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
Value type abstraction for locations differ from others in that a Location can NOT be null. NOTE: dyn_cast returns an Optional<T>.
PiperOrigin-RevId: 220682078
Previously, index (aka affint) type was hidden under OtherType in the type API.
We will need to identify and operate on values of index types in the upcoming
MLFunc->CFGFunc(->LLVM) lowering passes. Materialize index type into a
separate class and make it visible to LLVM RTTI hierarchy directly.
Practically, index is an integer type of unknown bit width and is accetable in
most places where regular integer types are. This is purely an API change that
does not affect the IR.
After IndexType is separated out from OtherType, the remaining "other types"
are, in fact, TF-specific types only. Further renaming may be of interest.
PiperOrigin-RevId: 220614026
This is done by changing Type to be a POD interface around an underlying pointer storage and adding in-class support for isa/dyn_cast/cast.
PiperOrigin-RevId: 219372163
This is done by changing Attribute to be a POD interface around an underlying pointer storage and adding in-class support for isa/dyn_cast/cast.
PiperOrigin-RevId: 218764173
- Introduce Fourier-Motzkin variable elimination to eliminate a dimension from
a system of linear equalities/inequalities. Update isEmpty to use this.
Since FM is only exact on rational/real spaces, an emptiness check based on
this is guaranteed to be exact whenever it says the underlying set is empty;
if it says, it's not empty, there may still be no integer points in it.
Also, supports a version that computes "dark shadows".
- Test this by checking for "always false" conditionals in if statements.
- Unique IntegerSet's that are small (few constraints, few variables). This
basically means the canonical empty set and other small sets that are
likely commonly used get uniqued; allows checking for the canonical empty set
by pointer. IntegerSet::kUniquingThreshold gives the threshold constraint size
for uniqui'ing.
- rename simplify-affine-expr -> simplify-affine-structures
Other cleanup
- IntegerSet::numConstraints, AffineMap::numResults are no longer needed;
remove them.
- add copy assignment operators for AffineMap, IntegerSet.
- rename Invalid() -> Null() on AffineExpr, AffineMap, IntegerSet
- Misc cleanup for FlatAffineConstraints API
PiperOrigin-RevId: 218690456
For some of the constant vector / tesor, if the compiler doesn't need to
interpret their elements content, they can be stored in this class to save the
serialize / deserialize cost.
syntax:
`opaque<` tensor-type `,` opaque-string `>`
opaque-string ::= `0x` [0-9a-fA-F]*
PiperOrigin-RevId: 218399426
We should be able to represent arbitrary precision Float-point values inside
the IR, so compiler optimizations, such as constant folding can be done
independently on the compiling platform.
This CL also added a new field, AttrValueGetter, to the Attr class definition
for TableGen. This field is used to customize which mlir::Attr getter method to
get the defined PrimitiveType.
PiperOrigin-RevId: 218034983
The SparseElementsAttr uses (COO) Coordinate List encoding to represents a
sparse tensor / vector. Specifically, the coordinates and values are stored as
two dense elements attributes. The first dense elements attribute is a 2-D
attribute with shape [N, ndims], which contains the indices of the elements
with nonzero values in the constant vector/tensor. The second elements
attribute is a 1-D attribute list with shape [N], which supplies the values for
each element in the first elements attribute. ndims is the rank of the
vector/tensor and N is the total nonzero elements.
The syntax is:
`sparse<` (tensor-type | vector-type)`, ` indices-attribute-list, values-attribute-list `>`
Example: a sparse tensor
sparse<vector<3x4xi32>, [[0, 0], [1, 2]], [1, 2]> represents the dense tensor
[[1, 0, 0, 0]
[0, 0, 2, 0]
[0, 0, 0, 0]]
PiperOrigin-RevId: 217764319
The syntax of dense vecor/tensor attribute value is
`dense<` (tensor-type | vector-type)`,` attribute-list`>`
and
attribute-list ::= `[` attribute-list (`, ` attribute-list)* `]`.
The construction of the dense vector/tensor attribute takes a vector/tensor
type and a character array as arguments. The size of the input array should be
larger than the size specified by the type argument. It also assumes the
elements of the vector or tensor have been trunked to the data type sizes in
the input character array, so it extends the trunked data to 64 bits when it is
retrieved.
