/*
 * Copyright (c) 2017-2018 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 "arm_compute/runtime/NEON/functions/NESoftmaxLayer.h"

#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/NEON/kernels/NESoftmaxLayerKernel.h"
#include "arm_compute/runtime/NEON/NEScheduler.h"

#include <cfloat>

using namespace arm_compute;

NESoftmaxLayer::NESoftmaxLayer(std::shared_ptr<IMemoryManager> memory_manager)
    : _memory_group(std::move(memory_manager)), _max_kernel(), _softmax_kernel(), _fill_border_kernel(), _max(), _tmp()
{
}

void NESoftmaxLayer::configure(ITensor *input, ITensor *output, float beta)
{
    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);

    // Configure Kernels
    _max_kernel.configure(input, &_max);
    _fill_border_kernel.configure(input, _max_kernel.border_size(), BorderMode::REPLICATE);
    _softmax_kernel.configure(input, &_max, output, beta, &_tmp);

    // Init intermediate tensors
    _max.allocator()->init(*_max.info());
    _tmp.allocator()->init(*_tmp.info());

    // Manage intermediate buffers
    _memory_group.manage(&_max);
    _memory_group.manage(&_tmp);

    // Allocate intermediate tensors
    _max.allocator()->allocate();
    _tmp.allocator()->allocate();
}

Status NESoftmaxLayer::validate(const ITensorInfo *input, const ITensorInfo *output, float beta)
{
    // Perform validation step
    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
    ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_dimensions() > 2, "Only 2D inputs are supported");

    const TensorShape max_shape           = TensorShape(input->tensor_shape()).set(0, 1);
    const TensorInfo  tensor_info_max_sum = TensorInfo(*input).set_tensor_shape(max_shape).reset_padding();
    const TensorInfo  dont_care;

    ARM_COMPUTE_RETURN_ON_ERROR(NELogits1DMaxKernel::validate(input, &tensor_info_max_sum));
    ARM_COMPUTE_RETURN_ON_ERROR(NELogits1DSoftmaxKernel::validate(input, &tensor_info_max_sum, output, beta, &dont_care));

    return Status{};
}

void NESoftmaxLayer::run()
{
    _memory_group.acquire();

    NEScheduler::get().schedule(&_fill_border_kernel, Window::DimY);
    NEScheduler::get().schedule(&_max_kernel, Window::DimY);
    NEScheduler::get().schedule(&_softmax_kernel, Window::DimY);

    _memory_group.release();
}