseBinaryLayer>,
+ &IsLayerOfType<armnn::ConvertFp16ToFp32Layer>,
+ &IsLayerOfType<armnn::OutputLayer>));
+
+ Layer* const addLayer = GetFirstLayerWithName(graph, "add");
+ Layer* const subLayer = GetFirstLayerWithName(graph, "sub");
+
+ CHECK(addLayer->GetDataType() == armnn::DataType::Float16);
+ CHECK(addLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo().GetDataType()
+ == armnn::DataType::Float16);
+ CHECK(addLayer->GetOutputSlot(0).GetTensorInfo().GetDataType() == armnn::DataType::Float16);
+
+ CHECK(subLayer->GetDataType() == armnn::DataType::Float16);
+ CHECK(subLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo().GetDataType()
+ == armnn::DataType::Float16);
+ CHECK(subLayer->GetOutputSlot(0).GetTensorInfo().GetDataType() == armnn::DataType::Float16);
+}
+
+TEST_CASE("ReduceFp32ToFp16EnabledFirstBackendNoFp16SupportTest")
+{
+ using namespace armnn;
+
+ // Create a mock backend without FP16 support
+ MockImportBackendInitialiser initialiser; // Register the Mock Backend
+ auto backendObjPtr = CreateBackendObject(MockImportBackendId());
+ CHECK((backendObjPtr != nullptr));
+
+ BackendIdSet backendIds = BackendRegistryInstance().GetBackendIds();
+ if (backendIds.find("MockRef") == backendIds.end())
+ {
+ std::string message = "Cannot load MockRef";
+ FAIL(message);
+ }
+
+ IRuntime::CreationOptions options;
+ IRuntimePtr runtime(IRuntime::Create(options));
+
+ // Builds up the structure of the network.
+ INetworkPtr net(INetwork::Create());
+
+ IConnectableLayer* input0 = net->AddInputLayer(0, "input0");
+ IConnectableLayer* input1 = net->AddInputLayer(1, "input1");
+ IConnectableLayer* input2 = net->AddInputLayer(2, "input2");
+ IConnectableLayer* add = net->AddElementwiseBinaryLayer(BinaryOperation::Add, "add");
+ IConnectableLayer* sub = net->AddElementwiseBinaryLayer(BinaryOperation::Sub, "sub");
+ IConnectableLayer* output = net->AddOutputLayer(0, "output");
+
+ input0->GetOutputSlot(0).Connect(add->GetInputSlot(0));
+ input1->GetOutputSlot(0).Connect(add->GetInputSlot(1));
+ input2->GetOutputSlot(0).Connect(sub->GetInputSlot(0));
+ add->GetOutputSlot(0).Connect(sub->GetInputSlot(1));
+ sub->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+
+ TensorInfo info = TensorInfo({ 1, 2, 4, 2 }, DataType::Float32);
+
+ input0->GetOutputSlot(0).SetTensorInfo(info);
+ input1->GetOutputSlot(0).SetTensorInfo(info);
+ input2->GetOutputSlot(0).SetTensorInfo(info);
+ add->GetOutputSlot(0).SetTensorInfo(info);
+ sub->GetOutputSlot(0).SetTensorInfo(info);
+
+ std::vector<BackendId> backends = { "MockRef", Compute::CpuRef };
+
+ // optimize the network
+ OptimizerOptionsOpaque optOptions;
+ optOptions.SetReduceFp32ToFp16(true);
+ IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec(), optOptions);
+
+ Graph& graph = GetGraphForTesting(optNet.get());
+
+ // Do not add layers to convert the inputs to FP16
+ CHECK(CheckSequence(graph.cbegin(), graph.cend(), &IsLayerOfType<armnn::InputLayer>,
+ &IsLayerOfType<armnn::InputLayer>,
+ &IsLayerOfType<armnn::InputLayer>,
+ &IsLayerOfType<armnn::ElementwiseBinaryLayer>,
+ &IsLayerOfType<armnn::ElementwiseBinaryLayer>,
+ &IsLayerOfType<armnn::OutputLayer>));
+
+ // Checks that data type is FP32
+ Layer* const addLayer = GetFirstLayerWithName(graph, "add");
+ Layer* const subLayer = GetFirstLayerWithName(graph, "sub");
+
+ CHECK(addLayer->GetDataType() == armnn::DataType::Float32);
+ CHECK(addLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo().GetDataType()
+ == armnn::DataType::Float32);
+ CHECK(addLayer->GetOutputSlot(0).GetTensorInfo().GetDataType() == armnn::DataType::Float32);
+
+ CHECK(subLayer->GetDataType() == armnn::DataType::Float32);
+ CHECK(subLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo().GetDataType()
+ == armnn::DataType::Float32);
+ CHECK(subLayer->GetOutputSlot(0).GetTensorInfo().GetDataType() == armnn::DataType::Float32);
+}
+#endif // ARMNNREF_ENABLED
+
} \ No newline at end of file
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-01 03:30:36 +0000