From ae12306486efc55293a40048618abe5e8b19151b Mon Sep 17 00:00:00 2001 From: Matthew Sloyan Date: Fri, 7 May 2021 14:18:01 +0000 Subject: Revert "MLCE-418 Reduce layer does not support multiple axes" This reverts commit d905decd256558bbee165e636ce4242ac3b9c917. Reason for revert: LargeGraph_TENSOR_FLOAT32/FLOAT16 CTS tests failures Change-Id: Ie69826549e73775825f45134375b5b2c41aebd01 --- .../test/optimizations/ReduceMultipleAxesTests.cpp | 288 --------------------- 1 file changed, 288 deletions(-) delete mode 100644 src/armnn/test/optimizations/ReduceMultipleAxesTests.cpp (limited to 'src/armnn/test') diff --git a/src/armnn/test/optimizations/ReduceMultipleAxesTests.cpp b/src/armnn/test/optimizations/ReduceMultipleAxesTests.cpp deleted file mode 100644 index 28c0ea1466..0000000000 --- a/src/armnn/test/optimizations/ReduceMultipleAxesTests.cpp +++ /dev/null @@ -1,288 +0,0 @@ -// -// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#include "../GraphUtils.hpp" -#include "../TestUtils.hpp" - -#include - -#include - -using namespace armnn; - -BOOST_AUTO_TEST_SUITE(Optimizer) - -INetworkPtr CreateSimpleReduceNetwork(ReduceDescriptor reduceDescriptor, - TensorShape& inputShape, - TensorShape& outputShape) -{ - // Create a network - INetworkPtr network = INetwork::Create(); - - const std::string layerName("reduce_layer"); - const TensorInfo inputInfo (inputShape, DataType::Float32); - const TensorInfo outputInfo(outputShape, DataType::Float32); - - IConnectableLayer* const inputLayer = network->AddInputLayer(0); - IConnectableLayer* const reduceLayer = network->AddReduceLayer(reduceDescriptor, layerName.c_str()); - IConnectableLayer* const outputLayer = network->AddOutputLayer(0); - - inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); - reduceLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); - - inputLayer->GetOutputSlot(0).Connect(reduceLayer->GetInputSlot(0)); - reduceLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); - - return network; -} - -void ReduceWithMultipleAxesTest(INetworkPtr& network, - const TensorShape& outputShape, - const std::vector& inputData, - const std::vector& expectedOutput, - const size_t numOfAxes, - Compute backendId) -{ - // Create ArmNN runtime - IRuntimePtr run = IRuntime::Create(IRuntime::CreationOptions()); - - // Optimise ArmNN network - IOptimizedNetworkPtr optNet = Optimize(*network, {backendId}, run->GetDeviceSpec()); - - Graph& graph = GetGraphForTesting(optNet.get()); - if (numOfAxes == 2) - { - BOOST_CHECK(graph.GetNumLayers() == 4); - BOOST_TEST(CheckSequence(graph.cbegin(), - graph.cend(), - &IsLayerOfType, - &IsLayerOfType, - &IsLayerOfType, - &IsLayerOfType)); - } - else - { - BOOST_CHECK(graph.GetNumLayers() == 5); - BOOST_TEST(CheckSequence(graph.cbegin(), - graph.cend(), - &IsLayerOfType, - &IsLayerOfType, - &IsLayerOfType, - &IsLayerOfType, - &IsLayerOfType)); - } - - // Get last layer in new