| Commit message (Collapse) | Author | Age | Files | Lines |
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Summary:
The visibility defines the structural reachability of the symbol within the IR. Symbols can define one of three visibilities:
* Public
The symbol \may be accessed from outside of the visible IR. We cannot assume that we can observe all of the uses of this symbol.
* Private
The symbol may only be referenced from within the operations in the current symbol table, via SymbolRefAttr.
* Nested
The symbol may be referenced by operations in symbol tables above the current symbol table, as long as each symbol table parent also defines a non-private symbol. This allows or referencing the symbol from outside of the defining symbol table, while retaining the ability for the compiler to see all uses.
These properties help to reason about the properties of a symbol, and will be used in a follow up to implement a dce pass on dead symbols.
A few examples of what this would look like in the IR are shown below:
module @public_module {
// This function can be accessed by 'live.user'
func @nested_function() attributes { sym_visibility = "nested" }
// This function cannot be accessed outside of 'public_module'
func @private_function() attributes { sym_visibility = "private" }
}
// This function can only be accessed from within this module.
func @private_function() attributes { sym_visibility = "private" }
// This function may be referenced externally.
func @public_function()
"live.user"() {uses = [@public_module::@nested_function,
@private_function,
@public_function]} : () -> ()
Depends On D72043
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D72044
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CallableOpInterface
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
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properly value-typed.
Summary: These were temporary methods used to simplify the transition.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D72548
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ValuePtr was a temporary typedef during the transition to a value-typed Value.
PiperOrigin-RevId: 286945714
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PiperOrigin-RevId: 286906740
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Value being value-typed.
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
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This is the block argument equivalent of the existing `getAsmResultNames` hook.
Closes tensorflow/mlir#329
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/329 from plaidml:flaub-region-arg-names fc7876f2d1335024e441083cd25263fd6247eb7d
PiperOrigin-RevId: 286523299
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This enables providing a default implementation of an interface method. This method is defined on the Trait that is attached to the operation, and thus has all of the same constraints and properties as any other interface method. This allows for interface authors to provide a conservative default implementation for certain methods, without requiring that all users explicitly define it. The default implementation can be specified via the argument directly after the interface method body:
StaticInterfaceMethod<
/*desc=*/"Returns whether two array of types are compatible result types for an op.",
/*retTy=*/"bool",
/*methodName=*/"isCompatibleReturnTypes",
/*args=*/(ins "ArrayRef<Type>":$lhs, "ArrayRef<Type>":$rhs),
/*methodBody=*/[{
return ConcreteOp::isCompatibleReturnTypes(lhs, rhs);
}],
/*defaultImplementation=*/[{
/// Returns whether two arrays are equal as strongest check for
/// compatibility by default.
return lhs == rhs;
}]
PiperOrigin-RevId: 286226054
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This change allows for DialectConversion to attempt folding as a mechanism to legalize illegal operations. This also expands folding support in OpBuilder::createOrFold to generate new constants when folding, and also enables it to work in the context of a PatternRewriter.
PiperOrigin-RevId: 285448440
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Closes tensorflow/mlir#304
PiperOrigin-RevId: 284568358
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Follows ValueRange in representing a generic abstraction over the different
ways to represent a range of Regions. This wrapper is not as ValueRange and only
considers the current cases of interest: MutableArrayRef<Region> and
ArrayRef<std::unique_ptr<Region>> as occurs during op construction vs op region
querying.
Note: ArrayRef<std::unique_ptr<Region>> allows for unset regions, so this range
returns a pointer to a Region instead of a Region.
PiperOrigin-RevId: 284563229
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This allows for users to provide operand_range and result_range in builder.create<> calls, instead of requiring an explicit copy into a separate data structure like SmallVector/std::vector.
PiperOrigin-RevId: 284360710
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Previously the error case was using a sentinel in the error case which was bad. Also make the one `build` invoke the other `build` to reuse verification there.
And follow up on suggestion to use formatv which I missed during previous review.
PiperOrigin-RevId: 284265762
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For ops with infer type op interface defined, generate version that calls the inferal method on build. This is intermediate step to removing special casing of SameOperandsAndResultType & FirstAttrDereivedResultType. After that would be generating the inference code, with the initial focus on shaped container types. In between I plan to refactor these a bit to reuse generated paths. The intention would not be to add the type inference trait in multiple places, but rather to take advantage of the current modelling in ODS where possible to emit it instead.
Switch the `inferReturnTypes` method to be static.
Skipping ops with regions here as I don't like the Region vs unique_ptr<Region> difference at the moment, and I want the infer return type trait to be useful for verification too. So instead, just skip it for now to avoid churn.
PiperOrigin-RevId: 284217913
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Note for broken code, the following transformations occurred:
ModuleManager::insert(Block::iterator, Operation*) - > SymbolTable::insert(Operation*, Block::iterator)
ModuleManager::lookupSymbol -> SymbolTable::lookup
ModuleManager::getModule() -> SymbolTable::getOp()
ModuleManager::getContext() -> SymbolTable::getOp()->getContext()
ModuleManager::* -> SymbolTable::*
PiperOrigin-RevId: 283944635
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Right now op argument matching in DRR is position-based, meaning we need to
specify N arguments for an op with N ODS-declared argument. This can be annoying
when we don't want to capture all the arguments. `$_` is to remedy the situation.
