Matrix Inverse¶
Cached API¶
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template<typename TensorTypeAInv, typename TensorTypeA, MatInverseAlgo_t ALGO = MAT_INVERSE_ALGO_LU>
void matx::inv(TensorTypeAInv &a_inv, const TensorTypeA &a, cudaStream_t stream = 0)¶
Non-Cached API¶
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template<typename TensorTypeAInv, typename TensorTypeA, MatInverseAlgo_t ALGO = MAT_INVERSE_ALGO_LU>
class matx::matxInversePlan_t¶ Public Functions
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inline matxInversePlan_t(TensorTypeAInv &a_inv, const TensorTypeA &a)¶
Construct a matrix inverse handle
Creates a handle for executing a matrix inverse. There are several methods of performing a matrix inverse with various tradeoffs, so an algorithm type is supplied to give flexibility. To perform a matrix inversion the input matrix must be square, and non-singular.
- Template Parameters
T1 – Data type of A matrix
RANK – Rank of A matrix
ALGO – Inverse algorithm to use
- Parameters
a – Input tensor view
a_inv – Inverse of A (if it exists)
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inline ~matxInversePlan_t()¶
Inverse handle destructor
Destroys any helper data used for provider type and any workspace memory created
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inline void Exec(cudaStream_t stream)¶
Execute a matrix inverse
Execute a matrix inverse operation on matrix A with the chosen algorithm.
Note
Views being passed to matxInverse_t must be column-major order for now
- Template Parameters
T1 – Type of matrix A
- Parameters
stream – CUDA stream
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inline matxInversePlan_t(TensorTypeAInv &a_inv, const TensorTypeA &a)¶