* [Biketal22] Aart J.C. Bik, Penporn Koanantakool, Tatiana Shpeisman,
Nicolas Vasilache, Bixia Zheng, and Fredrik Kjolstad. Compiler Support
for Sparse Tensor Computations in MLIR. ACM Transactions on Architecture
- and Code Optimization, June, 2022 (see https://dl.acm.org/doi/10.1145/3544559).
+ and Code Optimization, June, 2022. See: https://dl.acm.org/doi/10.1145/3544559
* [Chou18] Stephen Chou, Fredrik Berg Kjolstad, and Saman Amarasinghe.
Format Abstraction for Sparse Tensor Algebra Compilers. Proceedings of
the ACM on Programming Languages, October 2018.
```
Example returning +1 for existing values and -1 for missing values:
+
```mlir
%result = sparse_tensor.unary %a : f64 to i32
present={
Example showing a structural inversion (existing values become missing in
the output, while missing values are filled with 1):
+
```mlir
%result = sparse_tensor.unary %a : f64 to i64
present={}
argument types.
Note that this operation is only required for custom reductions beyond the
-
standard operations (add, mul, and, or, etc). The `linalg.generic`
`iterator_types` defines which indices are being reduced. When the associated
operands are used in an operation, a reduction will occur. The use of this