This fixes a bug: previously, during conversion function argument
attributes were neither beings passed through nor converted. This fix
extends DialectConversion to allow for simultaneous conversion of the
function type and the argument attributes.
This was important when lowering MLIR to LLVM where attribute
information (e.g. noalias) needs to be preserved in MLIR(LLVMDialect).
Longer run it seems reasonable that we want to convert both the
function attribute and its type and the argument attributes, but that
requires a small refactoring in Function.h to aggregate these three
fields in an inner struct, which will require some discussion.
PiperOrigin-RevId: 236709409
Dialect attributes are defined as:
dialect-namespace `.` attr-name `:` attribute-value
Dialects can override any of the following hooks to verify the validity of a given attribute:
* verifyFunctionAttribute
* verifyFunctionArgAttribute
* verifyInstructionAttribute
PiperOrigin-RevId: 236507970
Analysis - NFC
- refactor AffineExprFlattener (-> SimpleAffineExprFlattener) so that it
doesn't depend on FlatAffineConstraints, and so that FlatAffineConstraints
could be moved out of IR/; the simplification that the IR needs for
AffineExpr's doesn't depend on FlatAffineConstraints
- have AffineExprFlattener derive from SimpleAffineExprFlattener to use for
all Analysis/Transforms purposes; override addLocalFloorDivId in the derived
class
- turn addAffineForOpDomain into a method on FlatAffineConstraints
- turn AffineForOp::getAsValueMap into an AffineValueMap ctor
PiperOrigin-RevId: 235283610
Introduce support for binding MLIR functions as constant expressions. Standard
constant operation supports functions as possible constant values.
Provide C APIs to look up existing named functions in an MLIR module and expose
them to the Python bindings. Provide Python bindings to declare a function in
an MLIR module without defining it and to add a definition given a function
declaration. These declarations are useful when attempting to link MLIR
modules with, e.g., the standard library.
Introduce EDSC support for direct and indirect calls to other MLIR functions.
Internally, an indirect call is always emitted to leverage existing support for
delayed construction of MLIR Values using EDSC Exprs. If the expression is
bound to a constant function (looked up or declared beforehand), MLIR constant
folding will be able to replace an indirect call by a direct call. Currently,
only zero- and one-result functions are supported since we don't have support
for multi-valued expressions in EDSC.
Expose function calling interface to Python bindings on expressions by defining
a `__call__` function accepting a variable number of arguments.
PiperOrigin-RevId: 234959444
A recent change made ConstantOp::build accept a NumericAttr or assert that a
generic Attribute is in fact a NumericAttr. The rationale behind the change
was that NumericAttrs have a type that can be used as the result type of the
constant operation. FunctionAttr also has a type, and it is valid to construct
function-typed constants as exercised by the parser.mlir test. Relax
ConstantOp::build back to take a generic Attribute. In the overload that only
takes an attribute, assert that the Attribute is either a NumericAttr or a
FunctionAttr, because it is necessary to extract the type. In the overload
that takes both type type and the attribute, delegate the attribute type
checking to ConstantOp::verify to prevent non-Builder-based Op construction
mechanisms from creating invalid IR.
PiperOrigin-RevId: 234798569
- compute slices precisely where the destination iteration depends on multiple source
iterations (instead of over-approximating to the whole source loop extent)
- update unionBoundingBox to deal with input with non-matching symbols
- reenable disabled backend test case
PiperOrigin-RevId: 234714069
generation pass to make it drop certain assumptions, complete TODOs.
- multiple fixes for getMemoryFootprintBytes
- pass loopDepth correctly from getMemoryFootprintBytes()
- use union while computing memory footprints
- bug fixes for addAffineForOpDomain
- take into account loop step
- add domains of other loop IVs in turn that might have been used in the bounds
- dma-generate: drop assumption of "non-unit stride loops being tile space loops
and skipping those and recursing to inner depths"; DMA generation is now purely
based on available fast mem capacity and memory footprint's calculated
- handle memory region compute failures/bailouts correctly from dma-generate
- loop tiling cleanup/NFC
- update some debug and error messages to use emitNote/emitError in
pipeline-data-transfer pass - NFC
PiperOrigin-RevId: 234245969
Update FlatAffineConstraints::getLower/UpperBounds to project to the identifier for which bounds are being computed. This change enables computing bounds on an identifier which were previously dependent on the bounds of another identifier.
PiperOrigin-RevId: 234017514
Associates opaque constants with a particular dialect. Adds general mechanism to register dialect-specific hooks defined in external components. Adds hooks to decode opaque tensor constant and extract an element of an opaque tensor constant.
This CL does not change the existing mechanism for registering constant folding hook yet. One thing at a time.
PiperOrigin-RevId: 233544757
Aggregate types where at least one dimension is zero do not fully make sense as
they cannot contain any values (their total size is zero). However, TensorFlow
and XLA support tensors with zero sizes, so we must support those too. This is
relatively safe since, unlike vectors and memrefs, we don't have first-class
element accessors for MLIR tensors.
To support sparse element attributes of vector types that have no non-zero
elements, make sure that index and value element attributes have tensor type so
that we never need to create a zero vector type internally. Note that this is
already consistent with the inline documentation of the sparse elements
attribute. Users of the sparse elements attribute should not rely on the
storage schema anyway.
PiperOrigin-RevId: 232896707
Instead, we deduce the result type from the given attribute.
This is in preparation for generating constant ops with TableGen.
PiperOrigin-RevId: 232723467
*) Adds parameter to public API of MemRefRegion::compute for passing in the slice loop bounds to compute the memref region of the loop nest slice.
*) Exposes public method MemRefRegion::getRegionSize for computing the size of the memref region in bytes.
PiperOrigin-RevId: 232706165
* AffineStructures has moved to IR.
