Add labels to #ifdef, in TensorReductionCuda.h

This commit is contained in:
Hugh Perkins 2017-06-06 15:51:06 +01:00
parent 4343db84d8
commit 9341f258d4

View File

@ -62,9 +62,9 @@ __device__ EIGEN_ALWAYS_INLINE void atomicReduce(T* output, T accum, R& reducer)
else {
assert(0 && "Wordsize not supported");
}
#else
#else // __CUDA_ARCH__ >= 300
assert(0 && "Shouldn't be called on unsupported device");
#endif
#endif // __CUDA_ARCH__ >= 300
}
// We extend atomicExch to support extra data types
@ -98,15 +98,15 @@ __device__ inline void atomicReduce(half2* output, half2 accum, R<half>& reducer
}
}
}
#endif
#endif // EIGEN_HAS_CUDA_FP16
template <>
__device__ inline void atomicReduce(float* output, float accum, SumReducer<float>&) {
#if __CUDA_ARCH__ >= 300
atomicAdd(output, accum);
#else
#else // __CUDA_ARCH__ >= 300
assert(0 && "Shouldn't be called on unsupported device");
#endif
#endif // __CUDA_ARCH__ >= 300
}
@ -179,9 +179,9 @@ __global__ void FullReductionKernel(Reducer reducer, const Self input, Index num
// Let the last block reset the semaphore
atomicInc(semaphore, gridDim.x + 1);
}
#else
#else // __CUDA_ARCH__ >= 300
assert(0 && "Shouldn't be called on unsupported device");
#endif
#endif // __CUDA_ARCH__ >= 300
}
@ -268,7 +268,7 @@ __global__ void ReductionCleanupKernelHalfFloat(Op& reducer, half* output, half2
*output = tmp;
}
#endif
#endif // EIGEN_HAS_CUDA_FP16
template <typename Self, typename Op, typename OutputType, bool PacketAccess, typename Enabled = void>
struct FullReductionLauncher {
@ -335,7 +335,7 @@ struct FullReductionLauncher<Self, Op, Eigen::half, true> {
}
}
};
#endif
#endif // EIGEN_HAS_CUDA_FP16
template <typename Self, typename Op, bool Vectorizable>
@ -348,11 +348,11 @@ struct FullReducer<Self, Op, GpuDevice, Vectorizable> {
(internal::is_same<typename Self::CoeffReturnType, float>::value ||
internal::is_same<typename Self::CoeffReturnType, double>::value ||
(internal::is_same<typename Self::CoeffReturnType, Eigen::half>::value && reducer_traits<Op, GpuDevice>::PacketAccess));
#else
#else // EIGEN_HAS_CUDA_FP16
static const bool HasOptimizedImplementation = !Op::IsStateful &&
(internal::is_same<typename Self::CoeffReturnType, float>::value ||
internal::is_same<typename Self::CoeffReturnType, double>::value);
#endif
#endif // EIGEN_HAS_CUDA_FP16
template <typename OutputType>
static void run(const Self& self, Op& reducer, const GpuDevice& device, OutputType* output) {
@ -433,9 +433,9 @@ __global__ void InnerReductionKernel(Reducer reducer, const Self input, Index nu
}
}
}
#else
#else // __CUDA_ARCH__ >= 300
assert(0 && "Shouldn't be called on unsupported device");
#endif
#endif // __CUDA_ARCH__ >= 300
}
#ifdef EIGEN_HAS_CUDA_FP16
@ -533,7 +533,7 @@ __global__ void InnerReductionKernelHalfFloat(Reducer reducer, const Self input,
}
}
#endif
#endif // EIGEN_HAS_CUDA_FP16
template <typename Self, typename Op, typename OutputType, bool PacketAccess, typename Enabled = void>
struct InnerReductionLauncher {
@ -625,7 +625,7 @@ struct InnerReductionLauncher<Self, Op, Eigen::half, true> {
return false;
}
};
#endif
#endif // EIGEN_HAS_CUDA_FP16
template <typename Self, typename Op>
@ -638,11 +638,11 @@ struct InnerReducer<Self, Op, GpuDevice> {
(internal::is_same<typename Self::CoeffReturnType, float>::value ||
internal::is_same<typename Self::CoeffReturnType, double>::value ||
(internal::is_same<typename Self::CoeffReturnType, Eigen::half>::value && reducer_traits<Op, GpuDevice>::PacketAccess));
#else
#else // EIGEN_HAS_CUDA_FP16
static const bool HasOptimizedImplementation = !Op::IsStateful &&
(internal::is_same<typename Self::CoeffReturnType, float>::value ||
internal::is_same<typename Self::CoeffReturnType, double>::value);
#endif
#endif // EIGEN_HAS_CUDA_FP16
template <typename OutputType>
static bool run(const Self& self, Op& reducer, const GpuDevice& device, OutputType* output, typename Self::Index num_coeffs_to_reduce, typename Self::Index num_preserved_vals) {
@ -740,7 +740,7 @@ struct OuterReducer<Self, Op, GpuDevice> {
}
};
#endif
#endif // defined(EIGEN_USE_GPU) && defined(__CUDACC__)
} // end namespace internal