/*
 * Copyright (c) 2019-2021, 2023 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/core/CL/kernels/CLInstanceNormalizationLayerKernel.h"

#include "arm_compute/core/CL/CLHelpers.h"
#include "arm_compute/core/CL/CLKernelLibrary.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/utils/StringUtils.h"

#include "src/core/CL/CLValidate.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
#include "support/StringSupport.h"

namespace arm_compute
{
namespace
{
Status validate_arguments(const ITensorInfo                          *input,
                          const ITensorInfo                          *output,
                          const InstanceNormalizationLayerKernelInfo &info)
{
    ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.epsilon == 0.f, "Epsilon must be different than 0");
    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F16, DataType::F32);

    if (output != nullptr && output->total_size() != 0)
    {
        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
        ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_channels() != output->num_channels(),
                                        "Input and output have different number of channels");
    }

    return Status{};
}

Status validate_arguments_meanvar(const ITensorInfo *input, const ITensorInfo *output)
{
    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F16, DataType::F32);

    if (output != nullptr && output->total_size() != 0)
    {
        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
        ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_channels() != output->num_channels(),
                                        "Input and output have different number of channels");
    }

    return Status{};
}
} // namespace

CLComputeMeanVariance::CLComputeMeanVariance() : _input(nullptr), _output(nullptr)
{
    _type = CLKernelType::ELEMENTWISE;
}

void CLComputeMeanVariance::configure(const CLCompileContext &compile_context,
                                      ICLTensor              *input,
                                      ICLTensor              *output,
                                      bool                    use_mixed_precision)
{
    ARM_COMPUTE_ERROR_ON_NULLPTR(input);
    auto padding_info = get_padding_info({input, output});

    _input  = input;
    _output = output == nullptr ? input : output;

    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_meanvar(_input->info(), _output->info()));
    const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();

    CLBuildOptions build_opts;
    build_opts.add_option("-DINTERNAL_DATA_TYPE=" +
                          (use_mixed_precision ? "float" : get_cl_type_from_data_type(input->info()->data_type())));
    build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
    build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
    build_opts.add_option("-DDIM_X=" + support::cpp11::to_string(input->info()->dimension(0)));
    build_opts.add_option("-DDIM_Y=" + support::cpp11::to_string(input->info()->dimension(1)));
    build_opts.add_option("-DDIM_Z=" + support::cpp11::to_string(input->info()->dimension(2)));
    build_opts.add_option_if(_input->info()->data_layout() == DataLayout::NHWC, "-DNHWC");
    // Create kernel
    _kernel = create_kernel(compile_context, "compute_mean_var", build_opts.options());

    // We handle the planes manually
    Window             win           = calculate_max_window(*(input->info()), Steps(1));
    const auto         data_layout   = input->info()->data_layout();
    const unsigned int channel_idx   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
    const unsigned int batches_idx   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);
    const unsigned int input_channel = input->info()->dimension(channel_idx);
    const unsigned int input_batches = input->info()->dimension(batches_idx);
    const TensorShape  out_shape(input_channel, 2u, input_batches);

    // Output auto initialization if not yet initialized
    if (use_mixed_precision)
    {
        auto_init_if_empty(*_output->info(), out_shape, 1, DataType::F32);
    }
    else
    {
        auto_init_if_empty(*_output->info(), out_shape, 1, input->info()->data_type());
    }
    ICLKernel::configure_internal(win);
    ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
}

Status CLComputeMeanVariance::validate(const ITensorInfo *input, const ITensorInfo *output)
{
    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_meanvar(input, output));
    return Status{};
}

void CLComputeMeanVariance::run(const Window &window, cl::CommandQueue &queue)
{
    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

    Window collapsed_window = window.collapse(window, Window::DimZ);

