llvm-capstone/mlir/lib/IR/Builders.cpp

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//===- Builders.cpp - Helpers for constructing MLIR Classes ---------------===//
//
// Copyright 2019 The MLIR Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// =============================================================================
#include "mlir/IR/Builders.h"
#include "mlir/IR/AffineExpr.h"
#include "mlir/IR/AffineMap.h"
#include "mlir/IR/Attributes.h"
#include "mlir/IR/IntegerSet.h"
#include "mlir/IR/Location.h"
#include "mlir/IR/Module.h"
#include "mlir/IR/Types.h"
using namespace mlir;
Builder::Builder(Module *module) : context(module->getContext()) {}
Identifier Builder::getIdentifier(StringRef str) {
return Identifier::get(str, context);
}
Module *Builder::createModule() { return new Module(context); }
//===----------------------------------------------------------------------===//
// Locations.
//===----------------------------------------------------------------------===//
UnknownLoc *Builder::getUnknownLoc() { return UnknownLoc::get(context); }
UniquedFilename Builder::getUniquedFilename(StringRef filename) {
return UniquedFilename::get(filename, context);
}
FileLineColLoc *Builder::getFileLineColLoc(UniquedFilename filename,
unsigned line, unsigned column) {
return FileLineColLoc::get(filename, line, column, context);
}
//===----------------------------------------------------------------------===//
// Types.
//===----------------------------------------------------------------------===//
FloatType *Builder::getBF16Type() { return Type::getBF16(context); }
FloatType *Builder::getF16Type() { return Type::getF16(context); }
FloatType *Builder::getF32Type() { return Type::getF32(context); }
FloatType *Builder::getF64Type() { return Type::getF64(context); }
OtherType *Builder::getIndexType() { return Type::getIndex(context); }
OtherType *Builder::getTFControlType() { return Type::getTFControl(context); }
OtherType *Builder::getTFResourceType() { return Type::getTFResource(context); }
OtherType *Builder::getTFVariantType() { return Type::getTFVariant(context); }
OtherType *Builder::getTFComplex64Type() {
return Type::getTFComplex64(context);
}
OtherType *Builder::getTFComplex128Type() {
return Type::getTFComplex128(context);
}
OtherType *Builder::getTFF32REFType() { return Type::getTFF32REF(context); }
OtherType *Builder::getTFStringType() { return Type::getTFString(context); }
IntegerType *Builder::getIntegerType(unsigned width) {
return Type::getInteger(width, context);
}
FunctionType *Builder::getFunctionType(ArrayRef<Type *> inputs,
ArrayRef<Type *> results) {
return FunctionType::get(inputs, results, context);
}
MemRefType *Builder::getMemRefType(ArrayRef<int> shape, Type *elementType,
ArrayRef<AffineMap> affineMapComposition,
unsigned memorySpace) {
return MemRefType::get(shape, elementType, affineMapComposition, memorySpace);
}
VectorType *Builder::getVectorType(ArrayRef<int> shape, Type *elementType) {
return VectorType::get(shape, elementType);
}
RankedTensorType *Builder::getTensorType(ArrayRef<int> shape,
Type *elementType) {
return RankedTensorType::get(shape, elementType);
}
UnrankedTensorType *Builder::getTensorType(Type *elementType) {
return UnrankedTensorType::get(elementType);
}
//===----------------------------------------------------------------------===//
// Attributes.
//===----------------------------------------------------------------------===//
BoolAttr *Builder::getBoolAttr(bool value) {
return BoolAttr::get(value, context);
}
IntegerAttr *Builder::getIntegerAttr(int64_t value) {
return IntegerAttr::get(value, context);
}
FloatAttr *Builder::getFloatAttr(double value) {
return FloatAttr::get(value, context);
}
StringAttr *Builder::getStringAttr(StringRef bytes) {
return StringAttr::get(bytes, context);
}
ArrayAttr *Builder::getArrayAttr(ArrayRef<Attribute *> value) {
return ArrayAttr::get(value, context);
}
AffineMapAttr *Builder::getAffineMapAttr(AffineMap map) {
return AffineMapAttr::get(map);
}
TypeAttr *Builder::getTypeAttr(Type *type) {
return TypeAttr::get(type, context);
}
FunctionAttr *Builder::getFunctionAttr(const Function *value) {
return FunctionAttr::get(value, context);
}
//===----------------------------------------------------------------------===//
// Affine Expressions, Affine Maps, and Integet Sets.
