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 iterating the values of a non-opaque ElementsAttr, with all of the types currently supported by DenseElementsAttr. This should help reduce the amount of specialization on DenseElementsAttr.
PiperOrigin-RevId: 264968151
This will allow iterating the values of a non-opaque ElementsAttr, with all of the types currently supported by DenseElementsAttr. This should help reduce the amount of specialization on DenseElementsAttr.
PiperOrigin-RevId: 264637293
tensorflow/mlir#58 fixed and exercised
verification of load/store ops using empty affine maps. Unfortunately,
it didn't exercise the creation of them. This PR addresses that aspect.
It removes the assumption of AffineMap having at least one result and
stores a pointer to MLIRContext as member of AffineMap.
* Add empty map support to affine.store + test
* Move MLIRContext to AffineMapStorage
Closestensorflow/mlir#74
PiperOrigin-RevId: 264416260
All 'getValue' variants now require that the index is valid, queryable via 'isValidIndex'. 'getSplatValue' now requires that the attribute is a proper splat. This allows for querying these methods on DenseElementAttr with all possible value types; e.g. float, int, APInt, etc. This also allows for removing unnecessary conversions to Attribute that really want the underlying value.
PiperOrigin-RevId: 263437337
The current implementation only returns one element for the splat case, which often comes as a surprise; leading to subtle/confusing bugs. The new behavior will include an iterate over the full range of elements, as defined by the shaped type, by providing the splat value for each iterator index.
PiperOrigin-RevId: 262756780
SPIR-V has multiple constant instructions covering different
constant types:
* `OpConstantTrue` and `OpConstantFalse` for boolean constants
* `OpConstant` for scalar constants
* `OpConstantComposite` for composite constants
* `OpConstantNull` for null constants
* ...
We model them all with a single spv.constant op for uniformity
and friendliness to transformations. This does mean that when
doing (de)serialization, we need to poke spv.constant's type
to determine which SPIR-V binary instruction to use.
This CL only covers the case of bool and integer spv.constant.
The rest will follow.
PiperOrigin-RevId: 259311698
This cl standardizes the printing of the type of dialect attributes to work the same as other attribute kinds. The type of dialect attributes will trail the dialect specific portion:
`#` dialect-namespace `<` attr-data `>` `:` type
The attribute parsing hooks on Dialect have been updated to take an optionally null expected type for the attribute. This matches the respective parseAttribute hooks in the OpAsmParser.
PiperOrigin-RevId: 258661298
This allows for the attribute to hold symbolic references to other operations than FuncOp. This also allows for removing the dependence on FuncOp from the base Builder.
PiperOrigin-RevId: 257650017
Move the data members out of Function and into a new impl storage class 'FunctionStorage'. This allows for Function to become value typed, which will greatly simplify the transition of Function to FuncOp(given that FuncOp is also value typed).
PiperOrigin-RevId: 255983022
This allows for iterating over the internal elements via an iterator_range of Attribute, and also allows for removing the final SmallVectorImpl based 'getValues' method.
PiperOrigin-RevId: 255309555
Now that Locations are attributes, they have direct access to the MLIR context. This allows for simplifying error emission by removing unnecessary context lookups.
PiperOrigin-RevId: 255112791
This iterator is useful for implementing random access iterators based upon an index and an object pointer. Moving it to STLExtras allows for reuse elsewhere throughout the codebase, e.g. simplifying the DenseElementsAttr iterators.
PiperOrigin-RevId: 255020377
* 'get' methods that allow constructing from an ArrayRef of integer or floating point values.
* A 'reshape' method to allow for changing the shape without changing the underlying data.
PiperOrigin-RevId: 252067898
We want to support 64-bit shapes (even when the compiler is on a 32-bit architecture). Using int64_t consistently allows us to sidestep the bugginess of unsigned arithmetic.
Still unsigned: kind, memory space, and bit width. The first two are basically enums. We could have a discussion about the last one, but it's basically just a very large enum as well and we're not doing any math on it, I think.
--
PiperOrigin-RevId: 250985791
* 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.
--
PiperOrigin-RevId: 249510802
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
