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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 "internal/arm_compute.h"
#include "SimplePackLayer.h"
void SimplePackLayer::configure(const std::vector<::arm_compute::ICLTensor *> &input_vector,
::arm_compute::ICLTensor *output, int32_t axis)
{
uint32_t nr_inputs = input_vector.size();
uint32_t output_rank = output->info()->num_dimensions();
const ::arm_compute::PermutationVector pv{1, 2, 0};
_cl_permuted_vector.resize(nr_inputs);
_cl_permute_vector.resize(nr_inputs);
_output = output;
// A negative axis implies axis from the end.
// For example, axis = -1 implies the first axis from the end, i.e. axis = Rank - 1.
// Similarly, axis = -2 imples second axis from the end, i.e. axis = Rank - 2.
if (axis < 0)
{
axis += output_rank;
}
_axis = ToARMComputeAxis(output_rank, axis).value();
_cl_reshape_vector.resize(nr_inputs);
::arm_compute::TensorShape subTensor_shape{};
for (int i = 0; i < output_rank; i++)
{
if (i != _axis)
{
subTensor_shape.set(i, _output->info()->tensor_shape()[i]);
}
else
{
subTensor_shape.set(i, 1);
}
}
auto subTensor_offset = ::arm_compute::Coordinates{};
subTensor_offset.set_num_dimensions(output_rank);
for (int i = 0; i < input_vector.size(); i++)
{
_input_vector.push_back(input_vector[i]);
subTensor_offset[_axis] = i;
auto temp_tensor = std::make_shared<::arm_compute::CLSubTensor>(
CAST_CL(_output), subTensor_shape, subTensor_offset, true);
_sub_tensor_vector.push_back(temp_tensor);
// configure to resize of input tensor in sub tensor offseted, dimension expansion will be
// automatic
_cl_permute_vector[i].configure(CAST_CL(_input_vector[i]), &_cl_permuted_vector[i], pv);
_cl_reshape_vector[i].configure(&_cl_permuted_vector[i], _sub_tensor_vector[i].get());
_cl_permuted_vector[i].allocator()->allocate();
}
}
void SimplePackLayer::run(void)
{
for (int i = 0; i < _input_vector.size(); i++)
{
_cl_permute_vector[i].run();
_cl_reshape_vector[i].run();
}
}
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