Commit Graph

30 Commits

Author SHA1 Message Date
River Riddle 0c65cf283c Move the AffineFor loop bound folding to a canonicalization pattern on the AffineForOp.
PiperOrigin-RevId: 232610715
2019-03-29 16:16:11 -07:00
River Riddle bf9c381d1d Remove InstWalker and move all instruction walking to the api facilities on Function/Block/Instruction.
PiperOrigin-RevId: 232388113
2019-03-29 16:12:59 -07:00
River Riddle b499277fb6 Remove remaining usages of OperationInst in lib/Transforms.
PiperOrigin-RevId: 232323671
2019-03-29 16:10:53 -07:00
River Riddle a3d9ccaecb Replace the walkOps/visitOperationInst variants from the InstWalkers with the Instruction variants.
PiperOrigin-RevId: 232322030
2019-03-29 16:10:24 -07:00
River Riddle 5052bd8582 Define the AffineForOp and replace ForInst with it. This patch is largely mechanical, i.e. changing usages of ForInst to OpPointer<AffineForOp>. An important difference is that upon construction an AffineForOp no longer automatically creates the body and induction variable. To generate the body/iv, 'createBody' can be called on an AffineForOp with no body.
PiperOrigin-RevId: 232060516
2019-03-29 16:06:49 -07:00
Smit Hinsu 0eebe6ffd9 Update comment in the constant folding pass as constant folding is supported even when not all operands are constants
PiperOrigin-RevId: 229670189
2019-03-29 15:24:28 -07:00
Lei Zhang 61ec6c0992 Swap the type and attribute parameter in ConstantOp::build()
This is to keep consistent with other TableGen generated builders
so that we can also use this builder in TableGen rules.

PiperOrigin-RevId: 229244630
2019-03-29 15:14:52 -07:00
Chris Lattner 7974889f54 Update and generalize various passes to work on both CFG and ML functions,
simplifying them in minor ways.  The only significant cleanup here
is the constant folding pass.  All the other changes are simple and easy,
but this is still enough to shrink the compiler by 45LOC.

The one pass left to merge is the CSE pass, which will be move involved, so I'm
splitting it out to its own patch (which I'll tackle right after this).

This is step 28/n towards merging instructions and statements.

PiperOrigin-RevId: 227328115
2019-03-29 14:49:52 -07:00
Chris Lattner 456ad6a8e0 Standardize naming of statements -> instructions, revisting the code base to be
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
2019-03-29 14:44:30 -07:00
Chris Lattner 69d9e990fa Eliminate the using decls for MLFunction and CFGFunction standardizing on
Function.

This is step 18/n towards merging instructions and statements, NFC.

PiperOrigin-RevId: 227139399
2019-03-29 14:43:13 -07:00
Chris Lattner 5187cfcf03 Merge Operation into OperationInst and standardize nomenclature around
OperationInst.  This is a big mechanical patch.

This is step 16/n towards merging instructions and statements, NFC.

PiperOrigin-RevId: 227093712
2019-03-29 14:42:23 -07:00
Chris Lattner 4c05f8cac6 Merge CFGFuncBuilder/MLFuncBuilder/FuncBuilder together into a single new
FuncBuilder class.  Also rename SSAValue.cpp to Value.cpp

This is step 12/n towards merging instructions and statements, NFC.

PiperOrigin-RevId: 227067644
2019-03-29 14:40:22 -07:00
Chris Lattner 3f190312f8 Merge SSAValue, CFGValue, and MLValue together into a single Value class, which
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
2019-03-29 14:40:06 -07:00
Chris Lattner 776b035646 Eliminate the Instruction, BasicBlock, CFGFunction, MLFunction, and ExtFunction classes, using the Statement/StmtBlock hierarchy and Function instead.
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
2019-03-29 14:39:49 -07:00
Jacques Pienaar cc9a6ed09d Initialize Pass with PassID.
The passID is not currently stored in Pass but this avoids the unused variable warning. The passID is used to uniquely identify passes, currently this is only stored/used in PassInfo.

PiperOrigin-RevId: 220485662
2019-03-29 13:50:34 -07:00
Jacques Pienaar 6f0fb22723 Add static pass registration
Add static pass registration and change mlir-opt to use it. Future work is needed to refactor the registration for PassManager usage.

Change build targets to alwayslink to enforce registration.

PiperOrigin-RevId: 220390178
2019-03-29 13:49:34 -07:00
Uday Bondhugula 8201e19e3d Introduce memref bound checking.
Introduce analysis to check memref accesses (in MLFunctions) for out of bound
ones. It works as follows:

$ mlir-opt -memref-bound-check test/Transforms/memref-bound-check.mlir

/tmp/single.mlir:10:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#1
      %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32>
           ^
/tmp/single.mlir:10:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#1
      %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32>
           ^
/tmp/single.mlir:10:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#2
      %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32>
           ^
/tmp/single.mlir:10:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#2
      %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32>
           ^
/tmp/single.mlir:12:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#1
      %y = load %B[%idy] : memref<128 x i32>
           ^
/tmp/single.mlir:12:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#1
      %y = load %B[%idy] : memref<128 x i32>
           ^
#map0 = (d0, d1) -> (d0, d1)
#map1 = (d0, d1) -> (d0 * 128 - d1)
mlfunc @test() {
  %0 = alloc() : memref<9x9xi32>
  %1 = alloc() : memref<128xi32>
  for %i0 = -1 to 9 {
    for %i1 = -1 to 9 {
      %2 = affine_apply #map0(%i0, %i1)
      %3 = load %0[%2tensorflow/mlir#0, %2tensorflow/mlir#1] : memref<9x9xi32>
      %4 = affine_apply #map1(%i0, %i1)
      %5 = load %1[%4] : memref<128xi32>
    }
  }
  return
}

- Improves productivity while manually / semi-automatically developing MLIR for
  testing / prototyping; also provides an indirect way to catch errors in
  transformations.

