This CL enables verification code generation for variadic operands and results.
In verify(), we use fallback getter methods to access all the dynamic values
belonging to one static variadic operand/result to reuse the value range
calculation there.
PiperOrigin-RevId: 252288219
* Add a getCurrentLocation that returns the location directly.
* Add parseOperandList/parseTrailingOperandList overloads without the required operand count.
PiperOrigin-RevId: 251585488
These were just introduced by a previous CL moving MemRef getRank to return int64_t. size_t could be smaller than 64 bits and in equals comparisons, signed vs unsigned doesn't matter. In these cases, we know right now that the particular int64_t is not larger than max size_t (because it currently comes directly from a size() call), the alternative cast plus equals comparison is always safe, so we might as well do it that way and no longer require reasoning deeper into the callstack.
We are already assuming that size() calls fit into int64_t in a number of other cases like the aforementioned getRank() (since exabytes of RAM are rare). If we want to avoid this assumption we will have to come up with a principled way to do it throughout.
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PiperOrigin-RevId: 250980297
* There is no longer a need to explicitly remap function attrs.
- This removes a potentially expensive call from the destructor of Function.
- This will enable some interprocedural transformations to now run intraprocedurally.
- This wasn't scalable and forces dialect defined attributes to override
a virtual function.
* Replacing a function is now a trivial operation.
* This is a necessary first step to representing functions as operations.
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PiperOrigin-RevId: 249510802
Make it clear that it cares about the aggregate type being a vector or tensor and not just that it has a shape.
Remove redundant validation from the custom method that is now covered by the tablegen'ed verification
This is related to making MemRefs a ShapedType as well.
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PiperOrigin-RevId: 248610443
This is in preparation for making it also support/be a parent class of MemRefType. MemRefs have similar shape/rank/element semantics and it would be useful to be able to use these same utilities for them.
This CL should not change any semantics and only change variables, types, string literals, and comments. In follow-up CLs I will prepare all callers to handle MemRef types or remove their dependence on ShapedType.
Discussion/Rationale in https://groups.google.com/a/tensorflow.org/forum/#!topic/mlir/cHLoyfGu8y8
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PiperOrigin-RevId: 248476449
This closely mirrors the llvm fcmp instruction, defining 16 different predicates
Constant folding is unsupported for NaN and Inf because there's no way to represent those as constants at the moment
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PiperOrigin-RevId: 246932358
Add ConstantOp's Op Definition Spec. Currently we don't use convertFromStorage in the generated patterns and so needed to add a few casts to support patterns restricted to ElementsAttrs and to compensate for old rules where we defined ConstantOp to have a ElementsAttr to simplify writing the pattern.
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PiperOrigin-RevId: 246361555
Instead, fold such operations. This way callers don't need to conditionally create cast operations depending on if a value already has the target type.
Also, introduce areCastCompatible to allow cast users to verify that the generated op will be valid before creating the operation.
TESTED with unit tests
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PiperOrigin-RevId: 245606133
This adds parsing, printing and some folding/canonicalization.
Also extends rewriting of subi %0, %0 to handle vectors and tensors.
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PiperOrigin-RevId: 242448164
* dyn_cast_or_null
- This will first check if the operation is null before trying to 'dyn_cast':
Value *v = ...;
if (auto forOp = dyn_cast_or_null<AffineForOp>(v->getDefiningOp()))
...
* isa_nonnull
- This will first check if the pointer is null before trying to 'isa':
Value *v = ...;
if (isa_nonnull<AffineForOp>(v->getDefiningOp());
...
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PiperOrigin-RevId: 242171343
