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RAJA
RAJA provides a collection of platform portability abstractions for C++ HPC applications.
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#include <TensorScalarLiteral.hpp>
Public Types | |
| using | self_type = TensorScalarLiteral< T > |
| using | tensor_type = RAJA::expt::ScalarRegister< T > |
| using | element_type = T |
| using | result_type = T |
| using | index_type = RAJA::Index_type |
Public Types inherited from RAJA::internal::expt::ET::TensorExpressionBase< TensorScalarLiteral< T > > | |
| using | self_type = TensorScalarLiteral< T > |
Static Public Attributes | |
| static constexpr camp::idx_t | s_num_dims = 0 |
| using RAJA::internal::expt::ET::TensorScalarLiteral< T >::self_type = TensorScalarLiteral<T> |
| using RAJA::internal::expt::ET::TensorScalarLiteral< T >::tensor_type = RAJA::expt::ScalarRegister<T> |
| using RAJA::internal::expt::ET::TensorScalarLiteral< T >::element_type = T |
| using RAJA::internal::expt::ET::TensorScalarLiteral< T >::result_type = T |
| using RAJA::internal::expt::ET::TensorScalarLiteral< T >::index_type = RAJA::Index_type |
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inlineexplicitconstexprnoexcept |
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inlineconstexpr |
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inline |
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inline |
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staticconstexpr |