    // We will process the planes together
    if (_input->info()->data_layout() == DataLayout::NCHW)
    {
        collapsed_window.set(Window::DimX, Window::Dimension(0, 1, 1));
        collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1));
    }
    else
    {
        collapsed_window.set(Window::DimZ, Window::Dimension(0, 1, 1));
        collapsed_window.set(Window::DimY, Window::Dimension(0, _input->info()->dimension(3), 1));
    }
    unsigned int idx = 0;
    add_4D_tensor_argument(idx, _input, collapsed_window);
    add_3D_tensor_argument(idx, _output, collapsed_window);

    enqueue(queue, *this, collapsed_window, lws_hint());
}

CLInstanceNormalizationLayerKernel::CLInstanceNormalizationLayerKernel()
    : _input(nullptr), _output(nullptr), _mean(nullptr), _run_in_place(false)
{
    _type = CLKernelType::ELEMENTWISE;
}

void CLInstanceNormalizationLayerKernel::configure(const CLCompileContext                     &compile_context,
                                                   ICLTensor                                  *input,
                                                   ICLTensor                                  *mean_var,
                                                   ICLTensor                                  *output,
                                                   const InstanceNormalizationLayerKernelInfo &info)
{
    ARM_COMPUTE_ERROR_ON_NULLPTR(input);
    auto padding_info = get_padding_info({input, output});

    _input  = input;
    _output = output == nullptr ? input : output;
    _mean   = mean_var;

    _run_in_place = (output == nullptr) || (output == input);
    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(_input->info(), _output->info(), info));
    const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();

    CLBuildOptions build_opts;
    build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
    build_opts.add_option("-DINTERNAL_DATA_TYPE=" + (info.use_mixed_precision
                                                         ? "float"
                                                         : get_cl_type_from_data_type(input->info()->data_type())));
    build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
    build_opts.add_option("-DDIM_X=" + support::cpp11::to_string(input->info()->dimension(0)));
    build_opts.add_option("-DDIM_Y=" + support::cpp11::to_string(input->info()->dimension(1)));
    build_opts.add_option("-DDIM_Z=" + support::cpp11::to_string(input->info()->dimension(2)));
    build_opts.add_option("-DGAMMA=" + float_to_string_with_full_precision(info.gamma));
    build_opts.add_option("-DBETA=" + float_to_string_with_full_precision(info.beta));
    build_opts.add_option("-DEPSILON=" + float_to_string_with_full_precision(info.epsilon));
    build_opts.add_option_if(_run_in_place, "-DIN_PLACE");
    build_opts.add_option_if(_input->info()->data_layout() == DataLayout::NHWC, "-DNHWC");

    // Create kernel
    _kernel = create_kernel(compile_context, "instance_normalization", build_opts.options());

    // Configure kernel window
    Window win = calculate_max_window(*input->info(), Steps(1));
    if (output != nullptr)
    {
        auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type());
    }

    ICLKernel::configure_internal(win);
    ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
}

Status CLInstanceNormalizationLayerKernel::validate(const ITensorInfo                          *input,
                                                    const ITensorInfo                          *output,
                                                    const InstanceNormalizationLayerKernelInfo &info)
{
    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, info));
    return Status{};
}

void CLInstanceNormalizationLayerKernel::run(const Window &window, cl::CommandQueue &queue)
{
    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

    Window collapsed_window = window.collapse(window, Window::DimZ);

    // We will process the planes together
    if (_input->info()->data_layout() == DataLayout::NCHW)
    {
        collapsed_window.set(Window::DimX, Window::Dimension(0, 1, 1));
        collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1));
    }
    else
    {
        collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1));
        collapsed_window.set(Window::DimZ, Window::Dimension(0, _input->info()->dimension(3), 1));
    }

    unsigned int idx = 0;
    add_4D_tensor_argument(idx, _input, collapsed_window);
    add_3D_tensor_argument(idx, _mean, collapsed_window);

    if (!_run_in_place)
    {
        add_4D_tensor_argument(idx, _output, collapsed_window);
    }

    enqueue(queue, *this, collapsed_window, lws_hint());
}
} // namespace arm_compute