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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
/// Rewrites ConstFakeQuant into a qbarrier/dbarrier pair.
class ConstFakeQuantRewrite : public RewritePattern {
public:
bool *hadFailure;
ConstFakeQuantRewrite(MLIRContext *context, bool *hadFailure)
: RewritePattern(ConstFakeQuant::getOperationName(), 1, context),
hadFailure(hadFailure) {}
PatternMatchResult matchAndRewrite(Operation *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 matchFailure();
}
return matchSuccess();
}
bool failableRewrite(Operation *op, PatternRewriter &rewriter) const {
auto fqOp = cast<ConstFakeQuant>(op);
auto converter =
ExpressedToUniformQuantizedConverter::forInputType(fqOp.getType());
if (!converter) {
return (op->emitError("unsupported quantized type conversion"), true);
}
UniformQuantizedType uniformElementType = fakeQuantAttrsToType(
fqOp.getLoc(), fqOp.num_bits().getSExtValue(),
fqOp.min().convertToFloat(), fqOp.max().convertToFloat(),
fqOp.narrow_range(), converter.expressedType, fqOp.is_signed());
if (!uniformElementType) {
// Note that the fakeQuantAttrsToType will have emitted the error.
return true;
}
Type quantizedType = converter.convert(uniformElementType);
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,
fqOp.inputs());
rewriter.replaceOpWithNewOp<DequantizeCastOp>(op, converter.inputType,
qbarrier.getResult());
return false;
}
};
void ConvertSimulatedQuantPass::runOnFunction() {
bool hadFailure = false;
OwningRewritePatternList patterns;
auto func = getFunction();
auto *context = &getContext();
patterns.insert<ConstFakeQuantRewrite>(context, &hadFailure);
applyPatternsGreedily(func, patterns);
if (hadFailure)
signalPassFailure();
}
FunctionPassBase *mlir::quant::createConvertSimulatedQuantPass() {
return new ConvertSimulatedQuantPass();
}
static PassRegistration<ConvertSimulatedQuantPass>
pass("quant-convert-simulated-quantization",
"Converts training-time simulated quantization ops to corresponding "
"quantize/dequantize casts.");
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