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/*
* Copyright (c) 2021, 2023 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/gpu/cl/operators/ClSoftmax.h"
#include "arm_compute/core/experimental/Types.h"
#include "arm_compute/core/ITensorPack.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
#include "src/common/utils/Log.h"
#include "src/core/helpers/MemoryHelpers.h"
#include "src/gpu/cl/kernels/ClSoftmaxKernel.h"
#include "src/gpu/cl/utils/ClAuxTensorHandler.h"
using namespace arm_compute::experimental;
namespace arm_compute
{
namespace opencl
{
ClSoftmax::ClSoftmax() : _aux_mem(InternalTensorIdx::COUNT)
{
}
void ClSoftmax::configure(const CLCompileContext &compile_context,
const ITensorInfo &src,
ITensorInfo &dst,
const SoftmaxKernelInfo &info)
{
ARM_COMPUTE_LOG_PARAMS(src, dst, info);
auto k = std::make_unique<kernels::ClSoftmaxKernel>();
k->configure(compile_context, src, dst, info);
_tmp_info = k->tmp_tensor_info();
_kernel = std::move(k);
_aux_mem[InternalTensorIdx::TMP] =
MemoryInfo(offset_int_vec(InternalTensorIdx::TMP), MemoryLifetime::Temporary, _tmp_info.total_size());
}
Status ClSoftmax::validate(const ITensorInfo &src, const ITensorInfo &dst, const SoftmaxKernelInfo &info)
{
return kernels::ClSoftmaxKernel::validate(src, dst, info);
}
void ClSoftmax::run(ITensorPack &tensors)
{
CLAuxTensorHandler tmp(offset_int_vec(InternalTensorIdx::TMP), _tmp_info, tensors);
tensors.add_tensor(TensorType::ACL_INT_0, tmp.get());
CLScheduler::get().enqueue_op(*_kernel, tensors, false);
}
experimental::MemoryRequirements ClSoftmax::workspace() const
{
return _aux_mem;
}
} // namespace opencl
} // namespace arm_compute
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