//===----------------------------------------------------------------------===//
AffineMap Builder::getAffineMap(unsigned dimCount, unsigned symbolCount,
ArrayRef<AffineExpr> results,
ArrayRef<AffineExpr> rangeSizes) {
return AffineMap::get(dimCount, symbolCount, results, rangeSizes);
}
AffineExpr Builder::getAffineDimExpr(unsigned position) {
return mlir::getAffineDimExpr(position, context);
}
AffineExpr Builder::getAffineSymbolExpr(unsigned position) {
return mlir::getAffineSymbolExpr(position, context);
}
AffineExpr Builder::getAffineConstantExpr(int64_t constant) {
return mlir::getAffineConstantExpr(constant, context);
}
IntegerSet *Builder::getIntegerSet(unsigned dimCount, unsigned symbolCount,
ArrayRef<AffineExpr> constraints,
ArrayRef<bool> isEq) {
return IntegerSet::get(dimCount, symbolCount, constraints, isEq, context);
}
AffineMap Builder::getConstantAffineMap(int64_t val) {
return AffineMap::get(/*dimCount=*/0, /*symbolCount=*/0,
{getAffineConstantExpr(val)}, {});
}
AffineMap Builder::getDimIdentityMap() {
return AffineMap::get(/*dimCount=*/1, /*symbolCount=*/0,
{getAffineDimExpr(0)}, {});
}
AffineMap Builder::getMultiDimIdentityMap(unsigned rank) {
SmallVector<AffineExpr, 4> dimExprs;
dimExprs.reserve(rank);
for (unsigned i = 0; i < rank; ++i)
dimExprs.push_back(getAffineDimExpr(i));
return AffineMap::get(/*dimCount=*/rank, /*symbolCount=*/0, dimExprs, {});
}
AffineMap Builder::getSymbolIdentityMap() {
return AffineMap::get(/*dimCount=*/0, /*symbolCount=*/1,
{getAffineSymbolExpr(0)}, {});
}
AffineMap Builder::getSingleDimShiftAffineMap(int64_t shift) {
// expr = d0 + shift.
auto expr = getAffineDimExpr(0) + shift;
return AffineMap::get(/*dimCount=*/1, /*symbolCount=*/0, {expr}, {});
Introduce loop body skewing / loop pipelining / loop shifting utility. - loopBodySkew shifts statements of a loop body by stmt-wise delays, and is typically meant to be used to: - allow overlap of non-blocking start/wait until completion operations with other computation - allow shifting of statements (for better register reuse/locality/parallelism) - software pipelining (when applied to the innermost loop) - an additional argument specifies whether to unroll the prologue and epilogue. - add method to check SSA dominance preservation. - add a fake loop pipeline pass to test this utility. Sample input/output are below. While on this, fix/add following: - fix minor bug in getAddMulPureAffineExpr - add additional builder methods for common affine map cases - fix const_operand_iterator's for ForStmt, etc. When there is no such thing as 'const MLValue', the iterator shouldn't be returning const MLValue's. Returning MLValue is const correct. Sample input/output examples: 1) Simplest case: shift second statement by one. Input: for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint } Output: #map0 = (d0) -> (d0 - 1) mlfunc @loop_nest_simple1() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint for %i0 = 1 to 7 { %1 = "foo"(%i0) : (affineint) -> affineint %2 = affine_apply #map0(%i0) %3 = "bar"(%2) : (affineint) -> affineint } %4 = affine_apply #map0(%c8) %5 = "bar"(%4) : (affineint) -> affineint return } 2) DMA overlap: shift dma.wait and compute by one. Input for %i = 0 to 7 { %pingpong = affine_apply (d0) -> (d0 mod 2) (%i) "dma.enqueue"(%pingpong) : (affineint) -> affineint %pongping = affine_apply (d0) -> (d0 mod 2) (%i) "dma.wait"(%pongping) : (affineint) -> affineint "compute1"(%pongping) : (affineint) -> affineint } Output #map0 = (d0) -> (d0 mod 2) #map1 = (d0) -> (d0 - 1) #map2 = ()[s0] -> (s0 + 7) mlfunc @loop_nest_dma() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = affine_apply #map0(%c0) %1 = "dma.enqueue"(%0) : (affineint) -> affineint for %i0 = 1 to 7 { %2 = affine_apply #map0(%i0) %3 = "dma.enqueue"(%2) : (affineint) -> affineint %4 = affine_apply #map1(%i0) %5 = affine_apply #map0(%4) %6 = "dma.wait"(%5) : (affineint) -> affineint %7 = "compute1"(%5) : (affineint) -> affineint } %8 = affine_apply #map1(%c8) %9 = affine_apply #map0(%8) %10 = "dma.wait"(%9) : (affineint) -> affineint %11 = "compute1"(%9) : (affineint) -> affineint return } 3) With arbitrary affine bound maps: Shift last two statements by two. Input: for %i = %N to ()[s0] -> (s0 + 7)()[%N] { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foo_bar"(%i) : (affineint) -> (affineint) "bar_foo"(%i) : (affineint) -> (affineint) } Output #map0 = ()[s0] -> (s0 + 1) #map1 = ()[s0] -> (s0 + 2) #map2 = ()[s0] -> (s0 + 7) #map3 = (d0) -> (d0 - 2) #map4 = ()[s0] -> (s0 + 8) #map5 = ()[s0] -> (s0 + 9) for %i0 = %arg0 to #map0()[%arg0] { %0 = "foo"(%i0) : (affineint) -> affineint %1 = "bar"(%i0) : (affineint) -> affineint } for %i1 = #map1()[%arg0] to #map2()[%arg0] { %2 = "foo"(%i1) : (affineint) -> affineint %3 = "bar"(%i1) : (affineint) -> affineint %4 = affine_apply #map3(%i1) %5 = "foo_bar"(%4) : (affineint) -> affineint %6 = "bar_foo"(%4) : (affineint) -> affineint } for %i2 = #map4()[%arg0] to #map5()[%arg0] { %7 = affine_apply #map3(%i2) %8 = "foo_bar"(%7) : (affineint) -> affineint %9 = "bar_foo"(%7) : (affineint) -> affineint } 4) Shift one by zero, second by one, third by two for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foobar"(%i) : (affineint) -> affineint } #map0 = (d0) -> (d0 - 1) #map1 = (d0) -> (d0 - 2) #map2 = ()[s0] -> (s0 + 7) %c9 = constant 9 : affineint %c8 = constant 8 : affineint %c1 = constant 1 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint %1 = "foo"(%c1) : (affineint) -> affineint %2 = affine_apply #map0(%c1) %3 = "bar"(%2) : (affineint) -> affineint for %i0 = 2 to 7 { %4 = "foo"(%i0) : (affineint) -> affineint %5 = affine_apply #map0(%i0) %6 = "bar"(%5) : (affineint) -> affineint %7 = affine_apply #map1(%i0) %8 = "foobar"(%7) : (affineint) -> affineint } %9 = affine_apply #map0(%c8) %10 = "bar"(%9) : (affineint) -> affineint %11 = affine_apply #map1(%c8) %12 = "foobar"(%11) : (affineint) -> affineint %13 = affine_apply #map1(%c9) %14 = "foobar"(%13) : (affineint) -> affineint 5) SSA dominance violated; no shifting if a shift is specified for the second statement. for %i = 0 to 7 { %x = "foo"(%i) : (affineint) -> affineint "bar"(%x) : (affineint) -> affineint } PiperOrigin-RevId: 214975731
2018-09-28 12:17:26 -07:00
}
AffineMap Builder::getShiftedAffineMap(AffineMap map, int64_t shift) {
SmallVector<AffineExpr, 4> shiftedResults;
shiftedResults.reserve(map.getNumResults());
for (auto resultExpr : map.getResults()) {
shiftedResults.push_back(resultExpr + shift);
Introduce loop body skewing / loop pipelining / loop shifting utility. - loopBodySkew shifts statements of a loop body by stmt-wise delays, and is typically meant to be used to: - allow overlap of non-blocking start/wait until completion operations with other computation - allow shifting of statements (for better register reuse/locality/parallelism) - software pipelining (when applied to the innermost loop) - an additional argument specifies whether to unroll the prologue and epilogue. - add method to check SSA dominance preservation. - add a fake loop pipeline pass to test this utility. Sample input/output are below. While on this, fix/add following: - fix minor bug in getAddMulPureAffineExpr - add additional builder methods for common affine map cases - fix const_operand_iterator's for ForStmt, etc. When there is no such thing as 'const MLValue', the iterator shouldn't be returning const MLValue's. Returning MLValue is const correct. Sample input/output examples: 1) Simplest case: shift second statement by one. Input: for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint } Output: #map0 = (d0) -> (d0 - 1) mlfunc @loop_nest_simple1() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint for %i0 = 1 to 7 { %1 = "foo"(%i0) : (affineint) -> affineint %2 = affine_apply #map0(%i0) %3 = "bar"(%2) : (affineint) -> affineint } %4 = affine_apply #map0(%c8) %5 = "bar"(%4) : (affineint) -> affineint return } 2) DMA overlap: shift dma.wait and compute by one. Input for %i = 0 to 7 { %pingpong = affine_apply (d0) -> (d0 mod 2) (%i) "dma.enqueue"(%pingpong) : (affineint) -> affineint %pongping = affine_apply (d0) -> (d0 mod 2) (%i) "dma.wait"(%pongping) : (affineint) -> affineint "compute1"(%pongping) : (affineint) -> affineint } Output #map0 = (d0) -> (d0 mod 2) #map1 = (d0) -> (d0 - 1) #map2 = ()[s0] -> (s0 + 7) mlfunc @loop_nest_dma() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = affine_apply #map0(%c0) %1 = "dma.enqueue"(%0) : (affineint) -> affineint for %i0 = 1 to 7 { %2 = affine_apply #map0(%i0) %3 = "dma.enqueue"(%2) : (affineint) -> affineint %4 = affine_apply #map1(%i0) %5 = affine_apply #map0(%4) %6 = "dma.wait"(%5) : (affineint) -> affineint %7 = "compute1"(%5) : (affineint) -> affineint } %8 = affine_apply #map1(%c8) %9 = affine_apply #map0(%8) %10 = "dma.wait"(%9) : (affineint) -> affineint %11 = "compute1"(%9) : (affineint) -> affineint return } 3) With arbitrary affine bound maps: Shift last two statements by two. Input: for %i = %N to ()[s0] -> (s0 + 7)()[%N] { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foo_bar"(%i) : (affineint) -> (affineint) "bar_foo"(%i) : (affineint) -> (affineint) } Output #map0 = ()[s0] -> (s0 + 1) #map1 = ()[s0] -> (s0 + 2) #map2 = ()[s0] -> (s0 + 7) #map3 = (d0) -> (d0 - 2) #map4 = ()[s0] -> (s0 + 8) #map5 = ()[s0] -> (s0 + 9) for %i0 = %arg0 to #map0()[%arg0] { %0 = "foo"(%i0) : (affineint) -> affineint %1 = "bar"(%i0) : (affineint) -> affineint } for %i1 = #map1()[%arg0] to #map2()[%arg0] { %2 = "foo"(%i1) : (affineint) -> affineint %3 = "bar"(%i1) : (affineint) -> affineint %4 = affine_apply #map3(%i1) %5 = "foo_bar"(%4) : (affineint) -> affineint %6 = "bar_foo"(%4) : (affineint) -> affineint } for %i2 = #map4()[%arg0] to #map5()[%arg0] { %7 = affine_apply #map3(%i2) %8 = "foo_bar"(%7) : (affineint) -> affineint %9 = "bar_foo"(%7) : (affineint) -> affineint } 4) Shift one by zero, second by one, third by two for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foobar"(%i) : (affineint) -> affineint } #map0 = (d0) -> (d0 - 1) #map1 = (d0) -> (d0 - 2) #map2 = ()[s0] -> (s0 + 7) %c9 = constant 9 : affineint %c8 = constant 8 : affineint %c1 = constant 1 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint %1 = "foo"(%c1) : (affineint) -> affineint %2 = affine_apply #map0(%c1) %3 = "bar"(%2) : (affineint) -> affineint for %i0 = 2 to 7 { %4 = "foo"(%i0) : (affineint) -> affineint %5 = affine_apply #map0(%i0) %6 = "bar"(%5) : (affineint) -> affineint %7 = affine_apply #map1(%i0) %8 = "foobar"(%7) : (affineint) -> affineint } %9 = affine_apply #map0(%c8) %10 = "bar"(%9) : (affineint) -> affineint %11 = affine_apply #map1(%c8) %12 = "foobar"(%11) : (affineint) -> affineint %13 = affine_apply #map1(%c9) %14 = "foobar"(%13) : (affineint) -> affineint 5) SSA dominance violated; no shifting if a shift is specified for the second statement. for %i = 0 to 7 { %x = "foo"(%i) : (affineint) -> affineint "bar"(%x) : (affineint) -> affineint } PiperOrigin-RevId: 214975731
2018-09-28 12:17:26 -07:00
}
return AffineMap::get(map.getNumDims(), map.getNumSymbols(), shiftedResults,
map.getRangeSizes());