* simplifyAffineExpr/simplifyAffineMap/getFlattenedAffineExpr have moved to IR.
* makeComposedAffineApply/fullyComposeAffineMapAndOperands have moved to AffineOps.
* ComposeAffineMaps is replaced by AffineApplyOp::canonicalize and deleted.
PiperOrigin-RevId: 232586468
Existing type syntax contains the following productions:
function-type ::= type-list-parens `->` type-list
type-list ::= type | type-list-parens
type ::= <..> | function-type
Due to these rules, when the parser sees `->` followed by `(`, it cannot
disambiguate if `(` starts a parenthesized list of function result types, or a
parenthesized list of operands of another function type, returned from the
current function. We would need an unknown amount of lookahead to try to find
the `->` at the right level of function nesting to differentiate between type
lists and singular function types.
Instead, require the result type of the function that is a function type itself
to be always parenthesized, at the syntax level. Update the spec and the
parser to correspond to the production rule names used in the spec (although it
would have worked without modifications). Fix the function type parsing bug in
the process, as it used to accept the non-parenthesized list of types for
arguments, disallowed by the spec.
PiperOrigin-RevId: 232528361
In optional attribute dictionary used, among others, in the generic form of the
ops, attribute types for integers and floats are omitted. This could lead to
inconsistencies when round-tripping the IR, in particular the attributes are
created with incorrect types after parsing (integers default to i64, floats
default to f64). Provide API to emit a trailing type after the attribute for
integers and floats. Use it while printing the optional attribute dictionary.
Omitting types for i64 and f64 is a pragmatic decision that minimizes changes
in tests. We may want to reconsider in the future and always print types of
attributes in the generic form.
PiperOrigin-RevId: 232480116
The generic form may be more desirable even when there is a custom form
specified so add option to enable emitting it. This also exposes a current bug
when round tripping constant with function attribute.
PiperOrigin-RevId: 232350712
loops), (2) take into account fast memory space capacity and lower 'dmaDepth'
to fit, (3) add location information for debug info / errors
- change dma-generate pass to work on blocks of instructions (start/end
iterators) instead of 'for' loops; complete TODOs - allows DMA generation for
straightline blocks of operation instructions interspersed b/w loops
- take into account fast memory capacity: check whether memory footprint fits
in fastMemoryCapacity parameter, and recurse/lower the depth at which DMA
generation is performed until it does fit in the provided memory
- add location information to MemRefRegion; any insufficient fast memory
capacity errors or debug info w.r.t dma generation shows location information
- allow DMA generation pass to be instantiated with a fast memory capacity
option (besides command line flag)
- change getMemRefRegion to return unique_ptr's
- change getMemRefFootprintBytes to work on a 'Block' instead of 'ForInst'
- other helper methods; add postDomInstFilter option for
replaceAllMemRefUsesWith; drop forInst->walkOps, add Block::walkOps methods
Eg. output
$ mlir-opt -dma-generate -dma-fast-mem-capacity=1 /tmp/single.mlir
/tmp/single.mlir:9:13: error: Total size of all DMA buffers' for this block exceeds fast memory capacity
for %i3 = (d0) -> (d0)(%i1) to (d0) -> (d0 + 32)(%i1) {
^
$ mlir-opt -debug-only=dma-generate -dma-generate -dma-fast-mem-capacity=400 /tmp/single.mlir
/tmp/single.mlir:9:13: note: 8 KiB of DMA buffers in fast memory space for this block
for %i3 = (d0) -> (d0)(%i1) to (d0) -> (d0 + 32)(%i1) {
PiperOrigin-RevId: 232297044
These attribute kinds are different from the rest in the sense that their types are defined
in MLIR's type hierarchy and we can build constant op out of them.
By defining this middle-level base class, we have a unified way to test and query the type
of these attributes, which will be useful when constructing constant ops of various dialects.
This CL also added asserts to reject non-NumericAttr in constant op's build() method.
PiperOrigin-RevId: 232188178
- getTerminator() on a block can return nullptr; moreover, blocks that are improperly
constructed/transformed by utilities/passes may not have terminators even for the
top-level blocks
PiperOrigin-RevId: 232025963
Addresses b/122486036
This CL addresses some leftover crumbs in AffineMap and IntegerSet by removing
the Null method and cleaning up the constructors.
As the ::Null uses were tracked down, opportunities appeared to untangle some
of the Parsing logic and make it explicit where AffineMap/IntegerSet have
ambiguous syntax. Previously, ambiguous cases were hidden behind the implicit
pointer values of AffineMap* and IntegerSet* that were passed as function
parameters. Depending the values of those pointers one of 3 behaviors could
occur.
This parsing logic convolution is one of the rare cases where I would advocate
for code duplication. The more proper fix would be to make the syntax
unambiguous or to allow some lookahead.
PiperOrigin-RevId: 231058512
Use `-mlir-pretty-debuginfo` if the user wants line breaks between different callsite lines.
The print results before and after this CL are shown in the tests.
PiperOrigin-RevId: 231013812
canonicalizations of operations. The ultimate important user of this is
going to be a funcBuilder->foldOrCreate<YourOp>(...) API, but for now it
is just a more convenient way to write certain classes of canonicalizations
(see the change in StandardOps.cpp).
NFC.
PiperOrigin-RevId: 230770021
Example inline notation:
trailing-location ::= 'loc' '(' location ')'
// FileLineCol Location.