PiperOrigin-RevId: 217762811
This CL applies the same pattern as AffineMap to IntegerSet: a simple struct
that acts as the storage is allocated in the bump pointer. The IntegerSet is
immutable and accessed everywhere by value.
Note that unlike AffineMap, it is not possible to remove the MLIRContext
parameter when constructing an IntegerSet for now. One possible way to achieve
this would be to add an enum to distinguish between the mathematically empty
set, the universe set and other sets.
This is left for future discussion.
PiperOrigin-RevId: 216545361
This attribute represents a reference to a splat vector or tensor, where all
the elements have the same value. The syntax of the attribute is:
`splat<` (tensor-type | vector-type)`,` attribute-value `>`
PiperOrigin-RevId: 216537997
AbstractOperation* or an Identifier. This makes it possible to get to stuff in
AbstractOperation faster than going through a hash table lookup. This makes
constant folding a bit faster now, but will become more important with
subsequent changes.
PiperOrigin-RevId: 216476772
This CL applies the same pattern as AffineExpr to AffineMap: a simple struct
that acts as the storage is allocated in the bump pointer. The AffineMap is
immutable and accessed everywhere by value.
PiperOrigin-RevId: 216445930
This CL sketches what it takes for AffineExpr to fully have by-value semantics
and not be a not-so-smart pointer anymore.
This essentially makes the underyling class a simple storage struct and
implements the operations on the value type directly. Since there is no
forwarding of operations anymore, we can full isolate the storage class and
make a hard visibility barrier by moving detail::AffineExpr into
AffineExprDetail.h.
AffineExprDetail.h is only included where storage-related information is
needed.
PiperOrigin-RevId: 216385459
This CL:
1. performs the global codemod AffineXExpr->AffineXExprClass and
AffineXExprRef -> AffineXExpr;
2. simplifies function calls by removing the redundant MLIRContext parameter;
3. adds missing binary operator versions of scalar op AffineExpr where it
makes sense.
PiperOrigin-RevId: 216242674
This CL introduces a series of cleanups for AffineExpr value types:
1. to make it clear that the value types should be used, the pointer
AffineExpr types are put in the detail namespace. Unfortunately, since the
value type operator-> only forwards to the underlying pointer type, we
still
need to expose this in the include file for now;
2. AffineExprKind is ok to use, it thus comes out of detail and thus of
AffineExpr
3. getAffineDimExpr, getAffineSymbolExpr, getAffineConstantExpr are
similarly
extracted as free functions and their naming is mande consistent across
Builder, MLContext and AffineExpr
4. AffineBinaryOpEx::simplify functions are made into static free
functions.
In particular it is moved away from AffineMap.cpp where it does not belong
5. operator AffineExprType is made explicit
6. uses the binary operators everywhere possible
7. drops the pointer usage everywhere outside of AffineExpr.cpp,
MLIRContext.cpp and AsmPrinter.cpp
PiperOrigin-RevId: 216207212
1) affineint (as it is named) is not a type suitable for general computation (e.g. the multiply/adds in an integer matmul). It has undefined width and is undefined on overflow. They are used as the indices for forstmt because they are intended to be used as indexes inside the loop.
2) It can be used in both cfg and ml functions, and in cfg functions. As you mention, “symbols” are not affine, and we use affineint values for symbols.
3) Integers aren’t affine, the algorithms applied to them can be. :)
4) The only suitable use for affineint in MLIR is for indexes and dimension sizes (i.e. the bounds of those indexes).
PiperOrigin-RevId: 216057974
with a new one (of a potentially different rank/shape) with an optional index
remapping.
- introduce Utils::replaceAllMemRefUsesWith
- use this for DMA double buffering
(This CL also adds a few temporary utilities / code that will be done away with
once:
1) abstract DMA op's are added
2) memref deferencing side-effect / trait is available on op's
3) b/117159533 is resolved (memref index computation slices).
