| Commit message (Collapse) | Author | Age | Files | Lines |
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Summary: Introduce m_Constant() which allows matching a constant operation without forcing the user also to capture the attribute value.
Differential Revision: https://reviews.llvm.org/D72397
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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 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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It is sometimes useful to create operations separately from the builder before insertion as it may be easier to erase them in isolation if necessary. One example use case for this is folding, as we will only want to insert newly generated constant operations on success. This has the added benefit of fixing some silent PatternRewriter failures related to cloning, as the OpBuilder 'clone' methods don't call createOperation.
PiperOrigin-RevId: 285086242
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This turns a few manually written helper methods into auto-generated ones.
PiperOrigin-RevId: 283339617
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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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Closes tensorflow/mlir#177
PiperOrigin-RevId: 275692653
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These don't add any value, and some are even more restrictive than the respective static 'get' method.
PiperOrigin-RevId: 275391240
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PiperOrigin-RevId: 269120226
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PiperOrigin-RevId: 266863802
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This CL allows binary operations on n-D vector types to be lowered to LLVMIR by performing an (n-1)-D extractvalue, 1-D vector operation and an (n-1)-D insertvalue.
PiperOrigin-RevId: 264339118
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affine.load/affine.store/std.load/std.store
Verification complained when using zero-dimensional memrefs in
affine.load, affine.store, std.load and std.store. This PR extends
verification so that those memrefs can be used.
Closes tensorflow/mlir#58
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/58 from dcaballe:dcaballe/zero-dim 49bcdcd45c52c48beca776431328e5ce551dfa9e
PiperOrigin-RevId: 262164916
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This CL introduces a linalg.generic op to represent generic tensor contraction operations on views.
A linalg.generic operation requires a numbers of attributes that are sufficient to emit the computation in scalar form as well as compute the appropriate subviews to enable tiling and fusion.
These attributes are very similar to the attributes for existing operations such as linalg.matmul etc and existing operations can be implemented with the generic form.
In the future, most existing operations can be implemented using the generic form.
This CL starts by splitting out most of the functionality of the linalg::NInputsAndOutputs trait into a ViewTrait that queries the per-instance properties of the op. This allows using the attribute informations.
This exposes an ordering of verifiers issue where ViewTrait::verify uses attributes but the verifiers for those attributes have not been run. The desired behavior would be for the verifiers of the attributes specified in the builder to execute first but it is not the case atm. As a consequence, to emit proper error messages and avoid crashing, some of the
linalg.generic methods are defensive as such:
```
unsigned getNumInputs() {
// This is redundant with the `n_views` attribute verifier but ordering of verifiers
// may exhibit cases where we crash instead of emitting an error message.
if (!getAttr("n_views") || n_views().getValue().size() != 2)
return 0;
```
In pretty-printed form, the specific attributes required for linalg.generic are factored out in an independent dictionary named "_". When parsing its content is flattened and the "_name" is dropped. This allows using aliasing for reducing boilerplate at each linalg.generic invocation while benefiting from the Tablegen'd verifier form for each named attribute in the dictionary.
For instance, implementing linalg.matmul in terms of linalg.generic resembles:
```
func @mac(%a: f32, %b: f32, %c: f32) -> f32 {
%d = mulf %a, %b: f32
%e = addf %c, %d: f32
return %e: f32
}
#matmul_accesses = [
(m, n, k) -> (m, k),
(m, n, k) -> (k, n),
(m, n, k) -> (m, n)
]
#matmul_trait = {
doc = "C(m, n) += A(m, k) * B(k, n)",
fun = @mac,
indexing_maps = #matmul_accesses,
library_call = "linalg_matmul",
n_views = [2, 1],
n_loop_types = [2, 1, 0]
}
```
And can be used in multiple places as:
```
linalg.generic #matmul_trait %A, %B, %C [other-attributes] :
!linalg.view<?x?xf32>, !linalg.view<?x?xf32>, !linalg.view<?x?xf32>
```
In the future it would be great to have a mechanism to alias / register a new
linalg.op as a pair of linalg.generic, #trait.
Also, note that with one could theoretically only specify the `doc` string and parse all the attributes from it.
PiperOrigin-RevId: 261338740
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This field wasn't updated as the insertion point changed, making it potentially dangerous given the multi-level of MLIR(e.g. 'createBlock' would always insert the new block in 'region'). This also allows for building an OpBuilder with just a context.
PiperOrigin-RevId: 257829135
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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
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Module is a legacy name that only exists as a typedef of ModuleOp.
PiperOrigin-RevId: 257427248
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This allows for giving a Module a more interesting location than 'Unknown'.
PiperOrigin-RevId: 257310117
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PiperOrigin-RevId: 257293379
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As with Functions, Module will soon become an operation, which are value-typed. This eases the transition from Module to ModuleOp. A new class, OwningModuleRef is provided to allow for owning a reference to a Module, and will auto-delete the held module on destruction.
PiperOrigin-RevId: 256196193
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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
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Some dialects allow for string types, and this allows for reusing StringAttr for constants of these types.
PiperOrigin-RevId: 255413948
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PiperOrigin-RevId: 255078768
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DenseElementsAttr.
PiperOrigin-RevId: 253910543
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Identifier already contains all of the necessary functionality/verification, so having a separate class for filenames is unnecessary.