%1 = "foo"() : () -> i1 loc("mysource.cc":10:8)
// Name Location
return loc("foo")
// CallSite Location
return loc(callsite("foo" at "mysource.cc":19:9))
// Fused Location
/// Without metadata
func @inline_notation() loc(fused["foo", "mysource.cc":10:8])
/// With metadata
return loc(fused<"myPass">["foo", "foo2"])
// Unknown location.
return loc(unknown)
Locations are currently only printed with inline notation at the line of each instruction. Further work is needed to allow for reference notation, e.g:
...
return loc 1
}
...
loc 1 = "source.cc":10:1
PiperOrigin-RevId: 230587621
This CL just changes various docs and comments to use the term "generic" and
"custom" when mentioning assembly forms. To be consist, several methods are
also renamed:
* FunctionParser::parseVerboseOperation() -> parseGenericOperation()
* ModuleState::hasShorthandForm() -> hasCustomForm()
* OpAsmPrinter::printDefaultOp() -> printGenericOp()
PiperOrigin-RevId: 230568819
- ForInst::walkOps will also be used in an upcoming CL (cl/229438679); better to have
this instead of deriving from the InstWalker
PiperOrigin-RevId: 230413820
1) Fix FloatAttr type inconsistency in conversion from tf.FusedBatchNorm to TFLite ops
We used to compose the splat tensor out of the scalar epsilon attribute by using the
type of the variance operand. However, the epsilon attribute may have a different
bitwidth than the one in the variance operand. So it ends up we were creating
inconsistent types within the FloatAttr itself.
2) Fix SplatElementsAttr type inconsistency in AnnotateInputArrays
We need to create the zero-valued attribute according to the type provided as the
command-line arguments.
3) Concretize the result type of tf.Shape constant folding test case
Currently the resultant constant is created by the constant folding harness, using
the result type of the original op as the constant's result type. That can be
a different type than the constant's internal DenseElementsAttr.
PiperOrigin-RevId: 230244665
- print multiplication by -1 as unary negate; expressions like s0 * -1, d0 * -1
+ d1 will now appear as -s0, -d0 + d1 resp.
- a minor cleanup while on printAffineExprInternal
PiperOrigin-RevId: 230222151
The operand and result types of binary ops are not necessarily the
same. For those binary ops, we cannot print in the short-form assembly.
Enhance impl:::printBinaryOp to consider operand and result types
to select which assembly form to use.
PiperOrigin-RevId: 229608142
DenseElementAttr currently does not support value bitwidths of > 64. This can result in asan failures and crashes when trying to invoke DenseElementsAttr::writeBits/DenseElementsAttr::readBits.
PiperOrigin-RevId: 229241125
This CL is the 6th and last on the path to simplifying AffineMap composition.
This removes `AffineValueMap::forwardSubstitutions` and replaces it by simple
calls to `fullyComposeAffineMapAndOperands`.
PiperOrigin-RevId: 228962580
The const folding logic is structurally similar, so use a template
to abstract the common part.
Moved mul(x, 0) to a legalization pattern to be consistent with
mul(x, 1).
Also promoted getZeroAttr() to be a method on Builder since it is
expected to be frequently used.
PiperOrigin-RevId: 228891989
This CL is the 5th on the path to simplifying AffineMap composition.
This removes the distinction between normalized single-result AffineMap and
more general composed multi-result map.
One nice byproduct of making the implementation driven by single-result is
that the multi-result extension is a trivial change: the implementation is
still single-result and we just use:
```
unsigned idx = getIndexOf(...);
map.getResult(idx);
```
This CL also fixes an AffineNormalizer implementation issue related to symbols.
Namely it stops performing substitutions on symbols in AffineNormalizer and
instead concatenates them all to be consistent with the call to
`AffineMap::compose(AffineMap)`. This latter call to `compose` cannot perform
simplifications of symbols coming from different maps based on positions only:
i.e. dims are applied and renumbered but symbols must be concatenated.
The only way to determine whether symbols from different AffineApply are the
same is to look at the concrete values. The canonicalizeMapAndOperands is thus
extended with behavior to support replacing operands that appear multiple
times.
Lastly, this CL demonstrates that the implementation is correct by rewriting
ComposeAffineMaps using only `makeComposedAffineApply`. The implementation
uses a matcher because AffineApplyOp are introduced as composed operations on
the fly instead of iteratively forwardSubstituting. For this purpose, a walker
would revisit freshly introduced AffineApplyOp. Regardless, ComposeAffineMaps
is scheduled to disappear, this CL replaces the implementation based on
iterative `forwardSubstitute` by a composed-by-construction
`makeComposedAffineApply`.
Remaining calls to `forwardSubstitute` will be removed in the next CL.
PiperOrigin-RevId: 228830443
* Get a specific successor operand.
* Iterator support for non successor operands.
* Fix bug when removing the last operand from the operand list of an Instruction.
* Get the argument number for a BlockArgument.
PiperOrigin-RevId: 228660898
Originally, terminators were special kinds of operation and could not be
extended by dialects. Only builtin terminators were supported and they had
custom parsers and printers. Currently, "terminator" is a property of an
operation, making it possible for dialects to define custom terminators.
However, verbose forms of operation syntax were not designed to support
terminators that may have a list of successors (each successor contains a block
name and an optional operand list). Calling printDefaultOp on a terminator
drops all successor information. Dialects are thus required to provide custom
parsers and printers for their terminators.
Introduce the syntax for the list of successors in the verbose from of the
operation. Add support for printing and parsing verbose operations with
successors.
Note that this does not yet add support for unregistered terminators since
"terminator" is a property stored in AsbtractOperation and therefore is only
available for registered operations that have an instance of AbstractOperation.
Add tests for verbose parsing. It is currently impossible to test round-trip
for verbose terminators because none of the known dialects use verbose syntax
for printing terminators by default, however the printer was exercised on the
LLVM IR dialect prototype.
PiperOrigin-RevId: 228566453
This CL is the 4th on the path to simplifying AffineMap composition.