PiperOrigin-RevId: 215831373
This CL starts by replacing AffineExpr* with value-type AffineExprRef in a few
places in the IR. By a domino effect that is pretty telling of the
inconsistencies in the codebase, const is removed where it makes sense.
The rationale is that the decision was concisously made that unique'd types
have pointer semantics without const specifier. This is fine but we should be
consistent. In the end, the only logical invariant is that there should never
be such a thing as a const AffineExpr*, const AffineMap* or const IntegerSet*
in our codebase.
This CL takes a number of shortcuts to killing const with fire, in particular
forcing const AffineExprRef to return the underlying non-const
AffineExpr*. This will be removed once AffineExpr* has disappeared in
containers but for now such shortcuts allow a bit of sanity in this long quest
for cleanups.
The **only** places where const AffineExpr*, const AffineMap* or const
IntegerSet* may still appear is by transitive needs from containers,
comparison operators etc.
There is still one major thing remaining here: figure out why cast/dyn_cast
return me a const AffineXXX*, which in turn requires a bunch of ugly
const_casts. I suspect this is due to the classof
taking const AffineXXXExpr*. I wonder whether this is a side effect of 1., if
it is coming from llvm itself (I'd doubt it) or something else (clattner@?)
In light of this, the whole discussion about const makes total sense to me now
and I would systematically apply the rule that in the end, we should never
have any const XXX in our codebase for unique'd types (assuming we can remove
them all in containers and no additional constness constraint is added on us
from the outside world).
PiperOrigin-RevId: 215811554
This CL implements AffineExprBaseRef as a templated type to allow LLVM-style
casts to work properly. This also allows making AffineExprBaseRef::expr
private.
To achieve this, it is necessary to use llvm::simplify_type and make
AffineConstExpr derive from both AffineExpr and llvm::simplify<AffineExprRef>.
Note that llvm::simplify_type is just an interface to enable the proper
template resolution of isa/cast/dyn_cast but it otherwise holds no value.
Lastly note that certain dyn_cast operations wanted the const AffineExpr* form
of AffineExprBaseRef so I made the implicit constructor take that by default
and documented the immutable behavior. I think this is consistent with the
decision to make unique'd type immutable by convention and never use const on
them.
PiperOrigin-RevId: 215642247
This CL uniformizes the uses of AffineExprWrap outside of IR.
The public API of AffineExpr builder is modified to only use AffineExprWrap.
A few places access AffineExprWrap.expr, this is only while the API is in
transition to easily keep track (i.e. make expr private and let the compiler
track the errors).
Parser.cpp exhibits patterns that are dependent on nullptr values so
converting it is left for another CL.
PiperOrigin-RevId: 215642005
This CL proposes adding MLIRContext* to AffineExpr as discussed previously.
This allows the value class to not require the context in its constructor and
makes it a POD that it makes sense to pass by value everywhere.
A list of other RFC CLs will build on this. The RFC CLs are small incremental
pushes of the API which would be a pretty big change otherwise.
Pushing the thinking a little bit more it seems reasonable to use implicit
cast/constructor to/from AffineExpr*.
As this thing evolves, it looks to me like IR (and
probably Parser, for not so good reasons) want to operate on AffineExpr* and
the rest of the code wants to operate on the value type.
For this reason I think AffineExprImpl*/AffineExpr may also make sense but I
do not have a particular naming preference.
The jury is still out for naming decision between the above and
AffineExprBase*/AffineExpr or AffineExpr*/AffineExprRef.
PiperOrigin-RevId: 215641596
This CL argues that the builder API for AffineExpr should be used
with a lightweight wrapper that supports operators chaining.
This CL takes the ill-named AffineExprWrap and proposes a simple
set of operators with builtin constant simplifications.
This allows:
1. removing the getAddMulPureAffineExpr function;
2. avoiding concerns about constant vs non-constant simplifications
at **every call site**;
3. writing the mathematical expressions we want to write without unnecessary
obfuscations.
The points above represent pure technical debt that we don't want to carry on.
It is important to realize that this is not a mere convenience or "just sugar"
but reduction in cognitive overhead.
This thinking can be pushed significantly further, I have added some comments
with some basic ideas but we could make AffineMap, AffineApply and other
objects that use map applications more functional and value-based.
