/*
 * Copyright (c) 2017-2022 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 "src/cpu/kernels/CpuActivationKernel.h"

#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Utils.h"
#include "src/core/CPP/Validate.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"

#include "src/core/common/Registrars.h"
#include "src/cpu/kernels/activation/list.h"

#include <array>

namespace arm_compute
{
namespace cpu
{
namespace kernels
{
namespace
{
static const std::vector<CpuActivationKernel::ActivationKernel> available_kernels =
{
#ifdef ARM_COMPUTE_ENABLE_SVE
    {
        "sve_q8_activation_lut",
        [](const ActivationDataTypeISASelectorData & data) { return ActivationLayerInfo::is_lut_supported(data.f, data.dt) && data.cpumodel == CPUModel::A510 && data.isa.sve; },
        REGISTER_QASYMM8_SVE(arm_compute::cpu::sve_q8_activation_lut)
    },
#endif // ARM_COMPUTE_ENABLE_SVE
#ifdef __aarch64__
    {
        // Neon LUT implementantion takes precedence
        "neon_q8_activation_lut",
        [](const ActivationDataTypeISASelectorData & data) { return ActivationLayerInfo::is_lut_supported(data.f, data.dt); },
        REGISTER_Q8_NEON(arm_compute::cpu::neon_q8_activation_lut)
    },
#endif // __aarch64__
    {
        "sve2_qu8_activation",
        [](const ActivationDataTypeISASelectorData & data) { return data.dt == DataType::QASYMM8 && data.isa.sve2 && data.f != ActivationLayerInfo::ActivationFunction::GELU; },
        REGISTER_QASYMM8_SVE2(arm_compute::cpu::sve2_qasymm8_activation)
    },
    {
        "sve2_qs8_activation",
        [](const ActivationDataTypeISASelectorData & data) { return data.dt == DataType::QASYMM8_SIGNED && data.isa.sve2 && data.f != ActivationLayerInfo::ActivationFunction::GELU; },
        REGISTER_QASYMM8_SIGNED_SVE2(arm_compute::cpu::sve2_qasymm8_signed_activation)
    },
    {
        "sve2_qs16_activation",
        [](const ActivationDataTypeISASelectorData & data) { return data.dt == DataType::QSYMM16 && data.isa.sve2 && data.f != ActivationLayerInfo::ActivationFunction::GELU; },
        REGISTER_QSYMM16_SVE2(arm_compute::cpu::sve2_qsymm16_activation)
    },
    {
        "sve_fp16_activation",
        [](const ActivationDataTypeISASelectorData & data) { return data.dt == DataType::F16 && data.isa.sve && data.isa.fp16 && data.f != ActivationLayerInfo::ActivationFunction::GELU; },
        REGISTER_FP16_SVE(arm_compute::cpu::sve_fp16_activation)
    },
    {
        "sve_fp32_activation",
        [](const ActivationDataTypeISASelectorData & data) { return data.dt == DataType::F32 && data.isa.sve && data.f != ActivationLayerInfo::ActivationFunction::GELU; },
        REGISTER_FP32_SVE(arm_compute::cpu::sve_fp32_activation)
    },
    {
        "neon_fp16_activation",
        [](const ActivationDataTypeISASelectorData & data) { return data.dt == DataType::F16 && data.isa.fp16; },
        REGISTER_FP16_NEON(arm_compute::cpu::neon_fp16_activation)
    },
    {
        "neon_fp32_activation",
        [](const ActivationDataTypeISASelectorData & data) { return data.dt == DataType::F32; },
        REGISTER_FP32_NEON(arm_compute::cpu::neon_fp32_activation)
    },
    {
        "neon_qu8_activation",
        [](const ActivationDataTypeISASelectorData & data) { return data.dt == DataType::QASYMM8; },
        REGISTER_QASYMM8_NEON(arm_compute::cpu::neon_qasymm8_activation)
    },
    {
        "neon_qs8_activation",
        [](const ActivationDataTypeISASelectorData & data) { return data.dt == DataType::QASYMM8_SIGNED; },
        REGISTER_QASYMM8_SIGNED_NEON(arm_compute::cpu::neon_qasymm8_signed_activation)
    },
    {
        "neon_qs16_activation",
        [](const ActivationDataTypeISASelectorData & data) { return data.dt == DataType::QSYMM16; },
        REGISTER_QSYMM16_NEON(arm_compute::cpu::neon_qsymm16_activation)
    },
};