This CL extract canonicalizeMapAndOperands so it can be reused by other
functions; in particular, this will be used in
`makeNormalizedAffineApply`.
PiperOrigin-RevId: 228277890
This CL is the 2nd on the path to simplifying AffineMap composition.
This CL uses the now accepted `AffineExpr::compose(AffineMap)` to
implement `AffineMap::compose(AffineMap)`.
Implications of keeping the simplification function in
Analysis are documented where relevant.
PiperOrigin-RevId: 228276646
This CL is the 1st on the path to simplifying AffineMap composition.
This CL uses the now accepted AffineExpr.replaceDimsAndSymbols to
implement `AffineExpr::compose(AffineMap)`.
Arguably, `simplifyAffineExpr` should be part of IR and not Analysis but
this CL does not yet pull the trigger on that.
PiperOrigin-RevId: 228265845
- refactor toAffineFromEq and the code surrounding it; refactor code into
FlatAffineConstraints::getSliceBounds
- add FlatAffineConstraints methods to detect identifiers as mod's and div's of other
identifiers
- add FlatAffineConstraints::getConstantLower/UpperBound
- Address b/122118218 (don't assert on invalid fusion depths cmdline flags -
instead, don't do anything; change cmdline flags
src-loop-depth -> fusion-src-loop-depth
- AffineExpr/Map print method update: don't fail on null instances (since we have
a wrapper around a pointer, it's avoidable); rationale: dump/print methods should
never fail if possible.
- Update memref-dataflow-opt to add an optimization to avoid a unnecessary call to
IsRangeOneToOne when it's trivially going to be true.
- Add additional test cases to exercise the new support
- update a few existing test cases since the maps are now generated uniformly with
all destination loop operands appearing for the backward slice
- Fix projectOut - fix wrong range for getBestElimCandidate.
- Fix for getConstantBoundOnDimSize() - didn't show up in any test cases since
we didn't have any non-hyperrectangular ones.
PiperOrigin-RevId: 228265152
- Detect 'mod' to replace the combination of floordiv, mul, and subtract when
possible at construction time; when 'c' is a power of two, this reduces the number of
operations; also more compact and readable. Update simplifyAdd for this.
On a side note:
- with the affine expr flattening we have, a mod expression like d0 mod c
would be flattened into d0 - c * q, c * q <= d0 <= c*q + c - 1, with 'q'
being added as the local variable (q = d0 floordiv c); as a result, a mod
was turned into a floordiv whenever the expression was reconstructed back,
i.e., as d0 - c * (d0 floordiv c); as a result of this change, we recover
the mod back.
- rename SimplifyAffineExpr -> SimplifyAffineStructures (pass had been renamed but
the file hadn't been).
PiperOrigin-RevId: 228258120
The `for` instruction defines the loop induction variable it uses. In the
well-formed IR, the induction variable can only be used by the body of the
`for` loop. Existing implementation was explicitly cleaning the body of the
for loop to remove all uses of the induction variable before removing its
definition. However, in ill-formed IR that may appear in some stages of
parsing, there may be (invalid) users of the loop induction variable outside
the loop body. In case of unsuccessful parsing, destructor of the
ForInst-defined Value would assert because there are remaining though invalid
users of this Value. Explicitly drop all uses of the loop induction Value when
destroying a ForInst. It is no longer necessary to explicitly clean the body
of the loop, destructor of the block will take care of this.
PiperOrigin-RevId: 228168880
getAffineBinaryOpExpr for consistency (NFC)
- this is consistent with the name of the class and getAffineDimExpr/ConstantExpr, etc.
PiperOrigin-RevId: 228164959
Supervectorization does not plan on handling multi-result AffineMaps and
non-canonical chains of > 1 AffineApplyOp.
This CL introduces a simpler abstraction and composition of single-result
unbounded AffineApplyOp by using the existing unbound AffineMap composition.
This CL adds a simple API call and relevant tests:
```c++
OpPointer<AffineApplyOp> makeNormalizedAffineApply(
FuncBuilder *b, Location loc, AffineMap map, ArrayRef<Value*> operands);
```
which creates a single-result unbounded AffineApplyOp.
The operands of AffineApplyOp are not themselves results of AffineApplyOp by
consrtuction.
This represent the simplest possible interface to complement the composition
of (mathematical) AffineMap, for the cases when we are interested in applying
it to Value*.
In this CL the composed AffineMap is not compressed (i.e. there exist operands
that are not part of the result). A followup commit will compress to normal
form.
The single-result unbounded AffineApplyOp abstraction will be used in a
followup CL to support the MaterializeVectors pass.
PiperOrigin-RevId: 227879021
This impl class currently provides the following:
* auto definition of the 'ImplType = StorageClass'
* get/getChecked wrappers around TypeUniquer
* 'verifyConstructionInvariants' hook
- This hook verifies that the arguments passed into get/getChecked are valid
to construct a type instance with.
With this, all non-generic type uniquing has been moved out of MLIRContext.cpp
PiperOrigin-RevId: 227871108
symbols.
Included with this is some other infra:
- Testcases for other canonicalizations that I will implement next.
- Some helpers in AffineMap/Expr for doing simple walks without defining whole
visitor classes.
- A 'replaceDimsAndSymbols' facility that I'll be using to simplify maps and
exprs, e.g. to fold one constant into a mapping and to drop/renumber unused dims.
- Allow index (and everything else) to work in memref's, as we previously
discussed, to make the testcase easier to write.
- A "getAffineBinaryExpr" helper to produce a binop when you know the kind as
an enum.
This line of work will eventually subsume the ComposeAffineApply pass, but it is no where close to that yet :-)
PiperOrigin-RevId: 227852951
Dialect specific types are registered similarly to operations, i.e. registerType<...> within the dialect. Unlike operations, there is no notion of a "verbose" type, that is *all* types must be registered to a dialect. Casting support(isa/dyn_cast/etc.) is implemented by reserving a range of type kinds in the top level Type class as opposed to string comparison like operations.