I am putting this out to get a first batch of reviews and see what people
think.
I think in my preferred design I would have the Builder directly return such
AffineExprPtr objects by value everywhere and avoid the boilerplate explicit
creations that I am doing by hand at this point.
Yes this AffineExprPtr would implicitly convert to AffineExpr* because that is
what it is.
PiperOrigin-RevId: 215641317
Alternatively, we can defined a TFComplexType with a width parameter in the
mlir, then both types can be converted to the same mlir type with different width (like IntegerType).
We chose to use a direct mapping because there are only two TF Complex types.
PiperOrigin-RevId: 213856651
- extend loop unroll-jam similar to loop unroll for affine bounds
- extend both loop unroll/unroll-jam to deal with cleanup loop for non multiple
of unroll factor.
- extend promotion of single iteration loops to work with affine bounds
- fix typo bugs in loop unroll
- refactor common code b/w loop unroll and loop unroll-jam
- move prototypes of non-pass transforms to LoopUtils.h
- add additional builder methods.
- introduce loopUnrollUpTo(factor) to unroll by either factor or trip count,
whichever is less.
- remove Statement::isInnermost (not used for now - will come back at the right
place/in right form later)
PiperOrigin-RevId: 213471227
Use these methods to simplify existing code. Rename getConstantMap
getConstantAffineMap. Move declarations to group similar ones together.
PiperOrigin-RevId: 212814829
unroll/unroll-and-jam more powerful; add additional affine expr builder methods
- use previously added analysis/simplification to infer multiple of unroll
factor trip counts, making loop unroll/unroll-and-jam more general.
- for loop unroll, support bounds that are single result affine map's with the
same set of operands. For unknown loop bounds, loop unroll will now work as
long as trip count can be determined to be a multiple of unroll factor.
- extend getConstantTripCount to deal with single result affine map's with the
same operands. move it to mlir/Analysis/LoopAnalysis.cpp
- add additional builder utility methods for affine expr arithmetic
(difference, mod/floordiv/ceildiv w.r.t postitive constant). simplify code to
use the utility methods.
- move affine analysis routines to AffineAnalysis.cpp/.h from
AffineStructures.cpp/.h.
- Rename LoopUnrollJam to LoopUnrollAndJam to match class name.
- add an additional simplification for simplifyFloorDiv, simplifyCeilDiv
- Rename AffineMap::getNumOperands() getNumInputs: an affine map by itself does
not have operands. Operands are passed to it through affine_apply, from loop
bounds/if condition's, etc., operands are stored in the latter.
This should be sufficiently powerful for now as far as unroll/unroll-and-jam go for TPU
code generation, and can move to other analyses/transformations.
Loop nests like these are now unrolled without any cleanup loop being generated.
for %i = 1 to 100 {
// unroll factor 4: no cleanup loop will be generated.
for %j = (d0) -> (d0) (%i) to (d0) -> (5*d0 + 3) (%i) {
%x = "foo"(%j) : (affineint) -> i32
}
}
for %i = 1 to 100 {
// unroll factor 4: no cleanup loop will be generated.
for %j = (d0) -> (d0) (%i) to (d0) -> (d0 - d mod 4 - 1) (%i) {
%y = "foo"(%j) : (affineint) -> i32
}
}
for %i = 1 to 100 {
for %j = (d0) -> (d0) (%i) to (d0) -> (d0 + 128) (%i) {
%x = "foo"() : () -> i32
}
}
TODO(bondhugula): extend this to LoopUnrollAndJam as well in the next CL (with minor
changes).
PiperOrigin-RevId: 212661212
This CL also includes two other minor changes:
- change the implemented syntax from 'if (cond)' to 'if cond', as specified by MLIR spec.
- a minor fix to the implementation of the ForStmt.
PiperOrigin-RevId: 210618122
(and more useful) way rather than hacking up a pile of attributes for it. In
the future this will grow to represent inlined locations, fusion cases etc, but
for now we start with simple Unknown and File/Line/Col locations. NFC.
PiperOrigin-RevId: 210485775
This revamps implementation of the loop bounds in the ForStmt, using general representation that supports operands. The frequent case of constant bounds is supported
via special access methods.
