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Silenced some compilation warnings triggered by nvcc

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This commit is contained in:
Benoit Steiner 2015-12-17 13:39:01 -08:00
parent 40e6250fc3
commit 4aac55f684
3 changed files with 20 additions and 9 deletions
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7
unsupported/Eigen/CXX11/src/Tensor/TensorDeviceCuda.h
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@ -238,11 +238,14 @@ struct GpuDevice {
};
#ifndef __CUDA_ARCH__
#define LAUNCH_CUDA_KERNEL(kernel, gridsize, blocksize, sharedmem, device, ...) \
(kernel) <<< (gridsize), (blocksize), (sharedmem), (device).stream() >>> (__VA_ARGS__); \
assert(cudaGetLastError() == cudaSuccess);
#else
#define LAUNCH_CUDA_KERNEL(...) \
eigen_assert(false && "Cannot launch a kernel from another kernel");
#endif
// FIXME: Should be device and kernel specific.
#ifdef __CUDACC__

16
unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h
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@ -156,14 +156,14 @@ template <typename Expression>
class TensorExecutor<Expression, GpuDevice, false> {
public:
typedef typename Expression::Index Index;
static void run(const Expression& expr, const GpuDevice& device);
EIGEN_DEVICE_FUNC static void run(const Expression& expr, const GpuDevice& device);
};
template <typename Expression>
class TensorExecutor<Expression, GpuDevice, true> {
public:
typedef typename Expression::Index Index;
static void run(const Expression& expr, const GpuDevice& device);
EIGEN_DEVICE_FUNC static void run(const Expression& expr, const GpuDevice& device);
};
#if defined(__CUDACC__)
@ -213,8 +213,9 @@ EigenMetaKernel_Vectorizable(Evaluator memcopied_eval, Index size) {
/*static*/
template <typename Expression>
inline void TensorExecutor<Expression, GpuDevice, false>::run(const Expression& expr, const GpuDevice& device)
EIGEN_DEVICE_FUNC inline void TensorExecutor<Expression, GpuDevice, false>::run(const Expression& expr, const GpuDevice& device)
{
#ifndef __CUDA_ARCH__
TensorEvaluator<Expression, GpuDevice> evaluator(expr, device);
const bool needs_assign = evaluator.evalSubExprsIfNeeded(NULL);
if (needs_assign)
@ -227,13 +228,17 @@ inline void TensorExecutor<Expression, GpuDevice, false>::run(const Expression&
LAUNCH_CUDA_KERNEL((EigenMetaKernel_NonVectorizable<TensorEvaluator<Expression, GpuDevice>, Index>), num_blocks, block_size, 0, device, evaluator, size);
}
evaluator.cleanup();
#else
eigen_assert(false && "Cannot launch a kernel from another kernel");
#endif
}
/*static*/
template<typename Expression>
inline void TensorExecutor<Expression, GpuDevice, true>::run(const Expression& expr, const GpuDevice& device)
EIGEN_DEVICE_FUNC inline void TensorExecutor<Expression, GpuDevice, true>::run(const Expression& expr, const GpuDevice& device)
{
#ifndef __CUDA_ARCH__
TensorEvaluator<Expression, GpuDevice> evaluator(expr, device);
const bool needs_assign = evaluator.evalSubExprsIfNeeded(NULL);
if (needs_assign)
@ -246,6 +251,9 @@ inline void TensorExecutor<Expression, GpuDevice, true>::run(const Expression& e
LAUNCH_CUDA_KERNEL((EigenMetaKernel_Vectorizable<TensorEvaluator<Expression, GpuDevice>, Index>), num_blocks, block_size, 0, device, evaluator, size);
}
evaluator.cleanup();
#else
eigen_assert(false && "Cannot launch a kernel from another kernel");
#endif
}
#endif // __CUDACC__

6
unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
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@ -454,7 +454,7 @@ struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType>, Device>
input_strides[i] = input_strides[i + 1] * input_dims[i + 1];
}
}
int outputIndex = 0;
int reduceIndex = 0;
for (int i = 0; i < NumInputDims; ++i) {
@ -473,13 +473,13 @@ struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType>, Device>
m_preservedStrides[0] = internal::array_prod(input_dims);
}
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
typedef typename internal::remove_const<typename XprType::CoeffReturnType>::type CoeffReturnType;
typedef typename internal::remove_const<typename XprType::PacketReturnType>::type PacketReturnType;
EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType* data) {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType* data) {
m_impl.evalSubExprsIfNeeded(NULL);
// Use the FullReducer if possible.