To support derived types a few hooks need to be implemented:
In the concrete type class:
- static char typeID;
* A unique identifier for the type used during registration.
In the Dialect:
- typeParseHook and typePrintHook must be implemented to provide parser support.
The syntax for dialect extended types is as follows:
dialect-type: '!' dialect-namespace '<' '"' type-specific-data '"' '>'
The 'type-specific-data' is information used to identify different types within the dialect, e.g:
- !tf<"variant"> // Tensor Flow Variant Type
- !tf<"string"> // Tensor Flow String Type
TensorFlow/TensorFlowControl types are now implemented as dialect specific types as a proof
of concept.
PiperOrigin-RevId: 227580052
The entire compiler now looks at structural properties of the function (e.g.
does it have one block, does it contain an if/for stmt, etc) so the only thing
holding up this difference is round tripping through the parser/printer syntax.
Removing this shrinks the compile by ~140LOC.
This is step 31/n towards merging instructions and statements. The last step
is updating the docs, which I will do as a separate patch in order to split it
from this mostly mechanical patch.
PiperOrigin-RevId: 227540453
Moving forward dialect namespaces cannot contain '.' characters.
This cl also standardizes that operation names must begin with the dialect namespace followed by a '.'.
PiperOrigin-RevId: 227532193
- introduce PostDominanceInfo in the right/complete way and use that for post
dominance check in store-load forwarding
- replace all uses of Analysis/Utils::dominates/properlyDominates with
DominanceInfo::dominates/properlyDominates
- drop all redundant copies of dominance methods in Analysis/Utils/
- in pipeline-data-transfer, replace dominates call with a much less expensive
check; similarly, substitute dominates() in checkMemRefAccessDependence with
a simpler check suitable for that context
- fix a bug in properlyDominates
- improve doc for 'for' instruction 'body'
PiperOrigin-RevId: 227320507
function pass, and eliminating the need to copy over code and do
interprocedural updates. While here, also improve it to make fewer empty
blocks, and rename it to "LowerIfAndFor" since that is what it does. This is
a net reduction of ~170 lines of code.
As drive-bys, change the splitBlock method to *not* insert an unconditional
branch, since that behavior is annoying for all clients. Also improve the
AsmPrinter to not crash when a block is referenced that isn't linked into a
function.
PiperOrigin-RevId: 227308856
Function::walk functionality into f->walkInsts/Ops which allows visiting all
instructions, not just ops. Eliminate Function::getBody() and
Function::getReturn() helpers which crash in CFG functions, and were only kept
around as a bridge.
This is step 25/n towards merging instructions and statements.
PiperOrigin-RevId: 227243966
printing the entry block in a CFG function's argument line. Since I'm touching
all of the testcases anyway, change the argument list from printing as
"%arg : type" to "%arg: type" which is more consistent with bb arguments.
In addition to being more consistent, this is a much nicer look for cfg functions.
PiperOrigin-RevId: 227240069
requires enhancing DominanceInfo to handle the structure of an ML function,
which is required anyway. Along the way, this also fixes a const correctness
problem with Instruction::getBlock().
This is step 24/n towards merging instructions and statements.
PiperOrigin-RevId: 227228900
consistent and moving the using declarations over. Hopefully this is the last
truly massive patch in this refactoring.
This is step 21/n towards merging instructions and statements, NFC.
PiperOrigin-RevId: 227178245
The last major renaming is Statement -> Instruction, which is why Statement and
Stmt still appears in various places.
This is step 19/n towards merging instructions and statements, NFC.
PiperOrigin-RevId: 227163082
by about 100 LOC), without changing any existing behavior.
This is step 20/n towards merging instructions and statements, NFC.
PiperOrigin-RevId: 227155000
StmtResult -> InstResult, StmtOperand -> InstOperand, and remove the old names.
This is step 17/n towards merging instructions and statements, NFC.
PiperOrigin-RevId: 227121537
OperationInst derives from it. This allows eliminating some forwarding
functions, other complex code handling multiple paths, and the 'isStatement'
bit tracked by Operation.
This is the last patch I think I can make before the big mechanical change
merging Operation into OperationInst, coming next.
This is step 15/n towards merging instructions and statements, NFC.
PiperOrigin-RevId: 227077411
Sometimes we have to get the raw value of the FloatAttr to invoke APIs from
non-MLIR libraries (i.e. in the tpu_ops.inc and convert_tensor.cc files). Using
`FloatAttr::getValue().convertToFloat()` and
`FloatAttr::getValue().convertToDouble()` is not safe because interally they
checke the semantics of the APFloat in the attribute, and the semantics is not
always specified (the default value is f64 then convertToFloat will fail) or
inferred incorrectly (for example, using 1.0 instead of 1.f for IEEEFloat).
Calling these convert methods without knowing the semantics can usually crash
the compiler.
This new method converts the value of a FloatAttr to double even if it loses
precision. Currently this method can be used to read in f32 data from arrays.
PiperOrigin-RevId: 227076616
#includes so Statements.h includes Operation.h but nothing else does. This is
in preparation to eliminate the Operation class and the complexity it brings
with it. I split this patch off because it is just moving stuff around, the
next patch will be more complex.
This is step 14/n towards merging instructions and statements, NFC.
PiperOrigin-RevId: 227071777
FuncBuilder class. Also rename SSAValue.cpp to Value.cpp
This is step 12/n towards merging instructions and statements, NFC.
PiperOrigin-RevId: 227067644
is the new base of the SSA value hierarchy. This CL also standardizes all the
nomenclature and comments to use 'Value' where appropriate. This also eliminates a large number of cast<MLValue>(x)'s, which is very soothing.