PiperOrigin-RevId: 283339992
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Certain operations can have multiple variadic operands and their size
relationship is not always known statically. For such cases, we need
a per-op-instance specification to divide the operands into logical
groups or segments. This can be modeled by attributes.
This CL introduces C++ trait AttrSizedOperandSegments for operands and
AttrSizedResultSegments for results. The C++ trait just guarantees
such size attribute has the correct type (1D vector) and values
(non-negative), etc. It serves as the basis for ODS sugaring that
with ODS argument declarations we can further verify the number of
elements match the number of ODS-declared operands and we can generate
handy getter methods.
PiperOrigin-RevId: 282467075
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EnumAttr should provide meaningful defaults so concrete instances
do not need to duplicate the fields.
PiperOrigin-RevId: 282398431
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multi-result operations.
This changes changes the OpDefinitionsGen to automatically add the OpAsmOpInterface for operations with multiple result groups using the provided ODS names. We currently just limit the generation to multi-result ops as most single result operations don't have an interesting name(result/output/etc.). An example is shown below:
// The following operation:
def MyOp : ... {
let results = (outs AnyType:$first, Variadic<AnyType>:$middle, AnyType);
}
// May now be printed as:
%first, %middle:2, %0 = "my.op" ...
PiperOrigin-RevId: 281834156
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'simplifyRegions'.
This moves the different canonicalizations of regions into one place and invokes them in the fixed-point iteration of the canonicalizer.
PiperOrigin-RevId: 281617072
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AsmPrinter.
This interface provides more fine-grained hooks into the AsmPrinter than the dialect interface, allowing for operations to define the asm name to use for results directly on the operations themselves. The hook is also expanded to enable defining named result "groups". Get a special name to use when printing the results of this operation.
The given callback is invoked with a specific result value that starts a
result "pack", and the name to give this result pack. To signal that a
result pack should use the default naming scheme, a None can be passed
in instead of the name.
For example, if you have an operation that has four results and you want
to split these into three distinct groups you could do the following:
setNameFn(getResult(0), "first_result");
setNameFn(getResult(1), "middle_results");
setNameFn(getResult(3), ""); // use the default numbering.
This would print the operation as follows:
%first_result, %middle_results:2, %0 = "my.op" ...
PiperOrigin-RevId: 281546873
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PiperOrigin-RevId: 281501234
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This method is needed for N->1 conversion patterns to retrieve remapped
Values used in the original N operations.
Closes tensorflow/mlir#237
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/237 from dcaballe:dcaballe/getRemappedValue 1f64fadcf2b203f7b336ff0c5838b116ae3625db
PiperOrigin-RevId: 281321881
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The `Operator` class keeps an `arguments` field, which contains pointers
to `operands` and `attributes` elements. Thus it must be populated after
`operands` and `attributes` are finalized so to have stable pointers.
SmallVector may re-allocate when still having new elements added, which
will invalidate pointers.
PiperOrigin-RevId: 280466896
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This refactors the implementation of block signature(type) conversion to not insert fake cast operations to perform the type conversion, but to instead create a new block containing the proper signature. This has the benefit of enabling the use of pre-computed analyses that rely on mapping values. It also leads to a much cleaner implementation overall. The major user facing change is that applySignatureConversion will now replace the entry block of the region, meaning that blocks generally shouldn't be cached over calls to applySignatureConversion.
PiperOrigin-RevId: 280226936
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It is often helpful to inspect the operation that the error/warning/remark/etc. originated from, especially in the context of debugging or in the case of a verifier failure. This change adds an option 'mlir-print-op-on-diagnostic' that attaches the operation as a note to any diagnostic that is emitted on it via Operation::emit(Error|Warning|Remark). In the case of an error, the operation is printed in the generic form.
PiperOrigin-RevId: 280021438
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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
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A return type that differs from the inferred return type need not indicate that an operation is invalid (e.g., tensor<*xf32> vs tensor<10xf32>) but they should be compatible for the operation to be considered valid. Add method to query if inferred type is compatible with return type.
Also add InferTypeOpIntefaceDefault trait that considers equality and compatibility as the same. Currently an op has to opt in to using it explicitly.
PiperOrigin-RevId: 279085639
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This constraint can be used to limit a SymbolRefAttr to point
to a specific kind of op in the closest parent with a symbol table.
PiperOrigin-RevId: 278001364
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Upstream LLVM gained support for #ifndef with https://reviews.llvm.org/D61888
This is changed mechanically via the following command:
find . -name "*.td" -exec sed -i -e ':a' -e 'N' -e '$!ba' -e 's/#ifdef \([A-Z_]*\)\n#else/#ifndef \1/g' {} \;
PiperOrigin-RevId: 277789427
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Test dialect
PiperOrigin-RevId: 277741687
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For ops that recursively re-enter the parser to parse an operation (such as
ops with a "wraps" pretty form), this ensures that the wrapped op will parse
its location, which can then be used for the locations of the wrapping op
and any other implicit ops.
