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/*
* Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <OperationsUtils.h>
#include <arm_compute/core/TensorShape.h>
#include <arm_compute/core/TensorInfo.h>
#include <arm_compute/runtime/NEON/NEScheduler.h>
#include <cassert>
// TODO: fix include path in CMakeFiles
#include "../IO_accessor.h"
#include "../shape.h"
#include "../NEUniqueTensor.h"
#include "../DepthwiseConv2D.h"
namespace nnfw {
namespace kernel {
namespace acl {
namespace neon {
static void sync_scheduler() {
}
bool depthwiseConvFloat32(const float* inputData, const nnfw::rt::Shape& inputShape,
const float* filterData, const nnfw::rt::Shape& filterShape,
const float* biasData, const nnfw::rt::Shape& biasShape,
int32_t padding_left, int32_t padding_right,
int32_t padding_top, int32_t padding_bottom,
int32_t stride_width, int32_t stride_height,
int32_t depth_multiplier, int32_t activation,
float* outputData, const nnfw::rt::Shape& outputShape) {
return common::depthwiseConvFloat32<NEUniqueTensor, arm_compute::NEDepthwiseConvolutionLayer,
arm_compute::NEActivationLayer>(inputData, inputShape,
filterData, filterShape,
biasData, biasShape,
padding_left, padding_right,
padding_top, padding_bottom,
stride_width, stride_height,
depth_multiplier, activation,
outputData, outputShape,
sync_scheduler);
}
} // namespace neon
} // namespace acl
} // namespace kernel
} // namespace nnfw
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