/*
 * Copyright (c) 2017-2020, 2024 Arm Limited.
 *
 * SPDX-License-Identifier: MIT
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to
 * deal in the Software without restriction, including without limitation the
 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
 * sell copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in all
 * copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 */
#include "QuantizationLayer.h"

#include <cmath>

namespace arm_compute
{
namespace test
{
namespace validation
{
namespace reference
{
template <typename Tin, typename Tout>
SimpleTensor<Tout> quantization_layer(const SimpleTensor<Tin> &src, DataType output_data_type, const QuantizationInfo &quantization_info)
{
    // Create reference
    SimpleTensor<Tout> dst{ src.shape(), output_data_type, 1, quantization_info };

    const UniformQuantizationInfo qinfo = quantization_info.uniform();

#ifdef __aarch64__
    constexpr auto rounding_policy = RoundingPolicy::TO_NEAREST_EVEN;
#else  // __aarch64__
    constexpr auto rounding_policy = RoundingPolicy::TO_ZERO;
#endif // __aarch64__

    switch(output_data_type)
    {
        case DataType::QASYMM8:
#if defined(_OPENMP)
            #pragma omp parallel for
#endif /* _OPENMP */
            for(int i = 0; i < src.num_elements(); ++i)
            {
                dst[i] = quantize_qasymm8((src[i]), qinfo, rounding_policy);
            }
            break;
        case DataType::QASYMM8_SIGNED:
#if defined(_OPENMP)
            #pragma omp parallel for
#endif /* _OPENMP */
            for(int i = 0; i < src.num_elements(); ++i)
            {
#ifdef __aarch64__
                dst[i] = quantize_qasymm8_signed((src[i]), qinfo, RoundingPolicy::TO_NEAREST_EVEN);
#else  // __aarch64__
                dst[i] = quantize_qasymm8_signed((src[i]), qinfo, RoundingPolicy::TO_ZERO);
#endif // __aarch64__
            }
            break;
        case DataType::QASYMM16:
#if defined(_OPENMP)
            #pragma omp parallel for
#endif /* _OPENMP */
            for(int i = 0; i < src.num_elements(); ++i)
            {
                dst[i] = quantize_qasymm16((src[i]), qinfo, rounding_policy);
            }
            break;
        default:
            ARM_COMPUTE_ERROR("Unsupported output data type");
    }
    return dst;
}

template <>
SimpleTensor<uint8_t> quantization_layer(const SimpleTensor<uint8_t> &src, DataType output_data_type, const QuantizationInfo &quantization_info)
{
    SimpleTensor<float> src_tmp = convert_from_asymmetric<uint8_t>(src);
    return quantization_layer<float, uint8_t>(src_tmp, output_data_type, quantization_info);
}

template <>
SimpleTensor<int8_t> quantization_layer(const SimpleTensor<uint8_t> &src, DataType output_data_type, const QuantizationInfo &quantization_info)
{
    SimpleTensor<float> src_tmp = convert_from_asymmetric<uint8_t>(src);
    return quantization_layer<float, int8_t>(src_tmp, output_data_type, quantization_info);
}

template <>
SimpleTensor<uint8_t> quantization_layer(const SimpleTensor<int8_t> &src, DataType output_data_type, const QuantizationInfo &quantization_info)
{
    SimpleTensor<float> src_tmp = convert_from_asymmetric<int8_t>(src);
    return quantization_layer<float, uint8_t>(src_tmp, output_data_type, quantization_info);
}

template <>
SimpleTensor<int8_t> quantization_layer(const SimpleTensor<int8_t> &src, DataType output_data_type, const QuantizationInfo &quantization_info)
{
    SimpleTensor<float> src_tmp = convert_from_asymmetric<int8_t>(src);
    return quantization_layer<float, int8_t>(src_tmp, output_data_type, quantization_info);
}

template <>
SimpleTensor<uint16_t> quantization_layer(const SimpleTensor<uint8_t> &src, DataType output_data_type, const QuantizationInfo &quantization_info)
{
    SimpleTensor<float> src_tmp = convert_from_asymmetric<uint8_t>(src);
    return quantization_layer<float, uint16_t>(src_tmp, output_data_type, quantization_info);
}

template SimpleTensor<int8_t> quantization_layer(const SimpleTensor<half> &src, DataType output_data_type, const QuantizationInfo &quantization_info);
template SimpleTensor<int8_t> quantization_layer(const SimpleTensor<float> &src, DataType output_data_type, const QuantizationInfo &quantization_info);
template SimpleTensor<uint8_t> quantization_layer(const SimpleTensor<half> &src, DataType output_data_type, const QuantizationInfo &quantization_info);
template SimpleTensor<uint8_t> quantization_layer(const SimpleTensor<float> &src, DataType output_data_type, const QuantizationInfo &quantization_info);
template SimpleTensor<uint16_t> quantization_layer(const SimpleTensor<half> &src, DataType output_data_type, const QuantizationInfo &quantization_info);
template SimpleTensor<uint16_t> quantization_layer(const SimpleTensor<float> &src, DataType output_data_type, const QuantizationInfo &quantization_info);
} // namespace reference
} // namespace validation
} // namespace test
} // namespace arm_compute
