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Restore Tensor support for non c++11 compilers

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This commit is contained in:
Benoit Steiner 2016-04-29 15:19:19 -07:00
parent ba32ded021
commit c07404f6a1
2 changed files with 9 additions and 9 deletions
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10
unsupported/Eigen/CXX11/src/Tensor/TensorCostModel.h
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@ -34,25 +34,25 @@ class TensorOpCost {
template <typename ArgType> template <typename ArgType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static int MulCost() { EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static int MulCost() {
return internal::functor_traits< return internal::functor_traits<
internal::scalar_product_op<ArgType, ArgType>>::Cost; internal::scalar_product_op<ArgType, ArgType> >::Cost;
} }
template <typename ArgType> template <typename ArgType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static int AddCost() { EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static int AddCost() {
return internal::functor_traits<internal::scalar_sum_op<ArgType>>::Cost; return internal::functor_traits<internal::scalar_sum_op<ArgType> >::Cost;
} }
template <typename ArgType> template <typename ArgType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static int DivCost() { EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static int DivCost() {
return internal::functor_traits< return internal::functor_traits<
internal::scalar_quotient_op<ArgType, ArgType>>::Cost; internal::scalar_quotient_op<ArgType, ArgType> >::Cost;
} }
template <typename ArgType> template <typename ArgType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static int ModCost() { EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static int ModCost() {
return internal::functor_traits<internal::scalar_mod_op<ArgType>>::Cost; return internal::functor_traits<internal::scalar_mod_op<ArgType> >::Cost;
} }
template <typename SrcType, typename TargetType> template <typename SrcType, typename TargetType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static int CastCost() { EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static int CastCost() {
return internal::functor_traits< return internal::functor_traits<
internal::scalar_cast_op<SrcType, TargetType>>::Cost; internal::scalar_cast_op<SrcType, TargetType> >::Cost;
} }
TensorOpCost() : bytes_loaded_(0), bytes_stored_(0), compute_cycles_(0) {} TensorOpCost() : bytes_loaded_(0), bytes_stored_(0), compute_cycles_(0) {}

8
unsupported/test/cxx11_tensor_argmax.cpp
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@ -64,7 +64,7 @@ static void test_argmax_tuple_reducer()
Tensor<Tuple<DenseIndex, float>, 0, DataLayout> reduced; Tensor<Tuple<DenseIndex, float>, 0, DataLayout> reduced;
DimensionList<DenseIndex, 4> dims; DimensionList<DenseIndex, 4> dims;
reduced = index_tuples.reduce( reduced = index_tuples.reduce(
dims, internal::ArgMaxTupleReducer<Tuple<DenseIndex, float>>()); dims, internal::ArgMaxTupleReducer<Tuple<DenseIndex, float> >());
Tensor<float, 0, DataLayout> maxi = tensor.maximum(); Tensor<float, 0, DataLayout> maxi = tensor.maximum();
@ -74,7 +74,7 @@ static void test_argmax_tuple_reducer()
for (int d = 0; d < 3; ++d) reduce_dims[d] = d; for (int d = 0; d < 3; ++d) reduce_dims[d] = d;
Tensor<Tuple<DenseIndex, float>, 1, DataLayout> reduced_by_dims(7); Tensor<Tuple<DenseIndex, float>, 1, DataLayout> reduced_by_dims(7);
reduced_by_dims = index_tuples.reduce( reduced_by_dims = index_tuples.reduce(
reduce_dims, internal::ArgMaxTupleReducer<Tuple<DenseIndex, float>>()); reduce_dims, internal::ArgMaxTupleReducer<Tuple<DenseIndex, float> >());
Tensor<float, 1, DataLayout> max_by_dims = tensor.maximum(reduce_dims); Tensor<float, 1, DataLayout> max_by_dims = tensor.maximum(reduce_dims);
@ -96,7 +96,7 @@ static void test_argmin_tuple_reducer()
Tensor<Tuple<DenseIndex, float>, 0, DataLayout> reduced; Tensor<Tuple<DenseIndex, float>, 0, DataLayout> reduced;
DimensionList<DenseIndex, 4> dims; DimensionList<DenseIndex, 4> dims;
reduced = index_tuples.reduce( reduced = index_tuples.reduce(
dims, internal::ArgMinTupleReducer<Tuple<DenseIndex, float>>()); dims, internal::ArgMinTupleReducer<Tuple<DenseIndex, float> >());
Tensor<float, 0, DataLayout> mini = tensor.minimum(); Tensor<float, 0, DataLayout> mini = tensor.minimum();
@ -106,7 +106,7 @@ static void test_argmin_tuple_reducer()
for (int d = 0; d < 3; ++d) reduce_dims[d] = d; for (int d = 0; d < 3; ++d) reduce_dims[d] = d;
Tensor<Tuple<DenseIndex, float>, 1, DataLayout> reduced_by_dims(7); Tensor<Tuple<DenseIndex, float>, 1, DataLayout> reduced_by_dims(7);
reduced_by_dims = index_tuples.reduce( reduced_by_dims = index_tuples.reduce(
reduce_dims, internal::ArgMinTupleReducer<Tuple<DenseIndex, float>>()); reduce_dims, internal::ArgMinTupleReducer<Tuple<DenseIndex, float> >());
Tensor<float, 1, DataLayout> min_by_dims = tensor.minimum(reduce_dims); Tensor<float, 1, DataLayout> min_by_dims = tensor.minimum(reduce_dims);