IVGCVSW-8118 Added Two-Layer and Three-Layer Maxpool2d EndToEnd tests.
Signed-off-by: Tianle Cheng <tianle.cheng@arm.com>
Change-Id: I4d04fef5ce97901cd687e29adf86b18cb54a5d9a
diff --git a/src/backends/backendsCommon/test/Pooling2dEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/Pooling2dEndToEndTestImpl.hpp
index 026dbfd..7a264e1 100644
--- a/src/backends/backendsCommon/test/Pooling2dEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/Pooling2dEndToEndTestImpl.hpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2022-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
@@ -169,4 +169,126 @@
0.00001f);
}
+template<typename armnn::DataType DataType>
+armnn::INetworkPtr CreateTwoLayerPooling2dNetwork(const armnn::TensorShape& inputShape,
+ const armnn::TensorShape& outputShape,
+ PaddingMethod padMethod = PaddingMethod::Exclude,
+ PoolingAlgorithm poolAlg = PoolingAlgorithm::Max,
+ const float qScale = 1.0f,
+ const int32_t qOffset = 0)
+{
+ INetworkPtr network(INetwork::Create());
+
+ TensorInfo inputTensorInfo(inputShape, DataType, qScale, qOffset, true);
+ TensorInfo outputTensorInfo(outputShape, DataType, qScale, qOffset, true);
+
+ Pooling2dDescriptor descriptor;
+ descriptor.m_PoolType = poolAlg;
+ descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3;
+ descriptor.m_StrideX = descriptor.m_StrideY = 1;
+ descriptor.m_PadLeft = 1;
+ descriptor.m_PadRight = 1;
+ descriptor.m_PadTop = 1;
+ descriptor.m_PadBottom = 1;
+ descriptor.m_PaddingMethod = padMethod;
+ descriptor.m_DataLayout = DataLayout::NHWC;
+
+ IConnectableLayer* input = network->AddInputLayer(0, "input");
+ IConnectableLayer* pool1 = network->AddPooling2dLayer(descriptor, "pool_1");
+ IConnectableLayer* pool2 = network->AddPooling2dLayer(descriptor, "pool_2");
+ IConnectableLayer* output = network->AddOutputLayer(0, "output");
+
+ Connect(input, pool1, inputTensorInfo, 0, 0);
+ Connect(pool1, pool2, inputTensorInfo, 0, 0);
+ Connect(pool2, output, outputTensorInfo, 0, 0);
+
+ return network;
+}
+
+template<typename armnn::DataType DataType>
+armnn::INetworkPtr CreateThreeLayerPooling2dNetwork(const armnn::TensorShape& inputShape,
+ const armnn::TensorShape& outputShape,
+ PaddingMethod padMethod = PaddingMethod::Exclude,
+ PoolingAlgorithm poolAlg = PoolingAlgorithm::Max,
+ const float qScale = 1.0f,
+ const int32_t qOffset = 0)
+{
+ INetworkPtr network(INetwork::Create());
+
+ TensorInfo inputTensorInfo(inputShape, DataType, qScale, qOffset, true);
+ TensorInfo outputTensorInfo(outputShape, DataType, qScale, qOffset, true);
+
+ Pooling2dDescriptor descriptor;
+ descriptor.m_PoolType = poolAlg;
+ descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3;
+ descriptor.m_StrideX = descriptor.m_StrideY = 1;
+ descriptor.m_PadLeft = 1;
+ descriptor.m_PadRight = 1;
+ descriptor.m_PadTop = 1;
+ descriptor.m_PadBottom = 1;
+ descriptor.m_PaddingMethod = padMethod;
+ descriptor.m_DataLayout = DataLayout::NHWC;
+
+ IConnectableLayer* input = network->AddInputLayer(0, "input");
+ IConnectableLayer* pool1 = network->AddPooling2dLayer(descriptor, "pool_1");
+ IConnectableLayer* pool2 = network->AddPooling2dLayer(descriptor, "pool_2");
+ IConnectableLayer* pool3 = network->AddPooling2dLayer(descriptor, "pool_3");
+ IConnectableLayer* output = network->AddOutputLayer(0, "output");
+
+ Connect(input, pool1, inputTensorInfo, 0, 0);
+ Connect(pool1, pool2, inputTensorInfo, 0, 0);
+ Connect(pool2, pool3, inputTensorInfo, 0, 0);
+ Connect(pool3, output, outputTensorInfo, 0, 0);
+
+ return network;
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+void MaxPool2dTwoLayerEndToEnd(const std::vector<armnn::BackendId>& backends,
+ PaddingMethod padMethod = PaddingMethod::Exclude)
+{
+ const TensorShape& inputShape = { 1, 3, 3, 1 };
+ const TensorShape& outputShape = { 1, 3, 3, 1 };
+
+ INetworkPtr network = CreateTwoLayerPooling2dNetwork<ArmnnType>(inputShape, outputShape, padMethod);
+
+ CHECK(network);
+
+ std::vector<T> inputData{ 1, 2, 3,
+ 4, 5, 6,
+ 7, 8, 9 };
+ std::vector<T> expectedOutput{ 9, 9, 9,
+ 9, 9, 9,
+ 9, 9, 9 };
+
+ std::map<int, std::vector<T>> inputTensorData = { { 0, inputData } };
+ std::map<int, std::vector<T>> expectedOutputData = { { 0, expectedOutput } };
+
+ EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(network), inputTensorData, expectedOutputData, backends);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+void MaxPool2dThreeLayerEndToEnd(const std::vector<armnn::BackendId>& backends,
+ PaddingMethod padMethod = PaddingMethod::Exclude)
+{
+ const TensorShape& inputShape = { 1, 3, 3, 1 };
+ const TensorShape& outputShape = { 1, 3, 3, 1 };
+
+ INetworkPtr network = CreateThreeLayerPooling2dNetwork<ArmnnType>(inputShape, outputShape, padMethod);
+
+ CHECK(network);
+
+ std::vector<T> inputData{ 1, 2, 3,
+ 4, 5, 6,
+ 7, 8, 9 };
+ std::vector<T> expectedOutput{ 9, 9, 9,
+ 9, 9, 9,
+ 9, 9, 9 };
+
+ std::map<int, std::vector<T>> inputTensorData = { { 0, inputData } };
+ std::map<int, std::vector<T>> expectedOutputData = { { 0, expectedOutput } };
+
+ EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(network), inputTensorData, expectedOutputData, backends);
+}
+
} // anonymous namespace
diff --git a/src/backends/tosaReference/test/TosaRefEndToEndTests.cpp b/src/backends/tosaReference/test/TosaRefEndToEndTests.cpp
index 914df76..63fa69d 100644
--- a/src/backends/tosaReference/test/TosaRefEndToEndTests.cpp
+++ b/src/backends/tosaReference/test/TosaRefEndToEndTests.cpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2022-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
@@ -134,6 +134,16 @@
MaxPool2dEndToEnd<DataType::Float32>(tosaDefaultBackends, PaddingMethod::IgnoreValue);
}
+TEST_CASE("TosaRefMaxPool2DTwoLayerEndtoEndTestFloat32")
+{
+ MaxPool2dTwoLayerEndToEnd<DataType::Float32>(tosaDefaultBackends);
+}
+
+TEST_CASE("TosaRefMaxPool2DThreeLayerEndtoEndTestFloat32")
+{
+ MaxPool2dThreeLayerEndToEnd<DataType::Float32>(tosaDefaultBackends);
+}
+
// Quantization
TEST_CASE("TosaRefQuantizeFromFloat32ToInt8")
{