This is step 11/n towards merging instructions and statements, NFC.
PiperOrigin-RevId: 227064624
This *only* changes the internal data structures, it does not affect the user visible syntax or structure of MLIR code. Function gets new "isCFG()" sorts of predicates as a transitional measure.
This patch is gross in a number of ways, largely in an effort to reduce the amount of mechanical churn in one go. It introduces a bunch of using decls to keep the old names alive for now, and a bunch of stuff needs to be renamed.
This is step 10/n towards merging instructions and statements, NFC.
PiperOrigin-RevId: 227044402
making it more similar to the CFG side of things. It is true that in a deeply
nested case that this is not a guaranteed O(1) time operation, and that 'get'
could lead compiler hackers to think this is cheap, but we need to merge these
and we can look into solutions for this in the future if it becomes a problem
in practice.
This is step 9/n towards merging instructions and statements, NFC.
PiperOrigin-RevId: 226983931
For performance/memory saving purpose, having the Instruction holding a
std::vector for the operands isn't a really good tradeoff. The only reason for
this was to support adding/removing easily BasicBlock arguments to Terminator.
Since this isn't the most common operation, we instead force a pre-allocated
list of operands on Instructions at creation time.
PiperOrigin-RevId: 226981227
BlockArgument arguments of the entry block instead. This makes MLFunctions and
CFGFunctions work more similarly.
This is step 7/n towards merging instructions and statements, NFC.
PiperOrigin-RevId: 226966975
MLFunction, IfStmt, ForStmt even though they currently only contain exactly one
block in that list.
This is step 6/n towards merging instructions and statements, NFC.
PiperOrigin-RevId: 226960278
The NameLoc can be used to represent a variable, node or method. The
CallSiteLoc has two fields, one represents the concrete location and another
one represents the caller's location. Multiple CallSiteLocs can be chained as
a call stack.
For example, the following call stack
```
AAA
at file1:1
at file2:135
at file3:34
```
can be formed by call0:
```
auto name = NameLoc::get("AAA");
auto file1 = FileLineColLoc::get("file1", 1);
auto file2 = FileLineColLoc::get("file2", 135);
auto file3 = FileLineColLoc::get("file3", 34);
auto call2 = CallSiteLoc::get(file2, file3);
auto call1 = CallSiteLoc::get(file1, call2);
auto call0 = CallSiteLoc::get(name, call1);
```
PiperOrigin-RevId: 226941797
from it. This is necessary progress to squaring away the parent relationship
that a StmtBlock has with its enclosing if/for/fn, and makes room for functions
to have more than one block in the future. This also removes IfClause and ForStmtBody.
This is step 5/n towards merging instructions and statements, NFC.
PiperOrigin-RevId: 226936541
for SSA values in terminators, but easily worked around. At the same time,
move the StmtOperand list in a OperationStmt to the end of its trailing
objects list so we can *reduce* the number of operands, without affecting
offsets to the other stuff in the allocation.
This is important because we want OperationStmts to be consequtive, including
their operands - we don't want to use an std::vector of operands like
Instructions have.
This is patch 4/n towards merging instructions and statements, NFC.
PiperOrigin-RevId: 226865727
clients to use OperationState instead. This makes MLFuncBuilder more similiar
to CFGFuncBuilder. This whole area will get tidied up more when cfg and ml
worlds get unified. This patch is just gardening, NFC.
PiperOrigin-RevId: 226701959
optional successor operands when they are terminator operations.
This isn't used yet, but is part 2/n towards merging BasicBlock into StmtBlock
and Instruction into OperationStmt.
PiperOrigin-RevId: 226684636
StmtBlock. This is more consistent with IfStmt and also conceptually makes
more sense - a forstmt "isn't" its body, it contains its body.
This is step 1/N towards merging BasicBlock and StmtBlock. This is required
because in the new regime StmtBlock will have a use list (just like BasicBlock
does) of operands, and ForStmt already has a use list for its induction
variable.
This is a mechanical patch, NFC.
PiperOrigin-RevId: 226684158
This allows for us to decouple type uniquing/construction from MLIRContext and pave the way for dialect specific types.
To accomplish this we two new classes, TypeUniquer and TypeStorageAllocator.
* TypeUniquer is now responsible for all construction and uniquing of types.
* TypeStorageAllocator is a utility used by derived type storage objects to allocate memory within an MLIRContext.
This cl also standardizes what a derived type storage class needs to provide:
- Define a type alias, KeyTy, to a type that uniquely identifies the
instance of the type within its kind.
* The key type must be constructible from the values passed into the
detail::TypeUniquer::get call after the type kind.
* The key type must have a llvm::DenseMapInfo specialization for
hashing.
- Provide a method, 'KeyTy getKey() const', to construct the key type
from an existing storage instance.
- Provide a construction method:
'DerivedStorage *construct(TypeStorageAllocator &, ...)'
that builds a unique instance of the derived storage. The arguments
after the TypeStorageAllocator must correspond with the values passed
into the detail::TypeUniquer::get call after the type kind.
PiperOrigin-RevId: 226507184
Existing implementation always uses 64 bits to store floating point values in
DenseElementsAttr. This was due to FloatAttrs always a `double` for storage
independently of the actual type. Recent commits added support for FloatAttrs
with the proper f32 type and floating semantics and changed the bitwidth
reporting on FloatType.
Use the existing infrastructure for densely storing 16 and 32-bit values in
DenseElementsAttr storage to store f16 and f32 values. Move floating semantics
definition to the FloatType level. Properly support f16 / IEEEhalf semantics
at the FloatAttr level and in the builder.