chain, layers name follow 0, 1, 2 pattern - std::string layerName = "reduce_layer_" + std::to_string(numOfAxes - 1); - Layer* const reduceLayer = GetFirstLayerWithName(graph, layerName); - BOOST_TEST(reduceLayer); - auto reduceTensorInfo = reduceLayer->GetOutputSlot().GetTensorInfo(); - - // Tensorshape and the data type are correct - BOOST_TEST((reduceTensorInfo.GetShape() == outputShape)); - BOOST_TEST((reduceTensorInfo.GetDataType() == DataType::Float32)); - - // Load network into runtime - NetworkId networkIdentifier; - run->LoadNetwork(networkIdentifier, std::move(optNet)); - - // Create input and output tensors - std::vector outputData(expectedOutput.size()); - InputTensors inputTensors - { - { 0, armnn::ConstTensor(run->GetInputTensorInfo(networkIdentifier, 0), inputData.data()) } - }; - OutputTensors outputTensors - { - { 0, armnn::Tensor(run->GetOutputTensorInfo(networkIdentifier, 0), outputData.data()) } - }; - - // Run inference - run->EnqueueWorkload(networkIdentifier, inputTensors, outputTensors); - - // Checks the results - BOOST_TEST(outputData == expectedOutput); -} - -void ReduceSumWithTwoAxesKeepDimsTest(Compute backendId) -{ - armnn::ReduceDescriptor reduceDescriptor; - reduceDescriptor.m_vAxis = { 1, 2 }; - reduceDescriptor.m_KeepDims = true; - reduceDescriptor.m_ReduceOperation = armnn::ReduceOperation::Sum; - - TensorShape inputShape = { 1, 3, 2, 4 }; - TensorShape outputShape = { 1, 1, 1, 4 }; - - // Construct ArmNN network - INetworkPtr network = CreateSimpleReduceNetwork(reduceDescriptor, inputShape, outputShape); - - // Creates structures for input & output. - const std::vector inputData({ 1.0f, 2.0f, 3.0f, 4.0f, - 5.0f, 6.0f, 7.0f, 8.0f, - - 10.0f, 20.0f, 30.0f, 40.0f, - 50.0f, 60.0f, 70.0f, 80.0f, - - 100.0f, 200.0f, 300.0f, 400.0f, - 500.0f, 600.0f, 700.0f, 800.0f }); - const std::vector expectedOutput({ 666.0f, 888.0f, 1110.0f, 1332.0f }); - - ReduceWithMultipleAxesTest(network, - outputShape, - inputData, - expectedOutput, - reduceDescriptor.m_vAxis.size(), - backendId); -} - -void ReduceSumWithTwoAxesTest(Compute backendId) -{ - armnn::ReduceDescriptor reduceDescriptor; - reduceDescriptor.m_vAxis = { 1, 2 }; - reduceDescriptor.m_KeepDims = false; - reduceDescriptor.m_ReduceOperation = armnn::ReduceOperation::Sum; - - TensorShape inputShape = { 1, 3, 2, 4 }; - TensorShape outputShape = { 1, 4 }; - - // Construct ArmNN network - INetworkPtr network = CreateSimpleReduceNetwork(reduceDescriptor, inputShape, outputShape); - - // Creates structures for input & output. - const std::vector inputData({ 1.0f, 2.0f, 3.0f, 4.0f, - 5.0f, 6.0f, 7.0f, 8.0f, - - 10.0f, 20.0f, 30.0f, 40.0f, - 50.0f, 60.0f, 70.0f, 80.0f, - - 100.0f, 200.0f, 300.0f, 400.0f, - 500.0f, 600.0f, 700.0f, 800.0f }); - const std::vector expectedOutput({ 666.0f, 888.0f, 1110.0f, 1332.0f }); - - ReduceWithMultipleAxesTest(network, - outputShape, - inputData, - expectedOutput, - reduceDescriptor.m_vAxis.size(), - backendId); -} - -void