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/*
* Copyright (c) 2019 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 "ConstantInitializer.h"
namespace onert
{
namespace backend
{
namespace acl_neon
{
ConstantInitializer::ConstantInitializer(const ir::Operands &operands,
const std::shared_ptr<ITensorRegistry> &tensor_reg)
: acl_common::AclConstantInitializer{operands, tensor_reg}
{
// DO NOTHING
}
void ConstantInitializer::visit(const ir::operation::SpaceToBatchND &node)
{
const auto &block_size_index = node.getInputs().at(ir::operation::SpaceToBatchND::BLOCK_SIZE);
const auto &block_size_obj = _operands.at(block_size_index);
if (block_size_obj.isConstant())
{
_init_map[block_size_index] = [](const ir::Operand &model_obj, backend::ITensor &obj) {
assert(model_obj.data());
const auto &shape = model_obj.shape();
const auto base = reinterpret_cast<const int32_t *>(model_obj.data()->base());
assert(model_obj.shape().rank() == 1);
obj.access([&](ITensor &tensor) {
for (size_t i = 0; i < shape.num_elements(); ++i)
{
const int32_t value = base[shape.num_elements() - i - 1];
int32_t *into = reinterpret_cast<int32_t *>(tensor.buffer() +
tensor.calcOffset({static_cast<int32_t>(i)}));
*into = value;
}
});
};
}
const auto &paddings_index = node.getInputs().at(ir::operation::SpaceToBatchND::PADDINGS);
const auto &paddings_obj = _operands.at(paddings_index);
if (paddings_obj.isConstant())
{
_init_map[paddings_index] = [](const ir::Operand &model_obj, backend::ITensor &obj) {
assert(model_obj.data());
const auto &shape = model_obj.shape();
const auto base = reinterpret_cast<const int32_t *>(model_obj.data()->base());
assert(model_obj.shape().rank() == 2);
assert(shape.dim(0) == 2);
assert(shape.dim(1) == 2);
obj.access([&](ITensor &tensor) {
for (auto i = 0; i < shape.dim(0); ++i)
{
for (auto j = 0; j < shape.dim(1); ++j)
{
const int32_t value = base[i * 2 + j];
int32_t *into = reinterpret_cast<int32_t *>(
// The coordinates of NETensor are different from the coordiantes of CLTensor in
// this operand.
// NEON : {j, reversed i}
// CL : {reversed i, j}
tensor.buffer() + tensor.calcOffset({j, shape.dim(0) - i - 1}));
*into = value;
}
}
});
};
}
}
} // namespace acl_neon
} // namespace backend
} // namespace onert
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