Files
clang-p2996/mlir/lib/Dialect/Quant/Transforms/ConvertSimQuant.cpp
River Riddle 3fffffa882 [mlir][Pattern] Add a new FrozenRewritePatternList class
This class represents a rewrite pattern list that has been frozen, and thus immutable. This replaces the uses of OwningRewritePatternList in pattern driver related API, such as dialect conversion. When PDL becomes more prevalent, this API will allow for optimizing a set of patterns once without the need to do this per run of a pass.

Differential Revision: https://reviews.llvm.org/D89104
2020-10-26 18:01:06 -07:00

141 lines
4.9 KiB
C++

//===- ConvertSimQuant.cpp - Converts simulated quant ops------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
#include "PassDetail.h"
#include "mlir/Dialect/Quant/FakeQuantSupport.h"
#include "mlir/Dialect/Quant/Passes.h"
#include "mlir/Dialect/Quant/QuantOps.h"
#include "mlir/Dialect/Quant/UniformSupport.h"
#include "mlir/IR/StandardTypes.h"
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
using namespace mlir;
using namespace mlir::quant;
namespace {
struct ConvertSimulatedQuantPass
: public QuantConvertSimulatedQuantBase<ConvertSimulatedQuantPass> {
void runOnFunction() override;
};
/// Base class rewrites ConstFakeQuant into a qbarrier/dbarrier pair.
template <typename ConcreteRewriteClass, typename FakeQuantOp>
class FakeQuantRewrite : public OpRewritePattern<FakeQuantOp> {
public:
using OpRewritePattern<FakeQuantOp>::OpRewritePattern;
FakeQuantRewrite(MLIRContext *ctx, bool *hadFailure)
: OpRewritePattern<FakeQuantOp>(ctx), hadFailure(hadFailure) {}
LogicalResult matchAndRewrite(FakeQuantOp op,
PatternRewriter &rewriter) const override {
// TODO: If this pattern comes up more frequently, consider adding core
// support for failable rewrites.
if (failableRewrite(op, rewriter)) {
*hadFailure = true;
return failure();
}
return success();
}
private:
bool *hadFailure;
bool failableRewrite(FakeQuantOp op, PatternRewriter &rewriter) const {
auto converter = ExpressedToQuantizedConverter::forInputType(op.getType());
if (!converter) {
return (op.emitError("unsupported quantized type conversion"), true);
}
QuantizedType elementType =
static_cast<const ConcreteRewriteClass *>(this)
->convertFakeQuantAttrsToType(op, converter.expressedType);
if (!elementType) {
// Note that the fakeQuantAttrsToType will have emitted the error.
return true;
}
Type quantizedType = converter.convert(elementType);
assert(quantizedType &&
"Converter accepted a type that it did not convert");
// TODO: Map to a qbarrier with an attribute like [Forced] to signal that
// this is a forced/hard-coded constraint.
auto qbarrier = rewriter.create<QuantizeCastOp>(op.getLoc(), quantizedType,
op.inputs());
rewriter.replaceOpWithNewOp<DequantizeCastOp>(op, converter.inputType,
qbarrier.getResult());
return false;
}
};
class ConstFakeQuantRewrite
: public FakeQuantRewrite<ConstFakeQuantRewrite, ConstFakeQuant> {
public:
using BaseRewrite = FakeQuantRewrite<ConstFakeQuantRewrite, ConstFakeQuant>;
ConstFakeQuantRewrite(MLIRContext *ctx, bool *hadFailure)
: BaseRewrite(ctx, hadFailure) {}
QuantizedType convertFakeQuantAttrsToType(ConstFakeQuant fqOp,
Type expressedType) const {
return fakeQuantAttrsToType(
fqOp.getLoc(), fqOp.num_bits(), fqOp.min().convertToFloat(),
fqOp.max().convertToFloat(), fqOp.narrow_range(), expressedType,
fqOp.is_signed());
}
};
class ConstFakeQuantPerAxisRewrite
: public FakeQuantRewrite<ConstFakeQuantPerAxisRewrite,
ConstFakeQuantPerAxis> {
public:
using BaseRewrite =
FakeQuantRewrite<ConstFakeQuantPerAxisRewrite, ConstFakeQuantPerAxis>;
ConstFakeQuantPerAxisRewrite(MLIRContext *ctx, bool *hadFailure)
: BaseRewrite(ctx, hadFailure) {}
QuantizedType convertFakeQuantAttrsToType(ConstFakeQuantPerAxis fqOp,
Type expressedType) const {
SmallVector<double, 4> min, max;
min.reserve(fqOp.min().size());
max.reserve(fqOp.max().size());
for (auto m : fqOp.min())
min.push_back(m.cast<FloatAttr>().getValueAsDouble());
for (auto m : fqOp.max())
max.push_back(m.cast<FloatAttr>().getValueAsDouble());
return fakeQuantAttrsToType(fqOp.getLoc(), fqOp.num_bits(), fqOp.axis(),
min, max, fqOp.narrow_range(), expressedType,
fqOp.is_signed());
}
};
} // namespace
void ConvertSimulatedQuantPass::runOnFunction() {
bool hadFailure = false;
OwningRewritePatternList patterns;
auto func = getFunction();
auto ctx = func.getContext();
patterns.insert<ConstFakeQuantRewrite, ConstFakeQuantPerAxisRewrite>(
ctx, &hadFailure);
applyPatternsAndFoldGreedily(func, std::move(patterns));
if (hadFailure)
signalPassFailure();
}
std::unique_ptr<OperationPass<FuncOp>>
mlir::quant::createConvertSimulatedQuantPass() {
return std::make_unique<ConvertSimulatedQuantPass>();
}