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/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
* Copyright 2018 The TensorFlow Authors. 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 "kernels/LogicalAnd.h"
#include "kernels/Utils.h"
#include "kernels/BinaryOpCommon.h"
namespace luci_interpreter
{
namespace kernels
{
LogicalAnd::LogicalAnd(const Tensor *input1, const Tensor *input2, Tensor *output)
: Kernel({input1, input2}, {output})
{
}
void LogicalAnd::configure()
{
LUCI_INTERPRETER_CHECK(input1()->element_type() == input2()->element_type());
LUCI_INTERPRETER_CHECK(input1()->element_type() == output()->element_type());
output()->resize(calculateShapeForBroadcast(input1()->shape(), input2()->shape()));
}
void LogicalAnd::execute() const
{
switch (input1()->element_type())
{
case DataType::BOOL:
evalLogicalAnd();
break;
default:
throw std::runtime_error("Unsupported type.");
}
}
inline void LogicalAnd::evalLogicalAnd() const
{
BinaryOpBroadcastSlow(getTensorShape(input1()), getTensorData<bool>(input1()),
getTensorShape(input2()), getTensorData<bool>(input2()),
getTensorShape(output()), getTensorData<bool>(output()),
[](bool x, bool y) { return x && y; });
}
} // namespace kernels
} // namespace luci_interpreter
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