Note that bf16 is still stored as a 64-bit value with IEEEdouble semantics
because APFloat does not have first-class support for bf16 types.
PiperOrigin-RevId: 225981289
As MLIR moves towards dialect-specific types, a generic Type::getBitWidth does
not make sense for all of them. Even with the current type system, the bit
width is not defined (and causes the method in question to abort) for all
TensorFlow types.
This commit restricts the bit width definition to primitive standard types that
have a number of bits appearing verbatim in their type, i.e., integers and
floats. As a side effect, it delegates the decision on the bit width of the
`index` to the backends. Existing backends currently hardcode it to 64 bits.
The Type::getBitWidth method is replaced by Type::getIntOrFloatBitWidth that
only applies to integers and floats. The call sites are updated to use the new
method, where applicable, or rewritten so as not rely on it. Incidentally,
this fixes a utility method that did not account for memrefs being allowed to
have vectors as element types in the size computation.
As an observation, several places in the code use Type in places where a more
specific type could be used instead. Some of those are fixed by this commit.
PiperOrigin-RevId: 225844792
Store FloatAttr using more appropriate fltSemantics (mostly fixing up F32/F64 storage, F16/BF16 pending). Previously F32 type was used incorrectly for double (the storage was double). Also add query method that returns fltSemantics for IEEE fp types and use that to verify that the APfloat given matches the type:
* FloatAttr created using APFloat is verified that the semantics of the type and APFloat matches;
* FloatAttr created using double has the APFloat created to match the semantics of the type;
Change parsing of tensor negative splat element to pass in the element type expected. Misc other changes to account for the storage type matching the attribute.
PiperOrigin-RevId: 225821834
An extensive discussion demonstrated that it is difficult to support `index`
types as elements of compound (vector, memref, tensor) types. In particular,
their size is unknown until the target-specific lowering takes place. MLIR may
need to store constants of the fixed-shape compound types (e.g.,
vector<4 x index>) internally and must know the size of the element type and
data layout constraints. The same information is necessary for target-specific
lowering and translation to reliably support compound types with `index`
elements, but MLIR does not have a dedicated target description mechanism yet.
The uses cases for compound types with `index` elements, should they appear,
can be handled via an `index_cast` operation that converts between `index` and
fixed-size integer types at the SSA value level instead of the type level.
PiperOrigin-RevId: 225064373
This simplifies call-sites returning true after emitting an error. After the
conversion, dropped braces around single statement blocks as that seems more
common.
Also, switched to emitError method instead of emitting Error kind using the
emitDiagnostic method.
TESTED with existing unit tests
PiperOrigin-RevId: 224527868
This CL adds the following free functions:
```
/// Returns the AffineExpr e o m.
AffineExpr compose(AffineExpr e, AffineMap m);
/// Returns the AffineExpr f o g.
AffineMap compose(AffineMap f, AffineMap g);
```
This addresses the issue that AffineMap composition is only available at a
distance via AffineValueMap and is thus unusable on Attributes.
This CL thus implements AffineMap composition in a more modular and composable
way.
This CL does not claim that it can be a good replacement for the
implementation in AffineValueMap, in particular it does not support bounded
maps atm.
Standalone tests are added that replicate some of the logic of the AffineMap
composition pass.
Lastly, affine map composition is used properly inside MaterializeVectors and
a standalone test is added that requires permutation_map composition with a
projection map.
PiperOrigin-RevId: 224376870
update/improve/clean up API.
- update FlatAffineConstraints::getConstBoundDifference; return constant
differences between symbolic affine expressions, look at equalities as well.
- fix buffer size computation when generating DMAs symbolic in outer loops,
correctly handle symbols at various places (affine access maps, loop bounds,
loop IVs outer to the depth at which DMA generation is being done)
- bug fixes / complete some TODOs for getMemRefRegion
- refactor common code b/w memref dependence check and getMemRefRegion
- FlatAffineConstraints API update; added methods employ trivial checks /
detection - sufficient to handle hyper-rectangular cases in a precise way
while being fast / low complexity. Hyper-rectangular cases fall out as
trivial cases for these methods while other cases still do not cause failure
(either return conservative or return failure that is handled by the caller).
PiperOrigin-RevId: 224229879
The checks for `isa<IndexType>() || isa<IntegerType>()` and
`isa<IndexType>() || isa<IntegerType>() || isa<FloatType>()`
are frequently used, so it's useful to have some helper
methods for them.
PiperOrigin-RevId: 224133596
Ensures both hash values returned are the same. Tested by triggering resize of map/set and verifying failure before change.
PiperOrigin-RevId: 223651443
class. This change is NFC, but allows for new kinds of patterns, specifically
LegalizationPatterns which will be allowed to change the types of things they
rewrite.
PiperOrigin-RevId: 223243783
This CL added two new traits, SameOperandsAndResultShape and
ResultsAreBoolLike, and changed CmpIOp to embody these two
traits. As a consequence, CmpIOp's result type now is verified
to be bool-like.
PiperOrigin-RevId: 223208438
Not having self-contained headers in LLVM is a constant pain. Don't make the
same mistake in mlir. The only interesting change here is moving setSuccessor
to Instructions.cpp, which breaks the cycle between Instructions.h and
BasicBlock.h.
PiperOrigin-RevId: 222440816
This reverts the previous method which needs to create a new dialect with the
constant fold hook from TensorFlow. This new method uses a function object in
dialect to store the constant fold hook. Once a hook is registered to the
dialect, this function object will be assigned when the dialect is added to the
MLIRContext.
For the operations which are not registered, a new method getRegisteredDialects
is added to the MLIRContext to query the dialects which matches their op name
prefixes.