PiperOrigin-RevId: 277152636
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In some cases, it may be desirable to mark entire regions of operations as legal. This provides an additional granularity of context to the concept of "legal". The `ConversionTarget` supports marking operations, that were previously added as `Legal` or `Dynamic`, as `recursively` legal. Recursive legality means that if an operation instance is legal, either statically or dynamically, all of the operations nested within are also considered legal. An operation can be marked via `markOpRecursivelyLegal<>`:
```c++
ConversionTarget &target = ...;
/// The operation must first be marked as `Legal` or `Dynamic`.
target.addLegalOp<MyOp>(...);
target.addDynamicallyLegalOp<MySecondOp>(...);
/// Mark the operation as always recursively legal.
target.markOpRecursivelyLegal<MyOp>();
/// Mark optionally with a callback to allow selective marking.
target.markOpRecursivelyLegal<MyOp, MySecondOp>([](Operation *op) { ... });
/// Mark optionally with a callback to allow selective marking.
target.markOpRecursivelyLegal<MyOp>([](MyOp op) { ... });
```
PiperOrigin-RevId: 277086382
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PiperOrigin-RevId: 276714649
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Previously DRR assumes attributes to appear after operands. This was the
previous requirements on ODS, but that has changed some time ago. Fix
DRR to also support interleaved operands and attributes.
PiperOrigin-RevId: 275983485
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Closes tensorflow/mlir#175
PiperOrigin-RevId: 275726876
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This allows dialect-specific attributes to be attached to func results. (or more specifically, FunctionLike ops).
For example:
```
func @f() -> (i32 {my_dialect.some_attr = 3})
```
This attaches my_dialect.some_attr with value 3 to the first result of func @f.
Another more complex example:
```
func @g() -> (i32, f32 {my_dialect.some_attr = "foo", other_dialect.some_other_attr = [1,2,3]}, i1)
```
Here, the second result has two attributes attached.
PiperOrigin-RevId: 275564165
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Previously when we bind a symbol to an op in DRR, it means to capture
the op's result(s) and later references will be expanded to result(s).
This means for ops without result, we are replacing the symbol with
nothing. This CL treats non-result op capturing and referencing as a
special case to mean the op itself.
PiperOrigin-RevId: 275269702
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NativeCodeCall is handled differently than normal op creation in RewriterGen
(because its flexibility). It will only be materialized to output stream if
it is used. But when using it for auxiliary patterns, we still want the side
effect even if it is not replacing matched root op's results.
PiperOrigin-RevId: 275265467
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Create a ComplexType for table gen references. Include an AnyComplex type
to check whether the resulting tensor can be complex. Expand tensors to
allow complex types.
PiperOrigin-RevId: 275144804
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This hook is useful when an operation is known to be dead, and no replacement values make sense.
PiperOrigin-RevId: 275052756
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When dealing with regions, or other patterns that need to generate temporary operations, it is useful to be able to replace other operations than the root op being matched. Before this PR, these operations would still be considered for legalization meaning that the conversion would either fail, erroneously need to mark these ops as legal, or add unnecessary patterns.
PiperOrigin-RevId: 274598513
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PiperOrigin-RevId: 274046434
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1. Rename test ops referencing operand to index from 0 consistent with how we index elsewhere.
2. Don't limit type checking that functions for all shaped types to only tensors.
3. Don't limit (element) type checking functions and add tests for scalars.
4. Remove SSA values that don't do anything.
PiperOrigin-RevId: 273917608
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variadic result.
Add missing test for single line fix to `void OpEmitter::genFolderDecls()`
entitled "Fold away reduction over 0 dimensions."
PiperOrigin-RevId: 273880337
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SameOperandsAndResultType traits
Currently SameOperandsAndResultShape trait allows operands to have tensor<*xf32> and tensor<2xf32> but doesn't allow tensor<?xf32> and tensor<10xf32>.
Also, use the updated shape compatibility helper function in TensorCastOp::areCastCompatible method.
PiperOrigin-RevId: 273658336
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This is similar to the `inlineRegionBefore` hook, except the original blocks are unchanged. The region to be cloned *must* not have been modified during the conversion process at the point of cloning, i.e. it must belong an operation that has yet to be converted, or the operation that is currently being converted.
PiperOrigin-RevId: 273622533
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This allows confirming that a scalar argument has the same element type as a shaped one. It's easy to validate a type is shaped on its own if that's desirable, so this shouldn't make that use case harder. This matches the behavior of other traits that operate on element type (e.g. AllElementTypesMatch). Also this makes the code simpler because now we just use getElementTypeOrSelf.
Verified that all uses in core already check the type is shaped in another way.
PiperOrigin-RevId: 273068507
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1. Rename a few ops to make it clear they operate on *element* types.
2. Remove unused and generic operand and result ODS names (e.g. $res, $arg, $input). These are just clutter and don't make the op definitions any clearer.
3. Give test cases with duplicate names clearer names.
4. Add missing test case for no operands in SameOperandAndResultElementType.
PiperOrigin-RevId: 273067933
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