- This pass is an easy way to test the underlying affine analysis
  machinery including low level routines.

Some code (in getMemoryRegion()) borrowed from @andydavis cl/218263256.

While on this:

- create mlir/Analysis/Passes.h; move Pass.h up from mlir/Transforms/ to mlir/

- fix a bug in AffineAnalysis.cpp::toAffineExpr

TODO: extend to non-constant loop bounds (straightforward). Will transparently
work for all accesses once floordiv, mod, ceildiv are supported in the
AffineMap -> FlatAffineConstraints conversion.
PiperOrigin-RevId: 219397961
2019-03-29 13:46:08 -07:00
River Riddle 4c465a181d Implement value type abstraction for types.
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
2019-03-29 13:45:54 -07:00
River Riddle 792d1c25e4 Implement value type abstraction for attributes.
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
2019-03-29 13:39:19 -07:00
Lei Zhang 52a0e58bdb Change typedef to using to be consistent across the codebase
Google C++ style guide also prefers using to typedef.

PiperOrigin-RevId: 218541849
2019-03-29 13:37:55 -07:00
Chris Lattner 7850258c49 Introduce a new Operation::erase helper to generalize some code in
the pattern matcher / canonicalizer, and rename existing eraseFromBlock methods
to align with it.

PiperOrigin-RevId: 218104455
2019-03-29 13:34:51 -07:00
Uday Bondhugula 2f1103bd93 Loop bound constant folding: follow-up / address comments from cl/215997346
- create a single function to fold both bounds
- move bound constant folding into transforms

PiperOrigin-RevId: 217954701
2019-03-29 13:33:55 -07:00
Feng Liu 34927e2474 Rename Operation::getAs to Operation::dyn_cast
Also rename Operation::is to Operation::isa
Introduce Operation::cast

All of these are for consistency with global dyn_cast/cast/isa operators.

PiperOrigin-RevId: 217878786
2019-03-29 13:33:41 -07:00
Chris Lattner 7e7157fd1d Various improvements to pattern matching and other infra:
- Make it so OpPointer implicitly converts to SSAValue* when the underlying op
   has a single value.  This eliminates a lot more ->getResult() calls and makes
   the behavior more LLVM-like
 - Fill out PatternBenefit to be typed instead of just a typedef for int with
   magic numbers.
 - Simplify various code due to these changes.

PiperOrigin-RevId: 217020717
2019-03-29 13:29:49 -07:00
Jacques Pienaar 764fd035b0 Split BuiltinOps out of StandardOps.
* Move Return, Constant and AffineApply out into BuiltinOps;
* BuiltinOps are always registered, while StandardOps follow the same dynamic registration;
* Kept isValidX in MLValue as we don't have a verify on AffineMap so need to keep it callable from Parser (I wanted to move it to be called in verify instead);

PiperOrigin-RevId: 216592527
2019-03-29 13:28:12 -07:00
Uday Bondhugula d18ae9e2c7 Constant folding for loop bounds.
- Fold the lower/upper bound of a loop to a constant whenever the result of the
  application of the bound's affine map on the operand list yields a constant.

- Update/complete 'for' stmt's API to set lower/upper bounds with operands.
  Resolve TODOs for ForStmt::set{Lower,Upper}Bound.

- Moved AffineExprConstantFolder into AffineMap.cpp and added
  AffineMap::constantFold to be used by both AffineApplyOp and
  ForStmt::constantFoldBound.

PiperOrigin-RevId: 215997346
2019-03-29 13:24:01 -07:00
Chris Lattner 6822c4e29c Implement support for constant folding operations even when their operands are
not all constant.  Implement support for folding dim, x*0, and affine_apply.

PiperOrigin-RevId: 215917432
2019-03-29 13:23:32 -07:00
Uday Bondhugula 501462ac47 Use statement walker for constant folding.
- makes the code compact (gets rid of MLFunction walking logic)
- makes it natural to extend to fold affine map loop bounds
  and if conditions (upcoming CL)

PiperOrigin-RevId: 214668957
2019-03-29 13:19:32 -07:00
Chris Lattner d6f8ec7bac Introduce [post]dominator tree and related infrastructure, use it in CFG func
verifier.  We get most of this infrastructure directly from LLVM, we just
need to adapt it to our CFG abstraction.

This has a few unrelated changes engangled in it:
 - getFunction() in various classes was const incorrect, fix it.
 - This moves Verifier.cpp to the analysis library, since Verifier depends on
   dominance and these are both really analyses.
 - IndexedAccessorIterator::reference was defined wrong, leading to really
   exciting template errors that were fun to diagnose.
 - This flips the boolean sense of the foldOperation() function in constant
   folding pass in response to previous patch feedback.

PiperOrigin-RevId: 214046593
2019-03-29 13:17:20 -07:00
Chris Lattner 82eb284a53 Implement support for constant folding operations and a simple constant folding
optimization pass:

 - Give the ability for operations to implement a constantFold hook (a simple
   one for single-result ops as well as general support for multi-result ops).
 - Implement folding support for constant and addf.
 - Implement support in AbstractOperation and Operation to make this usable by
   clients.
 - Implement a very simple constant folding pass that does top down folding on
   CFG and ML functions, with a testcase that exercises all the above stuff.

Random cleanups:
 - Improve the build APIs for ConstantOp.
 - Stop passing "-o -" to mlir-opt in the testsuite, since that is the default.

PiperOrigin-RevId: 213749809
2019-03-29 13:16:33 -07:00