This also includes:
- Operand iterators for the Statement class.
- OpPointer::is() method to query the class of the Operation.
- Support for the bound shorthand notation parsing and printing.
- Validity checks for the bound operands used as dim ids and symbols
I didn't mean this CL to be so large. It just happened this way, as one thing led to another.
PiperOrigin-RevId: 210204858
- Implement support for the TensorFlow 'If' op, the first TF op definition.
- Fill in some missing basic infra, including the ability to split a basic block, the ability to create a branch with operands, etc.
- Implement basic lowering for some simple forms of If, where the condition is a zero-D bool tensor and when all the types line up. Future patches will generalize this.
There is still much to be done here. I'd like to get some example graphs coming from the converter to play with to direct this work.
PiperOrigin-RevId: 210198760
operation and statement to have a location, and make it so a location is
required to be specified whenever you make one (though a null location is still
allowed). This is to encourage compiler authors to propagate loc info
properly, allowing our failability story to work well.
This is still a WIP - it isn't clear if we want to continue abusing Attribute
for location information, or whether we should introduce a new class heirarchy
to do so. This is good step along the way, and unblocks some of the tf/xla
work that builds upon it.
PiperOrigin-RevId: 210001406
resolver support.
Still TODO are verifier support (to make sure you don't use an attribute for a
function in another module) and the TODO in ModuleParser::finalizeModule that I
will handle in the next patch.
PiperOrigin-RevId: 209361648
- introduce affine integer sets into the IR
- parse and print affine integer sets (both inline or outlined) similar to
affine maps
- use integer set for IfStmt's conditional, and implement parsing of IfStmt's
conditional
- fixed an affine expr paren omission bug while one this.
TODO: parse/represent/print MLValue operands to affine integer set references.
PiperOrigin-RevId: 207779408
encapsulates an operation that is yet to be created. This is a patch towards
custom ops providing create methods that don't need to be templated, allowing
them to move out of line in the future.
PiperOrigin-RevId: 207725557
Fix b/112039912 - we were recording 'i' instead of '%i' for loop induction variables causing "use of undefined SSA value" error.
PiperOrigin-RevId: 206884644
Induction variables are implemented by inheriting ForStmt from MLValue. ForStmt provides APIs that make this design decision invisible to the ForStmt users.
This CL in combination with cl/206253643 resolves http://b/111769060.
PiperOrigin-RevId: 206655937
and OtherType. Other type is now the thing that holds AffineInt, Control,
eventually Resource, Variant, String, etc. FloatType holds the floating point
types, and allows convenient query of isa<FloatType>().
This fixes issues where we allowed control to be the element type of tensor,
memref, vector. At the same time, ban AffineInt from being an element of a
vector/memref/tensor as well since we don't need it.
I updated the spec to match this as well.
PiperOrigin-RevId: 206361942
* Add tf_control as primitive type;
* Allow $ in bare-id to allow attributes with $ (to make it trivially to mangle a TF attribute);
PiperOrigin-RevId: 206342642
- Drop sub-classing of affine binary op expressions.
- Drop affine expr op kind sub. Represent it as multiply by -1 and add. This
will also be in line with the math form when we'll need to represent a system of
linear equalities/inequalities: the negative number goes into the coefficient
of an affine form. (For eg. x_1 + (-1)*x_2 + 3*x_3 + (-2) >= 0). The folding
simplification will transparently deal with multiplying the -1 with any other
constants. This also means we won't need to simplify a multiply expression
like in x_1 + (-2)*x_2 to a subtract expression (x_1 - 2*x_2) for
canonicalization/uniquing.
- When we print the IR, we will still pretty print to a subtract when possible.
PiperOrigin-RevId: 205298958
Loop bounds and presumed to be constants for now and are stored in ForStmt as affine constant expressions. ML function arguments, return statement operands and loop variable name are dropped for now.
PiperOrigin-RevId: 205256208
use it.
This also removes "operand" from the affine expr classes: it is unnecessary
verbosity and "operand" will mean something very specific for SSA stuff (we
will have an Operand type).
PiperOrigin-RevId: 203976504
River Riddle