mirror/eigen
2
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2024-12-27 07:29:52 +08:00
Code Issues Packages Projects Releases Wiki Activity

Fixed a number of compilation warnings generated by the cuda tests

Browse Source
This commit is contained in:
Benoit Steiner 2016-01-31 20:09:41 -08:00
parent 6720b38fbf
commit e80ed948e1
3 changed files with 42 additions and 9 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

39
unsupported/Eigen/CXX11/src/Core/util/EmulateArray.h
View File

@ -25,6 +25,16 @@ template <typename T, size_t n> class array {
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const T& operator[] (size_t index) const { return values[index]; }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE T& front() { return values[0]; }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const T& front() const { return values[0]; }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE T& back() { return values[n-1]; }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const T& back() const { return values[n-1]; }
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
static std::size_t size() { return n; }
@ -123,13 +133,33 @@ template <typename T> class array<T, 0> {
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE T& operator[] (size_t) {
eigen_assert(false && "Can't index a zero size array");
return *static_cast<T*>(NULL);
return dummy;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const T& operator[] (size_t) const {
eigen_assert(false && "Can't index a zero size array");
return *static_cast<const T*>(NULL);
return dummy;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE T& front() {
eigen_assert(false && "Can't index a zero size array");
return dummy;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const T& front() const {
eigen_assert(false && "Can't index a zero size array");
return dummy;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE T& back() {
eigen_assert(false && "Can't index a zero size array");
return dummy;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const T& back() const {
eigen_assert(false && "Can't index a zero size array");
return dummy;
}
static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE std::size_t size() { return 0; }
@ -142,6 +172,9 @@ template <typename T> class array<T, 0> {
eigen_assert(l.size() == 0);
}
#endif
private:
T dummy;
};
namespace internal {

8
unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h
View File

@ -21,7 +21,7 @@ namespace Eigen {
*/
namespace internal {
template <typename Index, typename InputDims, size_t NumKernelDims, int Layout>
template <typename Index, typename InputDims, int NumKernelDims, int Layout>
class IndexMapper {
public:
IndexMapper(const InputDims& input_dims, const array<Index, NumKernelDims>& kernel_dims,
@ -123,7 +123,7 @@ class IndexMapper {
}
inputIndex += p * m_inputStrides[NumKernelDims];
} else {
int limit = 0;
std::ptrdiff_t limit = 0;
if (NumKernelDims < NumDims) {
limit = NumDims - NumKernelDims - 1;
}
@ -147,7 +147,7 @@ class IndexMapper {
}
outputIndex += p * m_outputStrides[NumKernelDims];
} else {
int limit = 0;
std::ptrdiff_t limit = 0;
if (NumKernelDims < NumDims) {
limit = NumDims - NumKernelDims - 1;
}
@ -206,7 +206,7 @@ class IndexMapper {
}
private:
static const size_t NumDims = internal::array_size<InputDims>::value;
static const int NumDims = internal::array_size<InputDims>::value;
array<Index, NumDims> m_inputStrides;
array<Index, NumDims> m_outputStrides;
array<Index, NumDims> m_cudaInputStrides;

4
unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
View File

@ -463,7 +463,7 @@ struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType>, Device>
m_outputStrides[i] = m_outputStrides[i - 1] * m_dimensions[i - 1];
}
} else {
m_outputStrides[NumOutputDims - 1] = 1;
m_outputStrides.back() = 1;
for (int i = NumOutputDims - 2; i >= 0; --i) {
m_outputStrides[i] = m_outputStrides[i + 1] * m_dimensions[i + 1];
}
@ -479,7 +479,7 @@ struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType>, Device>
input_strides[i] = input_strides[i-1] * input_dims[i-1];
}
} else {
input_strides[NumInputDims - 1] = 1;
input_strides.back() = 1;
for (int i = NumInputDims - 2; i >= 0; --i) {
input_strides[i] = input_strides[i + 1] * input_dims[i + 1];
}