This transforms the symbol lookups to O(1) from O(NM), greatly speeding up both passes. For a large MLIR module this shaved seconds off of the compilation time.
Differential Revision: https://reviews.llvm.org/D89522
This is a wrapper around vector of NamedAttributes that keeps track of whether sorted and does some minimal effort to remain sorted (doing more, e.g., appending attributes in sorted order, could be done in follow up). It contains whether sorted and if a DictionaryAttr is queried, it caches the returned DictionaryAttr along with whether sorted.
Change MutableDictionaryAttr to always return a non-null Attribute even when empty (reserve null cases for errors). To this end change the getter to take a context as input so that the empty DictionaryAttr could be queried. Also create one instance of the empty dictionary attribute that could be reused without needing to lock context etc.
Update infer type op interface to use DictionaryAttr and use NamedAttrList to avoid incurring multiple conversion costs.
Fix bug in sorting helper function.
Differential Revision: https://reviews.llvm.org/D79463
This allows for walking the operations nested directly within a region, without traversing nested regions.
Differential Revision: https://reviews.llvm.org/D79056
Makes the relationship and function clearer. Accordingly rename getAttrList to getMutableAttrDict.
Differential Revision: https://reviews.llvm.org/D79125
Summary: This is somewhat complex(annoying) as it involves directly tracking the uses within each of the callgraph nodes, and updating them as needed during inlining. The benefit of this is that we can have a more exact cost model, enable inlining some otherwise non-inlinable cases, and also ensure that newly dead callables are properly disposed of.
Differential Revision: https://reviews.llvm.org/D75476
The interfaces themselves aren't really analyses, they may be used by analyses though. Having them in Analysis can also create cyclic dependencies if an analysis depends on a specific dialect, that also provides one of the interfaces.
Differential Revision: https://reviews.llvm.org/D75867
Summary: This is the most common operation performed on a CallOpInterface. This just moves the existing functionality from the CallGraph so that other users can access it.
Differential Revision: https://reviews.llvm.org/D74250
Summary:
This enables tracking calls that cross symbol table boundaries. It also simplifies some of the implementation details of CallableOpInterface, i.e. there can only be one region within the callable operation.
Depends On D72042
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D72043
This is an initial step to refactoring the representation of OpResult as proposed in: https://groups.google.com/a/tensorflow.org/g/mlir/c/XXzzKhqqF_0/m/v6bKb08WCgAJ
This change will make it much simpler to incrementally transition all of the existing code to use value-typed semantics.
PiperOrigin-RevId: 286844725
This change allows for adding additional nested references to a SymbolRefAttr to allow for further resolving a symbol if that symbol also defines a SymbolTable. If a referenced symbol also defines a symbol table, a nested reference can be used to refer to a symbol within that table. Nested references are printed after the main reference in the following form:
symbol-ref-attribute ::= symbol-ref-id (`::` symbol-ref-id)*
Example:
module @reference {
func @nested_reference()
}
my_reference_op @reference::@nested_reference
Given that SymbolRefAttr is now more general, the existing functionality centered around a single reference is moved to a derived class FlatSymbolRefAttr. Followup commits will add support to lookups, rauw, etc. for scoped references.
PiperOrigin-RevId: 279860501
This will allow for inlining newly devirtualized calls, as well as give a more accurate cost model(when we have one). Currently canonicalization will only run for nodes that have no child edges, as the child nodes may be erased during canonicalization. We can support this in the future, but it requires more intricate deletion tracking.
PiperOrigin-RevId: 274011386
Using the two call interfaces, CallOpInterface and CallableOpInterface, this change adds support for an initial multi-level CallGraph. This call graph builds a set of nodes for each callable region, and connects them via edges. An edge may be any of the following types:
* Abstract
- An edge not produced by a call operation, used for connecting to internal nodes from external nodes.
* Call
- A call edge is an edge defined via a call-like operation.
* Child
- This is an artificial edge connecting nested callgraph nodes.
This callgraph will be used, and improved upon, to begin supporting more interesting interprocedural analyses and transformation. In a followup, this callgraph will be used to support more complex inlining support.
PiperOrigin-RevId: 270724968
These two operation interfaces will be used in a followup to support building a callgraph:
* CallOpInterface
- Operations providing this interface are call-like, and have a "call" target. A call target may be a symbol reference, via SymbolRefAttr, or a SSA value.
* CallableOpInterface
- Operations providing this interfaces define destinations to call-like operations, e.g. FuncOp. These operations may define any number of callable regions.
PiperOrigin-RevId: 270723300
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