blob: 4021fd8dedf3628191b5961f4648fe7161121fa2 [file] [log] [blame]
/*
* Copyright (c) 2018-2021 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 "src/cpu/operators/CpuConcatenate.h"
#include "src/cpu/kernels/CpuConcatenateBatchKernel.h"
#include "src/cpu/kernels/CpuConcatenateDepthKernel.h"
#include "src/cpu/kernels/CpuConcatenateHeightKernel.h"
#include "src/cpu/kernels/CpuConcatenateWidthKernel.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/runtime/NEON/NEScheduler.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"
#include "src/common/utils/Log.h"
#include "src/core/helpers/AutoConfiguration.h"
namespace arm_compute
{
namespace cpu
{
void CpuConcatenate::configure(const std::vector<const ITensorInfo *> &srcs_vector, ITensorInfo *dst, size_t axis)
{
ARM_COMPUTE_ERROR_ON(dst == nullptr);
ARM_COMPUTE_LOG_PARAMS(srcs_vector, dst, axis);
_axis = axis;
_num_srcs = srcs_vector.size();
TensorShape dst_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(srcs_vector, axis);
// Output auto inizialitation if not yet initialized
auto_init_if_empty(*dst, dst_shape, 1, srcs_vector[0]->data_type());
ARM_COMPUTE_ERROR_THROW_ON(CpuConcatenate::validate(srcs_vector, dst, axis));
unsigned int offset = 0;
for(unsigned int i = 0; i < _num_srcs; ++i)
{
switch(axis)
{
case Window::DimX:
{
auto kernel = std::make_unique<kernels::CpuConcatenateWidthKernel>();
kernel->configure(srcs_vector.at(i), offset, dst);
_concat_kernels.emplace_back(std::move(kernel));
break;
}
case Window::DimY:
{
auto kernel = std::make_unique<kernels::CpuConcatenateHeightKernel>();
kernel->configure(srcs_vector.at(i), offset, dst);
_concat_kernels.emplace_back(std::move(kernel));
break;
}
case Window::DimZ:
{
auto kernel = std::make_unique<kernels::CpuConcatenateDepthKernel>();
kernel->configure(srcs_vector.at(i), offset, dst);
_concat_kernels.emplace_back(std::move(kernel));
break;
}
case 3:
{
auto kernel = std::make_unique<kernels::CpuConcatenateBatchKernel>();
kernel->configure(srcs_vector.at(i), offset, dst);
_concat_kernels.emplace_back(std::move(kernel));
break;
}
default:
ARM_COMPUTE_ERROR("Axis not supported");
}
offset += srcs_vector.at(i)->dimension(axis);
}
}
Status CpuConcatenate::validate(const std::vector<const ITensorInfo *> &srcs_vector, const ITensorInfo *dst, size_t axis)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(dst);
ARM_COMPUTE_RETURN_ERROR_ON(srcs_vector.size() < 2);
unsigned int offset = 0;
for(const auto &src : srcs_vector)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src);
switch(axis)
{
case Window::DimX:
{
ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuConcatenateWidthKernel::validate(src, offset, dst));
break;
}
case Window::DimY:
{
ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuConcatenateHeightKernel::validate(src, offset, dst));
break;
}
case Window::DimZ:
{
ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuConcatenateDepthKernel::validate(src, offset, dst));
break;
}
case 3:
{
ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuConcatenateBatchKernel::validate(src, offset, dst));
break;
}
default:
ARM_COMPUTE_ERROR("Axis not supported");
}
offset += src->dimension(axis);
}
if(dst->total_size() != 0)
{
TensorShape dst_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(srcs_vector, axis);
ARM_COMPUTE_RETURN_ERROR_ON(dst_shape.total_size() != dst->tensor_shape().total_size());
}
return Status{};
}
void CpuConcatenate::run(ITensorPack &tensors)
{
if(tensors.empty())
{
ARM_COMPUTE_ERROR("No inputs provided");
}
if(static_cast<int>(tensors.size() - 1) != static_cast<int>(_num_srcs))
{
ARM_COMPUTE_ERROR("Configured with different number of inputs");
}
int i = 0;
for(auto &k : _concat_kernels)
{
ITensorPack pack;
pack.add_tensor(TensorType::ACL_SRC, tensors.get_const_tensor(ACL_SRC_VEC + i));
pack.add_tensor(TensorType::ACL_DST, tensors.get_tensor(ACL_DST));
NEScheduler::get().schedule_op(k.get(), Window::DimY, k->window(), pack);
++i;
}
}
} // namespace cpu
} // namespace arm_compute