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//===- ConvertSimQuant.cpp - Converts simulated quant ops------------------===//
//
// 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/Dialect/QuantOps/FakeQuantSupport.h"
#include "mlir/Dialect/QuantOps/Passes.h"
#include "mlir/Dialect/QuantOps/QuantOps.h"
#include "mlir/Dialect/QuantOps/UniformSupport.h"
#include "mlir/IR/Attributes.h"
#include "mlir/IR/PatternMatch.h"
#include "mlir/IR/StandardTypes.h"
#include "mlir/Pass/Pass.h"
using namespace mlir;
using namespace mlir::quant;
namespace {
class ConvertSimulatedQuantPass
: public FunctionPass<ConvertSimulatedQuantPass> {
public:
void runOnFunction() override;
};
} // end anonymous namespace
/// 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) {}
PatternMatchResult 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 Pattern::matchFailure();
}
return Pattern::matchSuccess();
}
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().getSExtValue(),
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().getSExtValue(),
fqOp.axis().getSExtValue(), min, max,
fqOp.narrow_range(), expressedType,
fqOp.is_signed());
}
};
void ConvertSimulatedQuantPass::runOnFunction() {
bool hadFailure = false;
OwningRewritePatternList patterns;
auto func = getFunction();
auto ctx = func.getContext();
patterns.insert<ConstFakeQuantRewrite, ConstFakeQuantPerAxisRewrite>(
ctx, &hadFailure);
applyPatternsGreedily(func, patterns);
if (hadFailure)
signalPassFailure();
}
std::unique_ptr<OpPassBase<FuncOp>>
mlir::quant::createConvertSimulatedQuantPass() {
return std::make_unique<ConvertSimulatedQuantPass>();
}
static PassRegistration<ConvertSimulatedQuantPass>
pass("quant-convert-simulated-quantization",
"Converts training-time simulated quantization ops to corresponding "
"quantize/dequantize casts.");
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