PiperOrigin-RevId: 253855505
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character buffer. This made assumptions about how DenseElementsAttr structured its internal storage, which may change in the future. To replace the existing use cases, a few utility methods have been added:
* '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
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PiperOrigin-RevId: 251783931
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operation after creating it. This can be used to remove operations that are likely to be trivially folded later. Note, these functions only fold operations if all of the folded results are existing values.
PiperOrigin-RevId: 251674299
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instead of a function.
PiperOrigin-RevId: 251563898
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attribute, DictionaryAttr. This attribute maintains a sorted list of NamedAttributes. This will allow for operations/functions to maintain sub dictionaries of attributes.
The syntax is the same as top level attribute dictionaries:
{sub_dictionary: {fn: @someFn, boolAttr: true}}
--
PiperOrigin-RevId: 250898950
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--
PiperOrigin-RevId: 250572818
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instead of pointer. The one downside to this is that the function reference held by a FunctionAttr needs to be explicitly looked up from the parent module. This provides several benefits though:
* 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
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This is necessary for allowing more complicated rewrites in the future that may do things like update the insertion point (e.g. for rewrites involving regions).
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PiperOrigin-RevId: 248803153
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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
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and, transitively, access to the context.
This also fixes a bug where FunctionAttrs were not being remapped for function and function argument attributes.
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PiperOrigin-RevId: 246876924
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none-type ::= `none`
The `none` type is a unit type, i.e. a type with exactly one possible value, where its value does not have a defined dynamic representation.
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PiperOrigin-RevId: 245599248
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A unit attribute is an attribute that represents a value of `unit` type. The
`unit` type allows only one value forming a singleton set. This attribute value
is used to represent attributes that only have meaning from their existence.
One example of such an attribute could be the `swift.self` attribute. This attribute indicates that a function parameter is the self/context
parameter. It could be represented as a boolean attribute(true or false), but a
value of false doesn't really bring any value. The parameter either is the
self/context or it isn't.
```mlir {.mlir}
// A unit attribute defined with the `unit` value specifier.
func @verbose_form(i1 {unitAttr : unit})
// A unit attribute can also be defined without the `unit` value specifier.
func @simple_form(i1 {unitAttr})
```
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PiperOrigin-RevId: 245254045
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I32/I64/F32/F64/Str array attributes are commonly used in ops. It helps
to have handy methods for them.
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PiperOrigin-RevId: 242170569
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Due to legacy reasons (ML/CFG function separation), regions in affine control
flow operations require contained blocks not to have terminators. This is
inconsistent with the notion of the block and may complicate code motion
between regions of affine control operations and other regions.
Introduce `affine.terminator`, a special terminator operation that must be used
to terminate blocks inside affine operations and transfers the control back to
he region enclosing the affine operation. For brevity and readability reasons,
allow `affine.for` and `affine.if` to omit the `affine.terminator` in their
regions when using custom printing and parsing format. The custom parser
injects the `affine.terminator` if it is missing so as to always have it
present in constructed operations.
Update transformations to account for the presence of terminator. In
particular, most code motion transformation between loops should leave the
terminator in place, and code motion between loops and non-affine blocks should
drop the terminator.
PiperOrigin-RevId: 240536998
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This is step 2/N to renaming Instruction to Operation.
PiperOrigin-RevId: 240459216
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Currently, regions can only be constructed by passing in a `Function` or an
`Instruction` pointer referencing the parent object, unlike `Function`s or
`Instruction`s themselves that can be created without a parent. It leads to a
rather complex flow in operation construction where one has to create the
operation first before being able to work with its regions. It may be
necessary to work with the regions before the operation is created. In
particular, in `build` and `parse` functions that are executed _before_ the
operation is created in cases where boilerplate region manipulation is required
(for example, inserting the hypothetical default terminator in affine regions).
Allow creating standalone regions. Such regions are meant to own a list of
blocks and transfer them to other regions on demand.
Each instruction stores a fixed number of regions as trailing objects and has
ownership of them. This decreases the size of the Instruction object for the
common case of instructions without regions. Keep this behavior intact. To
allow some flexibility in construction, make OperationState store an owning
vector of regions. When the Builder creates an Instruction from
OperationState, the bodies of the regions are transferred into the
instruction-owned regions to minimize copying. Thus, it becomes possible to
fill standalone regions with blocks and move them to an operation when it is
constructed, or move blocks from a region to an operation region, e.g., for
inlining.
PiperOrigin-RevId: 240368183
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from Function.
PiperOrigin-RevId: 239638635
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PiperOrigin-RevId: 239616595
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merely provides a common mechanism for representing tuples in MLIR. It is up to dialect authors to provides operations for manipulating them, e.g. extract_tuple_element.
TupleType has the following form:
tuple-type ::= `tuple` `<` (type (`,` type)*)? `>`
Example:
// Empty tuple.
tuple<>
// Single element.
tuple<i32>
// Multi element.
tuple<i32, tuple<f32>, i16>
PiperOrigin-RevId: 239226021
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NFC. This is step 1/n to specifying regions as parts of any operation.
PiperOrigin-RevId: 238472370
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creating an operation
This is more friendly for the user than a raw segfault
PiperOrigin-RevId: 236504102
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(Instruction|Function)::setAttr(StringRef, Attribute) to simplify attribute manipulation.
PiperOrigin-RevId: 236222504
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some unnecessary factory methods on the Type class.
PiperOrigin-RevId: 233640730
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