135 lines
4.2 KiB
C++
135 lines
4.2 KiB
C++
//
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// Copyright © 2017 Arm Ltd. All rights reserved.
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// SPDX-License-Identifier: MIT
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//
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#include "OperationsUtils.h"
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#include "../DriverTestHelpers.hpp"
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#include "../TestTensor.hpp"
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#include "../1.1/HalPolicy.hpp"
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#include <boost/test/unit_test.hpp>
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#include <boost/test/data/test_case.hpp>
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#include <log/log.h>
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#include <array>
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#include <cmath>
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BOOST_AUTO_TEST_SUITE(TransposeTests)
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using namespace android::hardware;
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using namespace driverTestHelpers;
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using namespace armnn_driver;
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using HalPolicy = hal_1_1::HalPolicy;
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namespace
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{
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#ifndef ARMCOMPUTECL_ENABLED
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static const std::array<armnn::Compute, 1> COMPUTE_DEVICES = {{ armnn::Compute::CpuRef }};
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#else
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static const std::array<armnn::Compute, 2> COMPUTE_DEVICES = {{ armnn::Compute::CpuRef, armnn::Compute::GpuAcc }};
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#endif
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void TransposeTestImpl(const TestTensor & inputs, int32_t perm[],
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const TestTensor & expectedOutputTensor, armnn::Compute computeDevice)
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{
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auto driver = std::make_unique<ArmnnDriver>(DriverOptions(computeDevice));
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HalPolicy::Model model = {};
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AddInputOperand<HalPolicy>(model,inputs.GetDimensions());
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AddTensorOperand<HalPolicy>(model,
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hidl_vec<uint32_t>{4},
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perm,
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HalPolicy::OperandType::TENSOR_INT32);
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AddOutputOperand<HalPolicy>(model, expectedOutputTensor.GetDimensions());
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model.operations.resize(1);
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model.operations[0].type = HalPolicy::OperationType::TRANSPOSE;
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model.operations[0].inputs = hidl_vec<uint32_t>{0, 1};
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model.operations[0].outputs = hidl_vec<uint32_t>{2};
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android::sp<V1_0::IPreparedModel> preparedModel = PrepareModel(model, *driver);
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// the request's memory pools will follow the same order as
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// the inputs
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DataLocation inloc = {};
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inloc.poolIndex = 0;
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inloc.offset = 0;
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inloc.length = inputs.GetNumElements() * sizeof(float);
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RequestArgument input = {};
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input.location = inloc;
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input.dimensions = inputs.GetDimensions();
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// and an additional memory pool is needed for the output
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DataLocation outloc = {};
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outloc.poolIndex = 1;
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outloc.offset = 0;
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outloc.length = expectedOutputTensor.GetNumElements() * sizeof(float);
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RequestArgument output = {};
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output.location = outloc;
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output.dimensions = expectedOutputTensor.GetDimensions();
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// make the request based on the arguments
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V1_0::Request request = {};
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request.inputs = hidl_vec<RequestArgument>{input};
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request.outputs = hidl_vec<RequestArgument>{output};
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// set the input data
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AddPoolAndSetData(inputs.GetNumElements(),
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request,
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inputs.GetData());
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// add memory for the output
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android::sp<IMemory> outMemory = AddPoolAndGetData<float>(expectedOutputTensor.GetNumElements(), request);
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float* outdata = static_cast<float*>(static_cast<void*>(outMemory->getPointer()));
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if (preparedModel.get() != nullptr)
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{
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auto execStatus = Execute(preparedModel, request);
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}
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const float * expectedOutput = expectedOutputTensor.GetData();
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for (unsigned int i = 0; i < expectedOutputTensor.GetNumElements(); ++i)
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{
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BOOST_TEST(outdata[i] == expectedOutput[i]);
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}
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}
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} // namespace
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BOOST_DATA_TEST_CASE(Transpose , COMPUTE_DEVICES)
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{
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int32_t perm[] = {2, 3, 1, 0};
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TestTensor input{armnn::TensorShape{1, 2, 2, 2},{1, 2, 3, 4, 5, 6, 7, 8}};
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TestTensor expected{armnn::TensorShape{2, 2, 2, 1},{1, 5, 2, 6, 3, 7, 4, 8}};
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TransposeTestImpl(input, perm, expected, sample);
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}
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BOOST_DATA_TEST_CASE(TransposeNHWCToArmNN , COMPUTE_DEVICES)
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{
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int32_t perm[] = {0, 3, 1, 2};
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TestTensor input{armnn::TensorShape{1, 2, 2, 3},{1, 2, 3, 11, 12, 13, 21, 22, 23, 31, 32, 33}};
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TestTensor expected{armnn::TensorShape{1, 3, 2, 2},{1, 11, 21, 31, 2, 12, 22, 32, 3, 13, 23, 33}};
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TransposeTestImpl(input, perm, expected, sample);
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}
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BOOST_DATA_TEST_CASE(TransposeArmNNToNHWC , COMPUTE_DEVICES)
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{
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int32_t perm[] = {0, 2, 3, 1};
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TestTensor input{armnn::TensorShape{1, 2, 2, 2},{1, 2, 3, 4, 5, 6, 7, 8}};
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TestTensor expected{armnn::TensorShape{1, 2, 2, 2},{1, 5, 2, 6, 3, 7, 4, 8}};
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TransposeTestImpl(input, perm, expected, sample);
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}
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BOOST_AUTO_TEST_SUITE_END()
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