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/*
* 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/NEQuantizationLayer.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/runtime/NEON/NEScheduler.h"
using namespace arm_compute;
NEQuantizationLayer::NEQuantizationLayer()
: _quantize_kernel(), _min_max_kernel(), _min_max()
{
}
Status NEQuantizationLayer::validate(const ITensorInfo *input, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
TensorInfo min_max{ input->num_channels(), input->data_type() };
ARM_COMPUTE_RETURN_ON_ERROR(NEMinMaxLayerKernel::validate(input, &min_max));
ARM_COMPUTE_RETURN_ON_ERROR(NEQuantizationLayerKernel::validate(input, output, &min_max));
return Status{};
}
void NEQuantizationLayer::configure(const ITensor *input, ITensor *output)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
// Configure min-max kernel. _min_max tensor will be auto-configured within the kernel
_min_max_kernel.configure(input, &_min_max);
// Configure quantize kernel
_quantize_kernel.configure(input, output, &_min_max);
// Allocate min_max tensor
_min_max.allocator()->allocate();
}
void NEQuantizationLayer::run()
{
// Reset min and max
_min_max_kernel.reset();
// Run min and max kernel
NEScheduler::get().schedule(&_min_max_kernel, Window::DimY);
// Run quantize kernel
NEScheduler::get().schedule(&_quantize_kernel, Window::DimY);
}
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