Introduce loop body skewing / loop pipelining / loop shifting utility. - loopBodySkew shifts statements of a loop body by stmt-wise delays, and is typically meant to be used to: - allow overlap of non-blocking start/wait until completion operations with other computation - allow shifting of statements (for better register reuse/locality/parallelism) - software pipelining (when applied to the innermost loop) - an additional argument specifies whether to unroll the prologue and epilogue. - add method to check SSA dominance preservation. - add a fake loop pipeline pass to test this utility. Sample input/output are below. While on this, fix/add following: - fix minor bug in getAddMulPureAffineExpr - add additional builder methods for common affine map cases - fix const_operand_iterator's for ForStmt, etc. When there is no such thing as 'const MLValue', the iterator shouldn't be returning const MLValue's. Returning MLValue is const correct. Sample input/output examples: 1) Simplest case: shift second statement by one. Input: for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint } Output: #map0 = (d0) -> (d0 - 1) mlfunc @loop_nest_simple1() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint for %i0 = 1 to 7 { %1 = "foo"(%i0) : (affineint) -> affineint %2 = affine_apply #map0(%i0) %3 = "bar"(%2) : (affineint) -> affineint } %4 = affine_apply #map0(%c8) %5 = "bar"(%4) : (affineint) -> affineint return } 2) DMA overlap: shift dma.wait and compute by one. Input for %i = 0 to 7 { %pingpong = affine_apply (d0) -> (d0 mod 2) (%i) "dma.enqueue"(%pingpong) : (affineint) -> affineint %pongping = affine_apply (d0) -> (d0 mod 2) (%i) "dma.wait"(%pongping) : (affineint) -> affineint "compute1"(%pongping) : (affineint) -> affineint } Output #map0 = (d0) -> (d0 mod 2) #map1 = (d0) -> (d0 - 1) #map2 = ()[s0] -> (s0 + 7) mlfunc @loop_nest_dma() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = affine_apply #map0(%c0) %1 = "dma.enqueue"(%0) : (affineint) -> affineint for %i0 = 1 to 7 { %2 = affine_apply #map0(%i0) %3 = "dma.enqueue"(%2) : (affineint) -> affineint %4 = affine_apply #map1(%i0) %5 = affine_apply #map0(%4) %6 = "dma.wait"(%5) : (affineint) -> affineint %7 = "compute1"(%5) : (affineint) -> affineint } %8 = affine_apply #map1(%c8) %9 = affine_apply #map0(%8) %10 = "dma.wait"(%9) : (affineint) -> affineint %11 = "compute1"(%9) : (affineint) -> affineint return } 3) With arbitrary affine bound maps: Shift last two statements by two. Input: for %i = %N to ()[s0] -> (s0 + 7)()[%N] { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foo_bar"(%i) : (affineint) -> (affineint) "bar_foo"(%i) : (affineint) -> (affineint) } Output #map0 = ()[s0] -> (s0 + 1) #map1 = ()[s0] -> (s0 + 2) #map2 = ()[s0] -> (s0 + 7) #map3 = (d0) -> (d0 - 2) #map4 = ()[s0] -> (s0 + 8) #map5 = ()[s0] -> (s0 + 9) for %i0 = %arg0 to #map0()[%arg0] { %0 = "foo"(%i0) : (affineint) -> affineint %1 = "bar"(%i0) : (affineint) -> affineint } for %i1 = #map1()[%arg0] to #map2()[%arg0] { %2 = "foo"(%i1) : (affineint) -> affineint %3 = "bar"(%i1) : (affineint) -> affineint %4 = affine_apply #map3(%i1) %5 = "foo_bar"(%4) : (affineint) -> affineint %6 = "bar_foo"(%4) : (affineint) -> affineint } for %i2 = #map4()[%arg0] to #map5()[%arg0] { %7 = affine_apply #map3(%i2) %8 = "foo_bar"(%7) : (affineint) -> affineint %9 = "bar_foo"(%7) : (affineint) -> affineint } 4) Shift one by zero, second by one, third by two for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foobar"(%i) : (affineint) -> affineint } #map0 = (d0) -> (d0 - 1) #map1 = (d0) -> (d0 - 2) #map2 = ()[s0] -> (s0 + 7) %c9 = constant 9 : affineint %c8 = constant 8 : affineint %c1 = constant 1 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint %1 = "foo"(%c1) : (affineint) -> affineint %2 = affine_apply #map0(%c1) %3 = "bar"(%2) : (affineint) -> affineint for %i0 = 2 to 7 { %4 = "foo"(%i0) : (affineint) -> affineint %5 = affine_apply #map0(%i0) %6 = "bar"(%5) : (affineint) -> affineint %7 = affine_apply #map1(%i0) %8 = "foobar"(%7) : (affineint) -> affineint } %9 = affine_apply #map0(%c8) %10 = "bar"(%9) : (affineint) -> affineint %11 = affine_apply #map1(%c8) %12 = "foobar"(%11) : (affineint) -> affineint %13 = affine_apply #map1(%c9) %14 = "foobar"(%13) : (affineint) -> affineint 5) SSA dominance violated; no shifting if a shift is specified for the second statement. for %i = 0 to 7 { %x = "foo"(%i) : (affineint) -> affineint "bar"(%x) : (affineint) -> affineint } PiperOrigin-RevId: 214975731
2018-09-28 12:17:26 -07:00
}
//===----------------------------------------------------------------------===//
// CFG function elements.
//===----------------------------------------------------------------------===//
/// Add new basic block and set the insertion point to the end of it. If an
/// 'insertBefore' basic block is passed, the block will be placed before the
/// specified block. If not, the block will be appended to the end of the
/// current function.
BasicBlock *CFGFuncBuilder::createBlock(BasicBlock *insertBefore) {
BasicBlock *b = new BasicBlock();
// If we are supposed to insert before a specific block, do so, otherwise add
// the block to the end of the function.
if (insertBefore)
function->getBlocks().insert(CFGFunction::iterator(insertBefore), b);
else
function->push_back(b);
setInsertionPoint(b);
return b;
}
/// Create an operation given the fields represented as an OperationState.
OperationInst *CFGFuncBuilder::createOperation(const OperationState &state) {
SmallVector<CFGValue *, 8> operands;
operands.reserve(state.operands.size());
for (auto elt : state.operands)
operands.push_back(cast<CFGValue>(elt));
auto *op = OperationInst::create(state.location, state.name, operands,
state.types, state.attributes, context);
block->getOperations().insert(insertPoint, op);
return op;
}
//===----------------------------------------------------------------------===//
// Statements.
//===----------------------------------------------------------------------===//
/// Create an operation given the fields represented as an OperationState.
OperationStmt *MLFuncBuilder::createOperation(const OperationState &state) {
SmallVector<MLValue *, 8> operands;
operands.reserve(state.operands.size());
for (auto elt : state.operands)
operands.push_back(cast<MLValue>(elt));
auto *op = OperationStmt::create(state.location, state.name, operands,
state.types, state.attributes, context);
block->getStatements().insert(insertPoint, op);
return op;
}
/// Create an operation given the fields.
OperationStmt *MLFuncBuilder::createOperation(Location *location,
OperationName name,
ArrayRef<MLValue *> operands,
ArrayRef<Type *> types,
ArrayRef<NamedAttribute> attrs) {
auto *op = OperationStmt::create(location, name, operands, types, attrs,
getContext());
block->getStatements().insert(insertPoint, op);
return op;
}
ForStmt *MLFuncBuilder::createFor(Location *location,
ArrayRef<MLValue *> lbOperands,
AffineMap lbMap,
ArrayRef<MLValue *> ubOperands,
AffineMap ubMap, int64_t step) {
auto *stmt =
ForStmt::create(location, lbOperands, lbMap, ubOperands, ubMap, step);
block->getStatements().insert(insertPoint, stmt);
return stmt;
}
ForStmt *MLFuncBuilder::createFor(Location *location, int64_t lb, int64_t ub,
int64_t step) {
auto lbMap = AffineMap::getConstantMap(lb, context);
auto ubMap = AffineMap::getConstantMap(ub, context);
return createFor(location, {}, lbMap, {}, ubMap, step);
}
IfStmt *MLFuncBuilder::createIf(Location *location,
ArrayRef<MLValue *> operands, IntegerSet *set) {
auto *stmt = IfStmt::create(location, operands, set);
block->getStatements().insert(insertPoint, stmt);
return stmt;
}