Currently the builtin dialect is the default namespace used for parsing
and printing. As such module and func don't need to be prefixed.
In the case of some dialects that defines new regions for their own
purpose (like SpirV modules for example), it can be beneficial to
change the default dialect in order to improve readability.
Differential Revision: https://reviews.llvm.org/D107236
- Enables inferring return type for ConstShape, takes into account valid return types;
- The compatible return type function could be reused, leaving that for next use refactoring;
Differential Revision: https://reviews.llvm.org/D102182
This corresponds with the previous work to make shape.broadcast nary.
Additionally, simplify the ConvertShapeConstraints pass. It now doesn't
lower an implicit shape.is_broadcastable. This is still the same in
combination with shape-to-standard when the 2 passes are used in either
order.
Differential Revision: https://reviews.llvm.org/D96401
Enable querying shape function library ops from the module. Currently
supports singular or array of them (as long as array has all unique ops
in mappings). The preferred canonical form would have one library, but
given the invariant on the mapping, this can easily be achieved by a
simple merging pass.
Preferred the attribute approach vs naming convention as these could be
added in multiple different ways.
In a context in which `shape.broadcast` is known not to produce an error value,
we want it to operate solely on extent tensors. The operation's behavior is
then undefined in the error case as the result type cannot hold this value.
Differential Revision: https://reviews.llvm.org/D84933
Based on https://reviews.llvm.org/D84439 but less restrictive, else we
don't allow shape_of to be able to produce a ranked output and doesn't
allow for iterative refinement here. We can consider making it more
restrictive later.
The operation `shape.shape_of` now returns an extent tensor `tensor<?xindex>` in
cases when no error are possible. All consuming operation will eventually accept
both, shapes and extent tensors.
Differential Revision: https://reviews.llvm.org/D84160