/* Supported activation in the 8-bit integer domain */
static const std::array<ActivationLayerInfo::ActivationFunction, 8> qasymm8_activations =
{
    ActivationLayerInfo::ActivationFunction::RELU,
    ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
    ActivationLayerInfo::ActivationFunction::BOUNDED_RELU,
    ActivationLayerInfo::ActivationFunction::LOGISTIC,
    ActivationLayerInfo::ActivationFunction::TANH,
    ActivationLayerInfo::ActivationFunction::HARD_SWISH,
    ActivationLayerInfo::ActivationFunction::LEAKY_RELU,
    ActivationLayerInfo::ActivationFunction::GELU,
};
/* Supported activation in the 16-bit integer domain */
static const std::array<ActivationLayerInfo::ActivationFunction, 4> qsymm16_activations =
{
    ActivationLayerInfo::ActivationFunction::LOGISTIC,
    ActivationLayerInfo::ActivationFunction::TANH,
    ActivationLayerInfo::ActivationFunction::HARD_SWISH,
    ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU
};

Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dst, const ActivationLayerInfo &activation_info)
{
    ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(src);
    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::QASYMM8_SIGNED, DataType::QASYMM8, DataType::QSYMM16, DataType::F16, DataType::F32);

    const auto *uk = CpuActivationKernel::get_implementation(ActivationDataTypeISASelectorData{ src->data_type(), CPUInfo::get().get_cpu_model(), CPUInfo::get().get_isa(), activation_info.activation() });
    ARM_COMPUTE_RETURN_ERROR_ON(uk == nullptr || uk->ukernel == nullptr);

    const DataType                                data_type = src->data_type();
    const QuantizationInfo                       &oq_info   = (dst != nullptr) ? dst->quantization_info() : src->quantization_info();
    const ActivationLayerInfo::ActivationFunction f_act     = activation_info.activation();

    ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_data_type_quantized_asymmetric(data_type) && (std::find(std::begin(qasymm8_activations), std::end(qasymm8_activations), f_act) == std::end(qasymm8_activations)),
                                    "For QASYMM8 only hard swish, leaky relu, tanh, logistic, relu and lower/upper bounded relu are supported");

    ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_data_type_quantized_symmetric(data_type) && (std::find(std::begin(qsymm16_activations), std::end(qsymm16_activations), f_act) == std::end(qsymm16_activations)),
                                    "For QSYMM16 only tanh and logistic are supported");
    ARM_COMPUTE_RETURN_ERROR_ON((data_type == DataType::QASYMM8 || data_type == DataType::QASYMM16) && (f_act == ActivationLayerInfo::ActivationFunction::TANH)
                                && (oq_info != QuantizationInfo(1.f / 128.f, 128)));
    ARM_COMPUTE_RETURN_ERROR_ON((data_type == DataType::QASYMM8 || data_type == DataType::QASYMM16) && (f_act == ActivationLayerInfo::ActivationFunction::LOGISTIC)
                                && (oq_info != QuantizationInfo(1.f / 256.f, 0)));

    ARM_COMPUTE_RETURN_ERROR_ON(data_type == DataType::QASYMM8_SIGNED && (f_act == ActivationLayerInfo::ActivationFunction::TANH) && (oq_info != QuantizationInfo(1.f / 128.f, 0)));
    ARM_COMPUTE_RETURN_ERROR_ON(data_type == DataType::QASYMM8_SIGNED && (f_act == ActivationLayerInfo::ActivationFunction::LOGISTIC) && (oq_info != QuantizationInfo(1.f / 256.f, -128)));

    ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_symmetric(data_type) && (f_act == ActivationLayerInfo::ActivationFunction::TANH) && (oq_info != QuantizationInfo(1.f / 32768.f, 0)));
    ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_symmetric(data_type) && (f_act == ActivationLayerInfo::ActivationFunction::LOGISTIC) && (oq_info != QuantizationInfo(1.f / 32768.f, 0)));

    // Checks performed when dst is configured
    if((dst != nullptr) && (dst->total_size() != 0))
    {
        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(src, dst);
        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst);
    }

    return Status{};
}

std::pair<Status, Window> validate_and_configure_window(const ITensorInfo *src, ITensorInfo *dst)
{
    // Configure kernel window
    Window win = calculate_max_window(*src, Steps());

    if(dst != nullptr)
    {
        // dst auto inizialitation if not yet initialized
        auto_init_if_empty(*dst, *src->clone());
    }

    return std::make_pair(Status{}, win);
}
} // namespace

void CpuActivationKernel::configure(const ITensorInfo *src, ITensorInfo *dst, ActivationLayerInfo activation_info)
{
    ARM_COMPUTE_UNUSED(dst);
    ARM_COMPUTE_ERROR_ON_NULLPTR(src);
    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, dst, activation_info));

    const auto uk = CpuActivationKernel::get_implementation(ActivationDataTypeISASelectorData{ src->data_type(), CPUInfo::get().get_cpu_model(), CPUInfo::get().get_isa(), activation_info.activation() });
    if(dst != nullptr)
    {
        // dst auto inizialitation if not yet initialized
        auto_init_if_empty(*dst, *src->clone());
    }

    ARM_COMPUTE_ERROR_ON_NULLPTR(uk);

    _run_method = uk->ukernel;
    _name       = std::string("CpuActivationKernel").append("/").append(uk->name);

#ifdef __aarch64__
    if(ActivationLayerInfo::is_lut_supported(activation_info.activation(), src->data_type()))
    {
        activation_info.init_lut(src->data_type(), src->quantization_info().uniform(), (dst) ? dst->quantization_info().uniform() : src->quantization_info().uniform());
    }
#endif // __aarch64__
    _act_info = activation_info;

    Window win;

    // Use squashed window
    std::tie(win, _split_dimension) = calculate_squashed_or_max_window(*src);
    ICPPKernel::configure(win);
}

Status CpuActivationKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, const ActivationLayerInfo &act_info)
{
    ARM_COMPUTE_UNUSED(act_info);
    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, dst, act_info));
    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(src->clone().get(), (dst != nullptr) ? dst->clone().get() : nullptr).first);

    return Status{};
}

size_t CpuActivationKernel::get_mws(const CPUInfo &platform, size_t thread_count) const
{
    ARM_COMPUTE_UNUSED(thread_count);
    ARM_COMPUTE_UNUSED(platform);

    if(_split_dimension == Window::DimX)
    {
        // Don't split the work load too small if the tensor has been reinterpreted as 1D.
        // This number is loosely chosen as threading overhead in each platform varies wildly.
        return 1536;
    }
    return default_mws;
}

void CpuActivationKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
{
    // Early exit on disabled activation
    if(!_act_info.enabled())
    {
        return;
    }

    ARM_COMPUTE_UNUSED(info);
    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

    ARM_COMPUTE_ERROR_ON(tensors.empty());
    ARM_COMPUTE_ERROR_ON(_run_method == nullptr);

    const ITensor *src = tensors.get_const_tensor(TensorType::ACL_SRC);
    ITensor       *dst = tensors.get_tensor(TensorType::ACL_DST);

    _run_method(src, dst, _act_info, window);
}

const char *CpuActivationKernel::name() const
{
    return _name.c_str();
}

const std::vector<CpuActivationKernel::ActivationKernel> &CpuActivationKernel::get_available_kernels()
{
    return available_kernels;
}
} // namespace kernels
} // namespace cpu
} // namespace arm_compute