ReduceSumWithThreeAxesKeepDimsTest(Compute backendId) -{ - armnn::ReduceDescriptor reduceDescriptor; - reduceDescriptor.m_vAxis = { 0, 2, 3 }; - reduceDescriptor.m_KeepDims = true; - reduceDescriptor.m_ReduceOperation = armnn::ReduceOperation::Sum; - - TensorShape inputShape = { 2, 2, 2, 2 }; - TensorShape outputShape = { 1, 2, 1, 1 }; - - // Construct ArmNN network - INetworkPtr network = CreateSimpleReduceNetwork(reduceDescriptor, inputShape, outputShape); - - // Creates structures for input & output. - const std::vector inputData({ 1.0f, 2.0f, - 3.0f, 4.0f, - - 5.0f, 6.0f, - 7.0f, 8.0f, - - 10.0f, 20.0f, - 30.0f, 40.0f, - - 50.0f, 60.0f, - 70.0f, 80.0f }); - const std::vector expectedOutput({ 110.0f, 286.0f }); - - ReduceWithMultipleAxesTest(network, - outputShape, - inputData, - expectedOutput, - reduceDescriptor.m_vAxis.size(), - backendId); -} - -void ReduceSumWithThreeAxesTest(Compute backendId) -{ - armnn::ReduceDescriptor reduceDescriptor; - reduceDescriptor.m_vAxis = { 0, 2, 3 }; - reduceDescriptor.m_KeepDims = false; - reduceDescriptor.m_ReduceOperation = armnn::ReduceOperation::Sum; - - TensorShape inputShape = { 2, 2, 2, 2 }; - TensorShape outputShape = { 2 }; - - // Construct ArmNN network - INetworkPtr network = CreateSimpleReduceNetwork(reduceDescriptor, inputShape, outputShape); - - // Creates structures for input & output. - const std::vector inputData({ 1.0f, 2.0f, - 3.0f, 4.0f, - - 5.0f, 6.0f, - 7.0f, 8.0f, - - 10.0f, 20.0f, - 30.0f, 40.0f, - - 50.0f, 60.0f, - 70.0f, 80.0f }); - const std::vector expectedOutput({ 110.0f, 286.0f }); - - ReduceWithMultipleAxesTest(network, - outputShape, - inputData, - expectedOutput, - reduceDescriptor.m_vAxis.size(), - backendId); -} - -using namespace armnn; -#if defined(ARMCOMPUTENEON_ENABLED) -BOOST_AUTO_TEST_CASE(ReduceSumWithTwoAxesKeepDimsCpuAccTest) -{ - ReduceSumWithTwoAxesKeepDimsTest(Compute::CpuAcc); -} - -BOOST_AUTO_TEST_CASE(ReduceSumWithTwoAxesCpuAccTest) -{ - ReduceSumWithTwoAxesTest(Compute::CpuAcc); -} - -BOOST_AUTO_TEST_CASE(ReduceSumWithThreeAxesKeepDimsCpuAccTest) -{ - ReduceSumWithThreeAxesKeepDimsTest(Compute::CpuAcc); -} - -BOOST_AUTO_TEST_CASE(ReduceSumWithThreeAxesCpuAccTest) -{ - ReduceSumWithThreeAxesTest(Compute::CpuAcc); -} -#endif - -#if defined(ARMCOMPUTECL_ENABLED) -BOOST_AUTO_TEST_CASE(ReduceSumWithTwoAxesKeepDimsGpuAccTest) -{ - ReduceSumWithTwoAxesKeepDimsTest(Compute::GpuAcc); -} - -BOOST_AUTO_TEST_CASE(ReduceSumWithTwoAxesGpuAccTest) -{ - ReduceSumWithTwoAxesTest(Compute::GpuAcc); -} - -BOOST_AUTO_TEST_CASE(ReduceSumWithThreeAxesKeepDimsGpuAccTest) -{ - ReduceSumWithThreeAxesKeepDimsTest(Compute::GpuAcc); -} - -BOOST_AUTO_TEST_CASE(ReduceSumWithThreeAxesGpuAccTest) -{ - ReduceSumWithThreeAxesTest(Compute::GpuAcc); -} -#endif - -BOOST_AUTO_TEST_SUITE_END() \ No newline at end of file -- cgit v1.2.1