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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.
*/
#ifndef __NNFW_KERNEL_ACL_RESHAPE_COMMON_H__
#define __NNFW_KERNEL_ACL_RESHAPE_COMMON_H__
#include <OperationsUtils.h>
#include <arm_compute/core/TensorShape.h>
#include <arm_compute/core/TensorInfo.h>
// TODO: fix include path in CMakeFiles
#include "IO_accessor.h"
#include "shape.h"
namespace nnfw {
namespace kernel {
namespace acl {
namespace common {
typedef std::function<void (void)> sync_scheduler_f;
template<class TensorT, class LayerT>
bool reshapeGeneric(const void* inputData, const nnfw::rt::Shape& inputShape,
void* outputData, const nnfw::rt::Shape& outputShape,
sync_scheduler_f sync_scheduler) {
auto input_shape = util::fromNNShape(inputShape);
auto output_shape = util::fromNNShape(outputShape);
TensorT input(arm_compute::TensorInfo(input_shape, arm_compute::Format::F32));
TensorT output(arm_compute::TensorInfo(output_shape, arm_compute::Format::F32));
LayerT l;
l.configure(input.ptr(), output.ptr());
input.allocate();
output.allocate();
TensorAccess<InputAccessor>(input.ref(), (float*)inputData, inputShape);
l.run();
sync_scheduler();
TensorAccess<OutputAccessor>(output.ref(), (float*)outputData, outputShape);
return true;
}
} // namespace common
} // namespace acl
} // namespace kernel
} // namespace nnfw
#endif // __NNFW_KERNEL_ACL_RESHAPE_COMMON_H__
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