/usr/include/thrust/transform_reduce.h is in libthrust-dev 1.7.0-2.
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* Copyright 2008-2012 NVIDIA Corporation
*
* 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.
*/
/*! \file transform_reduce.h
* \brief Fused transform / reduction
*/
#pragma once
#include <thrust/detail/config.h>
#include <thrust/detail/execution_policy.h>
namespace thrust
{
/*! \addtogroup reductions
* \{
* \addtogroup transformed_reductions Transformed Reductions
* \ingroup reductions
* \{
*/
/*! \p transform_reduce fuses the \p transform and \p reduce operations.
* \p transform_reduce is equivalent to performing a transformation defined by
* \p unary_op into a temporary sequence and then performing \p reduce on the
* transformed sequence. In most cases, fusing these two operations together is
* more efficient, since fewer memory reads and writes are required.
*
* \p transform_reduce performs a reduction on the transformation of the
* sequence <tt>[first, last)</tt> according to \p unary_op. Specifically,
* \p unary_op is applied to each element of the sequence and then the result
* is reduced to a single value with \p binary_op using the initial value
* \p init. Note that the transformation \p unary_op is not applied to
* the initial value \p init. The order of reduction is not specified,
* so \p binary_op must be both commutative and associative.
*
* The algorithm's execution is parallelized as determined by \p exec.
*
* \param exec The execution policy to use for parallelization.
* \param first The beginning of the sequence.
* \param last The end of the sequence.
* \param unary_op The function to apply to each element of the input sequence.
* \param init The result is initialized to this value.
* \param binary_op The reduction operation.
* \return The result of the transformed reduction.
*
* \tparam DerivedPolicy The name of the derived execution policy.
* \tparam InputIterator is a model of <a href="http://www.sgi.com/tech/stl/InputIterator.html">Input Iterator</a>,
* and \p InputIterator's \c value_type is convertible to \p UnaryFunction's \c argument_type.
* \tparam UnaryFunction is a model of <a href="http://www.sgi.com/tech/stl/UnaryFunction.html">Unary Function</a>,
* and \p UnaryFunction's \c result_type is convertible to \c OutputType.
* \tparam OutputType is a model of <a href="http://www.sgi.com/tech/stl/Assignable.html">Assignable</a>,
* and is convertible to \p BinaryFunction's \c first_argument_type and \c second_argument_type.
* \tparam BinaryFunction is a model of <a href="http://www.sgi.com/tech/stl/BinaryFunction.html">Binary Function</a>,
* and \p BinaryFunction's \c result_type is convertible to \p OutputType.
*
* The following code snippet demonstrates how to use \p transform_reduce
* to compute the maximum value of the absolute value of the elements
* of a range using the \p thrust::host execution policy for parallelization:
*
* \code
* #include <thrust/transform_reduce.h>
* #include <thrust/functional.h>
* #include <thrust/execution_policy.h>
*
* template<typename T>
* struct absolute_value : public unary_function<T,T>
* {
* __host__ __device__ T operator()(const T &x) const
* {
* return x < T(0) ? -x : x;
* }
* };
*
* ...
*
* int data[6] = {-1, 0, -2, -2, 1, -3};
* int result = thrust::transform_reduce(thrust::host,
* data, data + 6,
* absolute_value<int>(),
* 0,
* thrust::maximum<int>());
* // result == 3
* \endcode
*
* \see \c transform
* \see \c reduce
*/
template<typename DerivedPolicy,
typename InputIterator,
typename UnaryFunction,
typename OutputType,
typename BinaryFunction>
OutputType transform_reduce(const thrust::detail::execution_policy_base<DerivedPolicy> &exec,
InputIterator first,
InputIterator last,
UnaryFunction unary_op,
OutputType init,
BinaryFunction binary_op);
/*! \p transform_reduce fuses the \p transform and \p reduce operations.
* \p transform_reduce is equivalent to performing a transformation defined by
* \p unary_op into a temporary sequence and then performing \p reduce on the
* transformed sequence. In most cases, fusing these two operations together is
* more efficient, since fewer memory reads and writes are required.
*
* \p transform_reduce performs a reduction on the transformation of the
* sequence <tt>[first, last)</tt> according to \p unary_op. Specifically,
* \p unary_op is applied to each element of the sequence and then the result
* is reduced to a single value with \p binary_op using the initial value
* \p init. Note that the transformation \p unary_op is not applied to
* the initial value \p init. The order of reduction is not specified,
* so \p binary_op must be both commutative and associative.
*
* \param first The beginning of the sequence.
* \param last The end of the sequence.
* \param unary_op The function to apply to each element of the input sequence.
* \param init The result is initialized to this value.
* \param binary_op The reduction operation.
* \return The result of the transformed reduction.
*
* \tparam InputIterator is a model of <a href="http://www.sgi.com/tech/stl/InputIterator.html">Input Iterator</a>,
* and \p InputIterator's \c value_type is convertible to \p UnaryFunction's \c argument_type.
* \tparam UnaryFunction is a model of <a href="http://www.sgi.com/tech/stl/UnaryFunction.html">Unary Function</a>,
* and \p UnaryFunction's \c result_type is convertible to \c OutputType.
* \tparam OutputType is a model of <a href="http://www.sgi.com/tech/stl/Assignable.html">Assignable</a>,
* and is convertible to \p BinaryFunction's \c first_argument_type and \c second_argument_type.
* \tparam BinaryFunction is a model of <a href="http://www.sgi.com/tech/stl/BinaryFunction.html">Binary Function</a>,
* and \p BinaryFunction's \c result_type is convertible to \p OutputType.
*
* The following code snippet demonstrates how to use \p transform_reduce
* to compute the maximum value of the absolute value of the elements
* of a range.
*
* \code
* #include <thrust/transform_reduce.h>
* #include <thrust/functional.h>
*
* template<typename T>
* struct absolute_value : public unary_function<T,T>
* {
* __host__ __device__ T operator()(const T &x) const
* {
* return x < T(0) ? -x : x;
* }
* };
*
* ...
*
* int data[6] = {-1, 0, -2, -2, 1, -3};
* int result = thrust::transform_reduce(data, data + 6,
* absolute_value<int>(),
* 0,
* thrust::maximum<int>());
* // result == 3
* \endcode
*
* \see \c transform
* \see \c reduce
*/
template<typename InputIterator,
typename UnaryFunction,
typename OutputType,
typename BinaryFunction>
OutputType transform_reduce(InputIterator first,
InputIterator last,
UnaryFunction unary_op,
OutputType init,
BinaryFunction binary_op);
/*! \} // end transformed_reductions
* \} // end reductions
*/
} // end namespace thrust
#include <thrust/detail/transform_reduce.inl>
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