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//
// Copyright © 2019 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include <aclCommon/ArmComputeTensorUtils.hpp>
#include <boost/test/unit_test.hpp>
using namespace armnn::armcomputetensorutils;
BOOST_AUTO_TEST_SUITE(ArmComputeTensorUtils)
BOOST_AUTO_TEST_CASE(BuildArmComputeTensorInfoTest)
{
const armnn::TensorShape tensorShape = { 1, 2, 3, 4 };
const armnn::DataType dataType = armnn::DataType::QuantisedAsymm8;
const std::vector<float> quantScales = { 1.5f, 2.5f, 3.5f, 4.5f };
const float quantScale = quantScales[0];
const int32_t quantOffset = 128;
// Tensor info with per-tensor quantization
const armnn::TensorInfo tensorInfo0(tensorShape, dataType, quantScale, quantOffset);
const arm_compute::TensorInfo aclTensorInfo0 = BuildArmComputeTensorInfo(tensorInfo0);
const arm_compute::TensorShape& aclTensorShape = aclTensorInfo0.tensor_shape();
BOOST_CHECK(aclTensorShape.num_dimensions() == tensorShape.GetNumDimensions());
for(unsigned int i = 0u; i < tensorShape.GetNumDimensions(); ++i)
{
// NOTE: arm_compute tensor dimensions are stored in the opposite order
BOOST_CHECK(aclTensorShape[i] == tensorShape[tensorShape.GetNumDimensions() - i - 1]);
}
BOOST_CHECK(aclTensorInfo0.data_type() == arm_compute::DataType::QASYMM8);
BOOST_CHECK(aclTensorInfo0.quantization_info().scale()[0] == quantScale);
// Tensor info with per-axis quantization
const armnn::TensorInfo tensorInfo1(tensorShape, dataType, quantScales, 0);
const arm_compute::TensorInfo aclTensorInfo1 = BuildArmComputeTensorInfo(tensorInfo1);
BOOST_CHECK(aclTensorInfo1.quantization_info().scale() == quantScales);
}
BOOST_AUTO_TEST_SUITE_END()
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