TensorBatchWrap shortcuts
- group NVCV_CPP_CUDATOOLS_TENSORBATCHWRAPS
Specializes TensorBatchWrap template classes to different dimensions.
The specializations have the last dimension as the only compile-time dimension as size of T. All other dimensions have run-time pitch and must be provided.
Template arguments:
T data type of each element in TensorBatchWrap
See also
Typedefs
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template<typename T, typename StrideType = int64_t>
using TensorBatch1DWrap = TensorBatchWrapT<T, StrideType, sizeof(T)>
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template<typename T, typename StrideType = int64_t>
using TensorBatch2DWrap = TensorBatchWrapT<T, StrideType, -1, sizeof(T)>
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template<typename T, typename StrideType = int64_t>
using TensorBatch3DWrap = TensorBatchWrapT<T, StrideType, -1, -1, sizeof(T)>
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template<typename T, typename StrideType = int64_t>
using TensorBatch4DWrap = TensorBatchWrapT<T, StrideType, -1, -1, -1, sizeof(T)>
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template<typename T, typename StrideType = int64_t>
using TensorBatch5DWrap = TensorBatchWrapT<T, StrideType, -1, -1, -1, -1, sizeof(T)>
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template<typename T, int N, typename StrideType = int64_t>
using TensorBatchNDWrap = std::conditional_t<N == 1, TensorBatch1DWrap<T, StrideType>, std::conditional_t<N == 2, TensorBatch2DWrap<T, StrideType>, std::conditional_t<N == 3, TensorBatch3DWrap<T, StrideType>, std::conditional_t<N == 4, TensorBatch4DWrap<T, StrideType>, std::conditional_t<N == 5, TensorBatch5DWrap<T, StrideType>, void>>>>>