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Diffstat (limited to 'tensorflow/core/kernels/reduction_ops_sum.cc')
| -rw-r--r-- | tensorflow/core/kernels/reduction_ops_sum.cc | 37 |
1 files changed, 37 insertions, 0 deletions
diff --git a/tensorflow/core/kernels/reduction_ops_sum.cc b/tensorflow/core/kernels/reduction_ops_sum.cc new file mode 100644 index 0000000000..82d685e225 --- /dev/null +++ b/tensorflow/core/kernels/reduction_ops_sum.cc @@ -0,0 +1,37 @@ +#include "tensorflow/core/kernels/reduction_ops_common.h" + +namespace tensorflow { + +#define REGISTER_CPU_KERNELS(type) \ + REGISTER_KERNEL_BUILDER( \ + Name("Sum").Device(DEVICE_CPU).TypeConstraint<type>("T"), \ + ReductionOp<CPUDevice, type, Eigen::internal::SumReducer<type>>); +TF_CALL_REAL_NUMBER_TYPES(REGISTER_CPU_KERNELS); +#undef REGISTER_CPU_KERNELS + +// NOTE: We should have mean(complex64,int32), too. But that needs to +// change Eigen::internal::MeanReducer to cast int to complex<float>. +// We don't see immediate need of mean(complex64,int32) anyway. +REGISTER_KERNEL_BUILDER( + Name("Sum").Device(DEVICE_CPU).TypeConstraint<complex64>("T"), + ReductionOp<CPUDevice, complex64, Eigen::internal::SumReducer<complex64>>); + +#if GOOGLE_CUDA + +#define REGISTER_GPU_KERNELS(type) \ + REGISTER_KERNEL_BUILDER( \ + Name("Sum") \ + .Device(DEVICE_GPU) \ + .TypeConstraint<type>("T") \ + .HostMemory("reduction_indices"), \ + ReductionOp<GPUDevice, type, Eigen::internal::SumReducer<type>>); +REGISTER_GPU_KERNELS(float); +#undef REGISTER_GPU_KERNELS + +REGISTER_KERNEL_BUILDER( + Name("Sum").Device(DEVICE_GPU).TypeConstraint<complex64>("T"), + ReductionOp<GPUDevice, complex64, Eigen::internal::SumReducer<complex64>>); + +#endif + +} // namespace tensorflow |