PiperOrigin-RevId: 222310149
This does create an inconsistency between the print formats (e.g., attributes are normally before operands) but fixes an invalid parsing & keeps constant uniform wrt itself (function or int attributes have type at same place). And specifying the specific type for a int/float attribute might get revised shortly.
Also add test to verify that output printed can be parsed again.
PiperOrigin-RevId: 221923893
We do some limited renaming here but define an alias for OperationInst so that a follow up cl can solely perform the large scale renaming.
PiperOrigin-RevId: 221726963
* Optionally attach the type of integer and floating point attributes to the attributes, this allows restricting a int/float to specific width.
- Currently this allows suffixing int/float constant with type [this might be revised in future].
- Default to i64 and f32 if not specified.
* For index types the APInt width used is 64.
* Change callers to request a specific attribute type.
* Store iN type with APInt of width N.
* This change does not handle the folding of constants of different types (e.g., doing int type promotions to support constant folding i3 and i32), and instead restricts the constant folding to only operate on the same types.
PiperOrigin-RevId: 221722699
Unranked tensors used to return an empty list of dimensions as their shape. This is confusing since an empty list of dimensions is also returned for 0-D tensors. In particular, hasStaticShape() method used to check if any of the dimensions are -1, which held for unranked tensors even though they don't have static shape.
PiperOrigin-RevId: 221571138
Array attributes can nested and function attributes can appear anywhere at that
level. They should be remapped to point to the generated CFGFunction after
ML-to-CFG conversion, similarly to plain function attributes. Extract the
nested attribute remapping functionality from the Parser to Utils. Extract out
the remapping function for individual Functions from the module remapping
function. Use these new functions in the ML-to-CFG conversion pass and in the
parser.
PiperOrigin-RevId: 221510997
* Add skeleton br/cond_br builtin ops.
* Add a terminator trait for operations.
* Mark ReturnOp as a Terminator.
The functionality for managing/parsing/verifying successors will be added in a follow up cl.
PiperOrigin-RevId: 221283000
Similarly to other types, introduce "get" and "getChecked" static member
functions for IntegerType. The latter emits errors to the error handler
registered with the MLIR context and returns a null type for the caller to
handle errors gracefully. This deduplicates type consistency checks between
the parser and the builder. Update the parser to call IntegerType::getChecked
for error reporting instead of the builder that would simply assert.
This CL completes the type system error emission refactoring: the parser now
only emits syntax-related errors for types while type factory systems may emit
type consistency errors.
PiperOrigin-RevId: 221165207
Branch instruction arguments were defined and used inconsistently across
different instructions, in both the spec and the implementation. In
particular, conditional and unconditional branch instructions were using
different syntax in the implementation. This led to the IR we produce not
being accepted by the parser. Update the printer to use common syntax: `(`
list-of-SSA-uses `:` list-of-types `)`. The motivation for choosing this
syntax as opposed to the one in the spec, `(` list-of-SSA-uses `)` `:`
list-of-types is double-fold. First, it is tricky to differentiate the label
of the false branch from the type while parsing conditional branches (which is
what apparently motivated the implementation to diverge from the spec in the
first place). Second, the ongoing convergence between terminator instructions
and other operations prompts for consistency between their operand list syntax.
After this change, the only remaining difference between the two is the use of
parentheses. Update the comment of the parser that did not correspond to the
code. Remove the unused isParenthesized argument from parseSSAUseAndTypeList.
Update the spec accordingly. Note that the examples in the spec were _not_
using the EBNF defined a couple of lines above them, but were using the current
syntax. Add a supplementary example of a branch to a basic block with multiple
arguments.
PiperOrigin-RevId: 221162655
Change the storage type to APInt from int64_t for IntegerAttr (following the change to APFloat storage in FloatAttr). Effectively a direct change from int64_t to 64-bit APInt throughout (the bitwidth hardcoded). This change also adds a getInt convenience method to IntegerAttr and replaces previous getValue calls with getInt calls.
While this changes updates the storage type, it does not update all constant folding calls.
PiperOrigin-RevId: 221082788
time. The "Fast and Flexible Instruction Selection With Constraints" paper
from CC2018 makes a credible argument that dynamic costs aren't actually
necessary/important, and we are not using them.
- Check in my "MLIR Generic DAG Rewriter Infrastructure" design doc into the
source tree.
PiperOrigin-RevId: 221017546
These are locations that form a collection of other source locations with an optional metadata attribute.
- Add initial support for print/dump for locations.
Location Printing Examples:
* Unknown : [unknown-location]
* FileLineColLoc : third_party/llvm/llvm/projects/google-mlir/test/TensorFlowLite/legalize.mlir:6:8
* FusedLoc : <"tfl-legalize">[third_party/llvm/llvm/projects/google-mlir/test/TensorFlowLite/legalize.mlir:6:8, third_party/llvm/llvm/projects/google-mlir/test/TensorFlowLite/legalize.mlir:7:8]
- Add diagnostic support for fused locs.
* Prints the first location as the main location and the remaining as "fused from here" notes:
e.g.
third_party/llvm/llvm/projects/google-mlir/test/TensorFlowLite/legalize.mlir:6:8: error: This is an error.
%1 = "tf.add"(%arg0, %0) : (i32, i32) -> i32
^
third_party/llvm/llvm/projects/google-mlir/test/TensorFlowLite/legalize.mlir:7:8: error: Fused from here.
%2 = "tf.relu"(%1) : (i32) -> i32
^
PiperOrigin-RevId: 220835552
This CL introduces the following related changes:
- move tensor element type validity checking to a static member function
TensorType::isValidElementType
- introduce get/getChecked similarly to MemRefType, where the checked function
emits errors and returns nullptrs;
- remove duplicate element type validity checking from the parser and rely on
the type constructor to emit errors instead.
PiperOrigin-RevId: 220694831
River Riddle